• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.74-81
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• 1995

Several non-manifold data structures have been compared, which are radial-edge data structure, partial-face data structure, vertex-based data structure, and Yamaguchi's data structrue. All the entities in the data structures are classified into common entities and special entities. The entities are also classified as model entities, primitive entities bounding entities, and coupling entities. The four data structures for nonmanifold solid modelers are compared in terms of accessing efficiency, storage requirements, and inclusion of circulation. The results of comparison will serve as the basis to develope a nonmanifold modeler.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.192-199
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• 2016

Mixed and augmented reality technique deals with mixing content between real world and virtual world containing augmented reality and augmented virtuality excluding of pure real and pure virtual world. In mixed and augmented reality, if a live actor and entity moving in real world can be embedded more naturally in 3D virtual world, various advanced applications such 3D tele-presence, 3D virtual experience education and etc can be serviced. Therefore, in this paper, we propose a standard model which is supporting to embed the live actor and entity into 3D virtual space, and to interact with each other. And also the natural embedding and interaction of live actor and entity can be performed based on the proposed model.

• Korean Journal of Cognitive Science
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• v.24 no.4
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• pp.301-321
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• 2013

For the task of sentence ordering, this paper attempts to utilize the Entity-Grid model, a type of entity-based modeling approach, as well as Latent Semantic analysis, which is based on vector space modeling, The task is well known as one of the fundamental tools used to measure text coherence and to enhance text generation processes. For the implementation of the Entity-Grid model, we attempt to use the syntactic roles of the nouns in the Korean text for the ordering task, and measure its impact on the result, since its contribution has been discussed in previous research. Contrary to the case of German, it shows a positive result. In order to obtain the information on the syntactic roles, we use a strategy of using Korean case-markers for the nouns. As a result, it is revealed that the cues can be helpful to measure text coherence. In addition, we compare the results with the ones of the LSA-based model, discussing the advantages and disadvantages of the models, and options for future studies.

• Journal of KIISE
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• v.43 no.2
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• pp.269-274
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• 2016

Named entity recognition is a process which extracts named entities in sentences and determines categories of the named entities. Previous studies on named entity recognition have primarily been used for supervised learning. For supervised learning, a large training corpus manually annotated with named entity categories is needed, and it is a time-consuming and labor-intensive job to manually construct a large training corpus. We propose a semi-supervised learning method to minimize the cost needed for training corpus construction and to rapidly enhance the performance of named entity recognition. The proposed method uses distance supervision for the construction of the initial training corpus. It can then effectively remove noise sentences in the initial training corpus through the use of an active bagging method, an ensemble method of bagging and active learning. In the experiments, the proposed method improved the F1-score of named entity recognition from 67.36% to 76.42% after active bagging for 15 times.

• Corrosion Science and Technology
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• v.15 no.6
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• pp.281-289
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• 2016

The effect of nitrogen on the electrochemical corrosion and nanomechanical behaviors of martensitic stainless steel was examined using potentiodynamic polarization and nanoindentation test methods. The results indicate that partial replacement of carbon with nitrogen effectively improved the passivation and pitting corrosion resistance of conventional high-carbon and high- chromium martensitic steels. Post-test observation of the samples after a potentiodynamic test revealed a severe pitting attacks in conventional martensitic steel compared with nitrogen- containing martensitic stainless steel. This was shown to be due to (i) microstructural refinement results in retaining a high-chromium content in the matrix, and (ii) the presence of reversed austenite formed during the tempering process. Since nitrogen addition also resulted in the formation of a $Cr_2N$ phase as a process of secondary hardening, the hardness of the nitrogen- containing steel is slightly higher than the conventional martensitic stainless steel under tempered conditions, even though the carbon content is lowered. The added nitrogen also improved the wear resistance of the steel as the critical load (Lc2) is less, along with a lower scratch friction coefficient (SFC) when compared to conventional martensitic stainless steel such as AISI 440C.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.47-52
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• 2018

Named Entity Recognition is a system that extracts entity names such as Persons(PS), Locations(LC), and Organizations(OG) that can have a unique meaning from a document and determines the categories of extracted entity names. Recently, Bi-LSTM-CRF, which is a combination of CRF using the transition probability between output data from LSTM-based Bi-LSTM model considering forward and backward directions of input data, showed excellent performance in the study of object name recognition using deep-learning, and it has a good performance on the efficient embedding vector creation by character and word unit and the model using CNN and LSTM. In this research, we describe the Bi-LSTM-CNN-CRF model that enhances the features of the Korean named entity recognition system and propose a method for constructing the traditional culture corpus. We also present the results of learning the constructed corpus with the feature augmentation model for the recognition of Korean object names.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.45-52
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• 2019

In recent years, there has been a demand for a residential supply model that can actively and flexibly cope with various housing demands in the changing paradigm of public rental housing. This study focuses on the two-step supply system that has been studied in Japan. It was used to examine and analyze cases to recommend a supply plan that can be used for domestic public rental housing. In more detail, the literature review of the two-step supply system discloses that four types by supply methods (A-1, A-2, B-2, and C-2) and four types of relationship (construction and management combine entities type, management entity type, construction entity type, a separated entity type) can be categorized. In addition, from the actual case study, it revealed that the way of linking and supplying activities among the entity can have a great influence on "ease of supply (supply)", "diversity of housing demand (diversity)," and "quality of construction (construction)". "Ease of supply (supply)" refers to whether the construction entity is separated, and the owner is a manager. "Diversity" refers to whether the management subject is separated, and if the owner is also the constructor or the manager. "Construction" is whether the management entity is connected and managed by the management entity and can be evaluated in "Good", "Middle", and "Bad" level. As a summary, even if the existing public rental housing in Korea can be separated into a skeleton and infill system, the result suggested that it has a limitation on response to residential demand. In addition, the paper was able to propose an improved plan to make the infill as a secondary operator.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.157-163
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• 2015

XML has become one of the most influential standard language for representing and exchanging data on internet. However, XML itself has a ability to represent a logical structure for storing and managing data, it is inadequate to use as a conceptual modeling tool because of its complexity for representing the document structures. In this paper, we propose the graphical form of conceptual modeling techniques for representing the structure of the XML schema documents using an extended entity relationship diagram. For this, extended entity relationship model is presented for representing the XML schema structure, transformation rules are presented for transforming extended entity relationship model into XML schema document to show the completeness of the proposed model.

• Journal of KIBIM
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• v.5 no.2
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• pp.46-54
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• 2015

Vision-based tracking has been proposed as a means to efficiently track a large number of construction resources operating in a congested site. In order to obtain 3D coordinates of an object, it is necessary to employ stereo-vision theories. Detecting and tracking of multiple objects require an entity matching process that finds corresponding pairs of detected entities across the two camera views. This paper proposes an efficient way of entity matching for tracking of construction workers. The proposed method basically uses epipolar geometry which represents the relationship between the two fixed cameras. Each pixel coordinate in a camera view is projected onto the other camera view as an epipolar line. The proposed method finds the matching pair of a worker entity by comparing the proximity of the all detected entities in the other view to the epipolar line. Experimental results demonstrate its suitability for automated entity matching for 3D vision-based tracking of construction workers.

• Journal of KIISE:Software and Applications
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• v.35 no.7
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• pp.405-416
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• 2008

To overcome the limitation of keyword-based integrated search, this study shows entity-centric integrated search method using URI scheme. Our system generates entity pages in ways of analyzing user's keyword and instances matched with it, selecting optimal entity type, and calling unit services simultaneously. Topic information extracted from articles is propagated to persons, institutions, and locations by reasoning for providing topic-centric information. With comparative experiments based on search results and usability tests, we proved that this approach is superior to keyword-based integrated search served by CiteSeer and Google Scholar.