• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.4
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• pp.46-51
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• 2012

Injection pressure, an important factor in filling process, should be minimized to enhance injection molding quality. Injection pressure can be controlled by valve gate open timing. In this work, we decided the valve gate open timing to minimize the injection pressure. To solve this design problem, we integrated MAPS-3D (Mold Analysis and Plastic Solution-3Dimension), a commercial injection molding CAE tool, to PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration, and Design Optimization) tool using the file parsing method. In order to reduce computational cost, we performed an approximate optimization using meta-models that replaced expensive computer simulations. At first, we carried out DOE (Design of Experiments) using OLHD (Optimal Latin Hypercube Design) available in PIAnO. Then, we built Kriging models using the simulation results at the sampling points. Finally, we used micro GA (Genetic Algorithm) available in PIAnO. Using the proposed design approach, the injection pressure has been reduced by 13.7% compared to the initial one. This design result clearly shows the validity of the proposed design approach.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.529-539
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• 2012

Testing is an important part of quality control in the software life cycle. One of the most important issues in the software testing is to generate the appropriate test cases. Generally, the software can be tested based on product understanding. However, it is not easy to create test cases that can ensure the quality of the software according to the clients' request. Especially, it is difficult to create test cases for abnormal or exceptional situations. In this paper, we present a novel approach to generate exceptional test cases at the design level of UML model. Furthermore, we describe the results of actual experiment where DAB(Digital Audio Broadcasting) parsing program is tested with previous method and also with the proposed method. The results implies that our proposed method of generating test cases for exceptional situations detect more faults than that of previous method by 7.08%.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.36-46
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• 2007

This paper presents an automated English scoring system designed to help non-native speakers of English, Korean-speaking learners in particular. The system is developed to help the 3rd grade students in junior high school improve their English grammar skills. Without human's efforts, the system identifies grammar errors in English sentences, provides feedback on the detected errors, and scores the sentences. Detecting grammar errors in the system requires implementing a special type of rules in addition to the rules to parse grammatical sentences. Error production rules are implemented to analyze ungrammatical sentences and recognize syntactic errors. The rules are collected from the junior high school textbooks and real student test data. By firing those rules, the errors are detected followed by setting corresponding error flags, and the system continues the parsing process without a failure. As the final step of the process, the system scores the student sentences based on the errors detected. The system is evaluated with real English test data produced by the students and the answers provided by human teachers.

• Korean Journal of Cognitive Science
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• v.19 no.3
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• pp.223-255
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• 2008

In this paper, we introduce an automatic system of scoring English essays. The system is comprised of three main components: a spelling checker, a grammar checker and a lexical cohesion checker. We have used such resources as WordNet, Link Grammar/parser and Roget's thesaurus for these components. The usefulness of an automatic scoring system depends on its reliability. To measure reliability, we compared the results of automatic scoring with those of manual scoring, on the basis of the Kappa statistics and the Multi-facet Rasch Model. The statistical data obtained from the comparison showed that the scoring system is as reliable as professional human graders. This system deals with textual units rather than sentential units and checks not only formal properties of a text but also its contents.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.426-429
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• 2007

CrossRef operates a cross-publisher citation linking system based on the DOI(R) global identifier. The number of organization building a reference citations linking structure through CrossRef is increasing. This paper concentrates on developing a Citation Matcher Solution to effectively build the reference linking structure. Citation Matcher automatically builds and processes the reference citation and identifier mapping which used to be handled manually. After the copy & paste of the reference citation, analyzation is processed to parse the journal title, author name, volume, issue, and start pages from the free style text. CrossRef, PubMed, and YesKISTI's identifiers are collected by through a standardized method. Renovation of the building process for domestic scholastic resources' reference linking and matching will be made possible by using a Citation Matcher. The connection between resources and seamless access for the electronic full-text will enhance the usability.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1601-1614
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• 2008

The number of web service users has been increased rapidly as existing services are changed into the web-based internet applications. Therefore, it is necessary for us to use web log pre-processing technique to detect attacks on diverse web service transactions and it is also possible to extract web mining information. However, existing mechanisms did not provide efficient pre-processing procedures for a huge volume of web log data. In this paper, we proposed both a field based parsing and a high-speed log indexing mechanism based on the suggested B-tree Index Vector structure for performance enhancement. In experiments, the proposed mechanism provides an efficient web log pre-processing and search functions with a session classification. Therefore it is useful to enhance web attack detection function.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.268-277
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• 2003

A document type definition(DTD) which defines tags for a document is a XML document grammar that defines syntactic structure of a document. An XML document keeps the rules and must be parsed to check validation. To parse XML document, the deterministic parsing method of programming language is irrelevant because it does not satisfy the definition of deterministic content model in element declaration. In this paper, we consider editing of a valid XML document in syntax-directed editing environment, and we suggest the internal storage representations of syntax in DTD and theirs algorithms. The consequence is that a syntactic structure of textual DTD is transformed into graph and table structures. The table structure of DTD is interpreted the context free grammar which has attribute values and is used in syntax-directed editor for XML. We called this the XML abstract grammar and showed generated results and examples.

• The KIPS Transactions:PartD
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• v.14D no.6
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• pp.623-632
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• 2007

GML is a markup language presented as exchange standard for geographic information by the OGC(Open GIS Consortium). In spatial network databases, researches for supporting GML(Geographic Markup Language) can be divided into the parsing, the storing and the retrieval of GML documents. Among them, the study on the storage of GML documents is essential for their efficient retrieval. However there is little research on the storing of GML documents whereas there have been a lot of researches on the storing of n documents. Because the storage schema designed for XML documents are not appropriate for geographic information, we, in this paper, propose three storage schema for efficiently storing GML documents including geographic information in order to solve the problem that the XML storage schema store duplicate data and need to search many tables for obtaining elements. In addition, we design and implement a low-level storage manager which can store GML documents using the proposed GML storage schema.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.459-472
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• 2011

The vast number of biomedical literature is an important source of biomedical interaction information discovery. However, it is complicated to obtain interaction information from them because most of them are not easily readable by machine. In this paper, we present a method for extracting biomedical interaction information assuming that the biomedical Named Entities (NEs) are already identified. The proposed method labels all possible pairs of given biomedical NEs as INTERACTION or NO-INTERACTION by using a Maximum Entropy (ME) classifier. The features used for the classifier are obtained by applying various NLP techniques such as POS tagging, base phrase recognition, parsing and predicate-argument recognition. Especially, specific verb predicates (activate, inhibit, diminish and etc.) and their biomedical NE arguments are very useful features for identifying interactive NE pairs. Based on this, we devised a twostep method: 1) an interaction verb extraction step to find biomedically salient verbs, and 2) an argument relation identification step to generate partial predicate-argument structures between extracted interaction verbs and their NE arguments. In the experiments, we analyzed how much each applied NLP technique improves the performance. The proposed method can be completely improved by more than 2% compared to the baseline method. The use of external contextual features, which are obtained from outside of NEs, is crucial for the performance improvement. We also compare the performance of the proposed method against the co-occurrence-based and the rule-based methods. The result demonstrates that the proposed method considerably improves the performance.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.655-667
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• 2014

This paper has identified five major categories of the T2D patients' concerns based on an online forum where the patients voluntarily verbalized their naturally occurring emotional reactions and concerns related to T2D. We have emphasized the fact that the lexical and phrasal analysis brought to the forefront the prevailing negative reactions and desires for clear information, professional advice, and emotional support. This study used lexical and phrasal analysis based on text-mining tools to estimate the potential of using a large sample of patient conversation of a specific disease posted on the internet for clinical features and patients' emotions. As a result, the study showed that quantitative analysis based on text-mining is a viable method of generalizing the psychological concerns and features of T2D patients.