• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.23-30
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• 2004

Ontologies play an important role in the Semantic Web by providing well-defined meaning to ontology consumers. But as the ontologies are authored in a bottom-up distributed mimer, a large number of overlapping ontologies are created and used for the similar domains. Ontology sharing and reuse have become a distinguished topic, and ontology merging and alignment are the solutions for the problem. Ontology merging and alignment algorithms previously proposed detect conflicts between concepts by making use of only local syntactic information of concept names. And they depend only on a semi-automatic approach, which makes ontology engineers tedious. Consequently, the quality of merging and alignment tends to be unsatisfying. To remedy the defects of the previous algorithms, we propose a new algorithm for ontology merging and alignment which uses local and global semantic set of a concept. We evaluated our algorithm with several pairs of ontologies written in OWL, and achieved around 91% of precision in merging and alignment. We expect that, with the widespread use of web ontology, the need for ontology sharing and reuse ill become higher, and our proposed algorithm can significantly reduce the time required for ontology development. And also, our algorithm can easily be applied to various fields such as ontology mapping where semantic information exchange is a requirement.

• IE interfaces
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• v.25 no.1
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• pp.40-51
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• 2012

Today, many manufacturing companies realize that collaboration is crucial for their survival. Especially, in the perspective of quality, the importance of collaboration is emphasized because economic loss increases exponentially while defective parts go through the process in supply chain. However, the manufacturing companies are facing two main difficulties in implementing collaborative relationships with their suppliers. First, it is difficult for the suppliers to produce reliable products due to their obsolete facilities. The problem gets worse for second- or third-tire vendors. Second, the companies experience the lack of universally understandable set of terminology and effective methodologies for knowledge representation. Ontology is one of the best approaches to expressing and processing a domain knowledge. In this paper, we propose the manufacturing ontology-based quality prediction framework to represent and share the knowledge of industrial environment and to predict product quality in manufacturing processes. In addition, we develop the ontology-based quality prediction system based on the proposed framework. We carried out a series of experiments for an injection molding process at an automotive part supplier. The experimental results demonstrated that the proposed framework and system can be successfully applicable in manufacturing industry.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.22-31
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• 2006

This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.

• Korean Journal of Artificial Intelligence
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• v.5 no.2
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• pp.1-14
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• 2017

This research proposes a method to provide visually impaired persons with better medical services and to mitigate their difficulties in taking medicines in their daily lives. Normally, pharmaceutical information are distributed in a form of printed materials, but it is not accessible by those who are visually impaired. Since persons who are visually impaired by accidents or diseases are required to take more types of medicines compared to other handicapped persons, and thus it is an important matter to let them have appropriate medicines at the right time. Although there are several web sites which are run by the Ministry of Health and Welfare providing pharmaceutic information, the information on those web sites are duplicated and some of the menus are similar, and thus giving users difficulties and discomfort in finding appropriate pharmaceutical information. Since ontology can define and describe the resource in an information system more clearly, in this research, an ontology consists of pharmaceutical information and knowledge on medicines is constructed to give patients more precise information more efficiently. Also, a service in which users can have voice guidance on pharmaceutical information retrieve from the ontology-based information system by contacting RFID sticker on the medicine to the reader.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.42-48
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• 2012

Since the Semantic Web emerged, ontology has been widely used in web environment. Even ontologies belong to the same domain, they may contain same meaning different words, or different meaning same words according to their development background and the type of utilization. In order to share and reuse the ontologies, ontology mapping is required. This paper presents a ontology mapping method that consists of the initial process of multi-level mapping based on lexical information, and the second mapping process using the lexical results and structural similarity. Mapping performance was improved by additionally expanding structural information of blank nodes, which have no lexical information. Through experiments, our method achieved 86.38% in F1-measure.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.179-185
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• 2017

Accident analysis is an essential process to make basic data for accident prevention. Most researches depend on survey data and accident statistics to analyze accidents, but these kinds of data are not sufficient for systematic and detailed analysis. We, in this paper, propose an accident classification model that extracts task type, original cause materials, accident type, and the number of deaths from accident reports. The classification model is a support vector machine (SVM) with word occurrence features, and these features are selected based on mutual information. Experiment shows that the proposed model can extract task type, original cause materials, accident type, and the number of deaths with almost 100% accuracy. We also develop an accident ontology to express the information extracted by the classification model. Finally, we illustrate how the proposed classification model and ontology effectively works for the accident analysis. The classification model and ontology are expected to effectively analyze various accidents.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.1
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• pp.19-29
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• 2011

The u-Healthcare system, a new paradigm, provides healthcare and medical service anytime, anywhere in daily life using wired and wireless networks. It only doesn't reach u-Hospital at home, to manage efficient personal health in fitness space, it is essential to feedback process through measuring and analyzing a personal vital signs. MBAN(Medical Body Area Network) is a core of this technology. MBAN, a new paradigm of the u-Healthcare system, can provide healthcare and medical service anytime, anywhere on real time in daily life using u-sensor networks. In this paper, an ontology-based context-awareness in MBAN proposed system development methodology. Accordingly, ontology-based context awareness system on MBAN to Elderly/severe patients/aged/, with measured respiratory rate/temperature/pulse and vital signs having small variables through u-sensor network in real-time, discovered abnormal signs and emergency situations which may happen to people at sleep or activity, alarmed and connected with members of a family or medical emergency alarm(Emergency Call) and 119 system to avoid sudden accidents for early detection. Therefore, We have proposed that accuracy of biological signal sensing and the confidence of ontology should be inspected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.415-421
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• 2008

The increasing interest in ontologies is driven by the large volumes of information now available as well as by the increasing complexity and diversity of this information. These trends have also increased interest in automating many activities that were traditionally performed manually. We are currently engaged in this paper that have realized benefits in productivity and clarity by utilizing UML class diagrams to develop and to display complex OWL ontologies. UML has many features, such as profiles, global modularity and extension mechanisms that are not generally available in most ontology languages. However, ontology languages have some features that UML does not support. Our paper identifies the similarities and differences between UML and the ontology languages RDF and OWL. To reconcile these differences, we propose a modification to the UML metamodel to address some of the most problematic differences.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.201-206
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• 2010

According to the ubiquitous technology development, managing of the warehouse system which stores and manages agriculture products is realized effectively. This paper proposes an ontology-based context aware system model for the purpose of storing and managing agricultural products using ubiquitous sensors to share and distribute information. In these days, owing to penetrating ubiquitous technologies into our way of life, the importance of information is increasing gradually. The importance of ontology in a domain is getting as well. Therefore, this paper focuses on describing to get data from ubiquitous devices such as sensors, and designs and build an ontology-based agricultural product warehouse model.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.117-124
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• 2019

This paper investigates how digital technology innovates the aesthetic ontology of film images. The modern civilization of computer and internet bring about the new ontology of film images. Digital hybrid image expands the contradictory combination of physical reality and filmic fantasy. It is inevitable to recount Walter Benjamin' s concept of mechanical reproduction in the age of digital cinema. The modern condition of image arts changes the concept of mechanical reproduction to the logic of digital configuration. In addition, computer simulation innovates the film aesthetics of montage to the aesthetics of digital collage. The technological and aesthetical development of computer simulation and internet network leads to the new ontology of digital hybrid images. This study suggests a new theoretic point that the aesthetic ontology of digital hybrid images leads to the expansion of filmic fantasy and expression.