• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.358-360
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• 2020

본 팀은 웹캠으로 촬영한 영상에서 원하는 물체를 선택하여 텍스처를 선택한 이미지의 스타일로 변환하는 프로젝트를 수행했다. 영상을 세그멘테이션하고 원하는 물체만을 원하는 텍스처로 변환하여 최종 아웃풋을 얻는다. 제안하는 네트워크는 물체를 다양한 스타일로 바꾸는 것이 가능한데, 이 중에서 이미지에 명화의 화풍을 입히는 것을 중점으로 하여 데모를 구현했다. 빠른 속도로 네트워크를 실행하기 위해 기존 연구들에 비디오 처리의 관점을 접목했다. 여러 프레임을 묶어 옵티컬 플로우를 생성하고, 첫 번째 프레임을 인스턴스 세그멘테이션한 후 마스크를 추출했다. 이후 마스크 영역만 뽑아낸 이미지를 새로운 입력으로 하여 스타일 트랜스퍼를 거치고, 이 첫번째 프레임과 나머지 프레임들의 옵티컬 플로우로 나머지 프레임들의 세그멘테이션과 스타일 트랜스퍼를 예측하여 다시 비디오 프레임으로 만들어 주었다. 본 알고리즘은 옵티컬 플로우 설정으로 네트워크의 계산량을 줄이며 속도를 개선했다. 빠른 데이터 처리로 사용자가 원하는 물체의 텍스쳐가 바뀔 수 있게 되었고, 이는 현실 세계가 실제로 바뀐 듯한 느낌을 들게 한다. 또한, 컴퓨터 비전에서 활발하게 연구되었던 분야를 AR로 끌어와 두 분야의 융합 가능성을 열었다. 현재 코로나의 영향으로 집에서 취미생활을 즐기는 인구가 많아졌다. 본 연구를 통해 많은 사람에게 집에서 쉽게 명화의 감성을 즐기고 느낄 수 있는 양질의 콘텐츠를 제공해주려 한다. 또한, 박물관과 미술관 등의 기관에서도 이 기술이 활용될 수 있다. 명화를 느낄 수 있는 다양한 콘텐츠를 이용하여 박물관이나 미술관의 홍보 효과도 기대할 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.21-29
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• 2012

We have proposed an ontology-based translation mashup system for foreigner to enjoy Korean cultural information without any language barrier(linguistic problem). In order to utilize public information, we use a mobile public information open API of Seoul metropolitan city. Google AJAX language API is used for translations of public information. We apply an ontology to minimize errors caused by the translations. For ontology modeling, we analyze the public information domain and define classes, relations and properties of cultural vocabulary ontology. We generate ontology instances for titles, places and sponsors which are the most frequently occurring translation errors. We compare the accuracy of translations through our experiment. Through the experimental results using the proposed ontology-based translation mashup system, we verify the validity of the system.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1011-1020
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• 2007

It is difficult to assemble independently developed software components because of discrepancies between their interfaces. In order to resolve such problem, we propose a new component model, Active Binding Technology, in which each component has its own independently-defined interface for service request that is revealed in its metadata, instead of passively following the interface of a service-providing component. This model Includes the use of the glue component, an interface mediating place, whose template code is automatically generated by reading in the metadata of the components to be combined. We also propose a runtime framework that holds the pool of component instances, completes the assembly of components in the manner of dependency injection, and performs middleware services and real-time system monitoring through glue components. In order to test the practical value of Active Binding Technology, we have made a tool, which supports the development and assembly of Active Binding components.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2676-2683
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• 2009

The objective of this thesis is to improve the quality of a software product based on the enhancement of a software design quality using a better error detecting method. Also, this thesis is based on a software design method called as MOA(Methodology for Object to Agents) which uses an ontology based ODES(A Method based on Ontology for Detecting Errors in the Software Design) model as a common information model. At this thesis, a new format of error detecting method was defined. The method is implemented during a transformation process from UML model to ODES model using a ODES model, a Inter-View Inconsistency Detection technique and a combination of ontologic property of consistency framework and related rules. Transformation process to ODES model includes lexicon analysis and meaning analysis of a software design using of multiple mapping table at algorithm for the generation of ODES model instance.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.33-38
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• 2018

In this study, we try to detect new attacks for vehicle by learning only one class. We use Car-Hacking dataset, an intrusion detection dataset, which is used to evaluate classification performance. The dataset are created by logging CAN (Controller Area Network) traffic through OBD-II port from a real vehicle. The dataset have four attack types. One class classification is one of unsupervised learning methods that classifies attack class by learning only normal class. When using unsupervised learning, it difficult to achieve high efficiency because it does not use negative instances for learning. However, unsupervised learning has the advantage for classifying unlabeled data, which are new attacks. In this study, we use one class classifier to detect new attacks that are difficult to detect using signature-based rules on network intrusion detection system. The proposed method suggests a combination of parameters that detect all new attacks and show efficient classification performance for normal dataset.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.137-149
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• 2004

A new software paradigm is required on the development of network and various service requirements. With this, many studies on a mobile agent have been made. For the execution of the mobile agent, migration is the most important factor that influences the performance of the mobile agent. In this paper we propose the method that leads to high migration efficiency in order to improve the performance. The features of our migration technique are as follows. First, the migration technique creates the dynamic itinerary that appropriately copes with the network conditions and the platform changes to improve the agent execution efficiency. Second, it perfecters an executed code to reduce the amount of the mobile data and reduces the execution time by instantiating the agent in advance. Third, it improves the execution efficiency by using the checkpoint-based recovery method that does not execute the agent again and recovers the process states even though the errors take place. Though the simulation we compare the proposed method with the existing methods. The simulation result shows that the proposed method outperform the existing methods in terms of migration.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.67-84
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• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• The Journal of Society for e-Business Studies
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• v.15 no.3
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• pp.1-23
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• 2010

It is crucially important to exchange and manage the financial information of an organization for the reason of complexity and diversity of information caused by its implicit information involved. Especially, according to the development of information technology, various approaches appeared to manage financial data of organization. For example, XBRL (Extensible Business Reporting Language) is one of the technologies dealing with the above criteria. Basically, XBRL is a business reporting language to define and exchange financial information, such as a financial statement of organization. XBRL is an international standard which enables the exchange of information between information providers and consumers by adding the tags involving the information of circumstantial factors of data. However, XBRL is not able to describe semantics because XBRL is fundamentally based on XML(Extensible Markup Language) having the purpose of expressing and structuring data. Therefore, this paper aims to enable semantic information to XBRL through the semantic technology. The objective of this paper is an ontologization of the knowledge to perform sharing, reusing, discovering, and inferring the knowledge described and conducted by XBRL. In order to achieve the above objective, this paper suggests the methodology for the ontologization of the category and instance document of XBRL. Furthermore, this paper points out the possibility of suggested methodology in a practical business through indicating the advantages of the knowledge described by XBRL.

• Spatial Information Research
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• v.22 no.1
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• pp.65-73
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• 2014

Recently indoor navigation with indoor map such as Indoor Google Maps is served. For the services, constructing indoor data are required. CityGML and IFC are widely used as standards for representing indoor data. The data models contains spatial information for the indoor visualization and analysis, but indoor navigation requires semantic and topological information like graph as well as geometry. For this reason, IndoorGML, which is a GML3 application schema and data model for representation, storage and exchange of indoor geoinformation, is under standardization of OGC. IndoorGML can directly describe geometric property and refer elements in external documents. Because a lot of data in CityGML or IFC have been constructed, a huge amount of construction time and cost for IndoorGML data will be reduced if CityGML can help generate data in IndoorGML. Thus, this paper suggest practical use of CityGML including deriving from and link to CityGML. We analyze relationships between IndoorGML and CityGML. In this paper, issues and solutions for linkage of IndoorGML and CityGML are addressed.