• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.10
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• pp.1193-1201
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• 1988

In this paper, we describe the syntactic and semantic parsing methods which use the case frames. The case structures based on obligatory cases of verbs. And, we use a small set of partial-garammar rules based on simple sentence to represent such case structures. Also, we enhance the efficiency by constructing independent procedure for particle classification and ambiguity resolution of major particle considering the importance of Japanese particle process in the generation. And we construct the generation table considering the combination possibility between the verbs and auxiliary verbs for processing the termination phrase. Therefore we can generate more natural translated sentence according to unique decision with information of syntactic analysis and simplify the generating process.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.1-9
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• 2006

The emergency lighting plan for underground space should be done with consideration of characteristics of the space. In terms of utilizing the Depthmap program from the Space Syntax theory, it is possible to analyze space quantitatively. Integration and intelligibility are major induces of this theory and we can use them as emergency lighting design parameters. For this study, human behaviors and survivor's evacuation routes in fire emergencies are analyzed through literature review. Based on those results, this study suggests the methodology of emergency lighting plan in underground space.

• Journal of IKEEE
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• v.20 no.3
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• pp.326-329
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• 2016

HEVC CABAC encoder performs binary arithmetic encoding after syntax elements are converted into binary values. Therefore, in HEVC CABAC decoder, binarized syntax elements from binary arithmetic decoder should be de-binarized into original syntax elements in the de-binarizer. In this paper, a HEVC CABAC de-binarizer architecture was proposed and implemented. It consists of a controller that analyzes and merges binarized syntax elements and an engine that converts merged binarized syntax elements into original syntax elements. The designed de-binarizer was described in Verilog HDL and it was synthesized and verified in 0.18um process technology. Its gate count and maximum operating frequency are 3,114 gates and 220 MHz, respectively.

• Cross-Cultural Studies
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• v.49
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• pp.1-32
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• 2017

This paper discusses the structural and meaning features of causative from/for V-ing constructions as complement and provides insight on their grammatical characteristics revealed from alternation between prepositions for and from in nonfinite V-ing complement clause constructions. Guided by empirical data, this paper demonstrates that there are three types of syntactic patterns classified by the main verbs in these constructions and that these three syntactic types are closely linked with the meaning. These classifications are supported by the passivizations and aspect. In addition, this paper suggests that the function of for and from followed by nonfinite V-ing clause should be treated as a preposition introducing nonfinite V-ing clauses.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.199-204
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• 2022

This study was carried out in an L2 writing class using machine translation. The aim of this study was to explore what types of errors are identified the most frequently in the Korean-to-English machine translation output and what causes those errors. The participants were seven EFL university students who completed three writing tasks throughout the semester. The findings of data analysis indicated that the most common errors were seen in sentence structure and mechanics, and those errors in the translated texts were caused by the errors in the Korean source texts.

• The Journal of Korean Association of Computer Education
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• v.18 no.4
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• pp.63-70
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• 2015

Program source code is a set of complex syntactic information which are expressed in text forms, and contains complex logical structures. Structural and logical complexity inside source code become barriers in applying visualization techniques shown in traditional big-data approaches when the volume of source code become over ten-thousand lines of code. This paper suggests a procedure for making visualization of structural characteristics in source code. For this purpose, this paper defines internal data structures as well as inter-procedural relationships among functions. The paper also suggests a means of outlining the structural characteristics of source code by visualizing the source codes with network forms The result of the research work can be used as a means of controling and understanding the massive volume of source code.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.235-242
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• 2021

In this work, we develop a Korean dependency parser based on a stack-pointer network that consists of a pointer network and an internal stack. The parser has an encoder and decoder and builds a dependency tree for an input sentence in a depth-first manner. The encoder of the parser encodes an input sentence, and the decoder selects a child for the word at the top of the stack at each step. Since the parser has the internal stack where a search path is stored, the parser can utilize information of previously derived subtrees when selecting a child node. Previous studies used only a grandparent and the most recently visited sibling without considering a subtree structure. In this paper, we introduce graph attention networks that can represent a previously derived subtree. Then we modify our parser based on the stack-pointer network to utilize subtree information produced by the graph attention networks. After training the dependency parser using Sejong and Everyone's corpus, we evaluate the parser's performance. Experimental results show that the proposed parser achieves better performance than the previous approaches at sentence-level accuracies when adopting 2-depth graph attention networks.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.642-652
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• 2009

In order to improve the performance of the existing relation extraction approaches, we propose a method for combining two pivotal concepts which play an important role in classifying semantic relationships between entities in text. Having built a composite kernel-based relation extraction system, which incorporates both entity features and syntactic structured information of relation instances, we define nine classes of lexical features and synthetically apply them to the system. Evaluation on the ACE RDC corpus shows that our approach boosts the effectiveness of the existing composite kernels in relation extraction. It also confirms that by integrating the three important features (entity features, syntactic structures and contextual lexical features), we can improve the performance of a relation extraction process.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.390-399
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• 2004

In this paper, we design and implement a multiple-view VoiceXML editor to improve editing efficiency of the VoiceXML. The VoiceXML multiple-view Editor uses a MVC framework to support multiple views and paradigm. Our multiple-view editor consists of Model. View and Controller using MVC framework. A model, core data structure. is constructed of abstract syntax tree and abstract grammar. A view. user interface. is formalized in unparsing rules and unparser. A controller. to control model and view. is made of command interpreter and tree handler. The VoiceXML multiple-view editor overcomes a drawbacks of existing XML editors by showing document structure and context concurrently. as well as document flows. Our VoiceXML multiple-view editor. which MVC framework has been applied, provides various editing views concurrently to users. Thereby. it supports efficient and convenient editing environments for voice-web documents to users and it guarantees transparency of editors. as various views have a same consistent model.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.984-989
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• 2005

This study aims to identify grammatical relations (GRs) in Korean sentences. The key task is to find the GRs in sentences in terms of such GR categories as subject, object, and adverbial. To overcome this problem, we are fared with the many ambiguities. We propose a statistical model, which resolves the grammatical relational ambiguity first, and then finds correct noun phrases (NPs) arguments of given verb phrases (VP) by using the probabilities of the GRs given NPs and VPs in sentences. The proposed model uses the characteristics of the Korean language such as distance, no-crossing and case property. We attempt to estimate the probabilities of GR given an NP and a VP with Support Vector Machines (SVM) classifiers. Through an experiment with a tree and GR tagged corpus for training the model, we achieved an overall accuracy of $84.8\%,\;94.1\%,\;and\;84.8\%$ in identifying subject, object, and adverbial relations in sentences, respectively.