• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.426-431
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• 1997

Features are well recognized to play an important role for the integration of ACD and CAPP. Majority of pervious works for the feature recognition for prismatic part is based on 3D solid model. But in real factories, 2D drawing are used more than 3D drawings. In this paper, we develope an algorithm of the feature recognition on prismatic parts in 2D drawings, using by the graph method and the heuristic algorithm. Previous algorithms have some conflicts at feature interaction. In this paper, elements are grouped into connection by the graph method. Then features are recognized by using these grouped elements and their relationships of front and side-view. For resolving the problem of feature interaction, the element graphs are modified by an deloped algorithm. This algorithm is applied to a CAPP system for milling process planning.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.105-110
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• 2014

Feature-oriented software product line engineering is to develop various products by developing product line core assets in terms of features and composing those features. However, the developed product may not behave correctly if the feature interaction problem has not be properly taken into account during the feature composition. This paper proposes techniques for identifying and modularizing undesirable feature interactions effectively. The scientific calculator product line is used for evaluating the applicability of the proposed method.

• English Language & Literature Teaching
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• v.9 no.spc
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• pp.185-208
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• 2003

The purpose of this paper is to examine some of the theories concerning socioaffective strategies, to analyze the dialogues of the students negotiating for meaning of a reading material and to suggest some implications of socioaffective strategies for teaching reading. The examination of the theories - the interaction hypothesis and the sociocultural theory - suggest that the use of socioaffective strategies facilitates more effective understanding of information that is to be found. distributed, and taken in among the participants. The discourse analyses of the students' interaction in a Korean college English reading class show ample evidence of the use of socioaffective strategies that helped them understand the meaning of a text. However, the analyses show that the strategies are mostly used to ask questions concerning the meaning of clauses. Only few analytical questions are raised for some structural and pragmatical features in the text which are crucial to the understanding of its meaning. Imbalance also exists in the types of the questions used by the participants. The analyses indicate that, instead of negotiating more interactively, the students tend to rely upon a more advanced student when they face difficult English sentences. Therefore as a conclusion this paper emphasizes the importance of teaching socioaffective strategies to help students to help themselves to become more cooperative, independent and analytical in reading English texts.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.115-124
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• 2017

In this paper, a different technique to predict the effects of soil-structure interaction (SSI) on seismic response of building systems is investigated. The technique use a machine learning algorithm called Support Vector Regression (SVR) with technical and analytical results as input features. Normally, the effects of SSI on seismic response of existing building systems can be identified by different types of large data sets. Therefore, predicting and estimating the seismic response of building is a difficult task. It is possible to approximate a real valued function of the seismic response and make accurate investing choices regarding the design of building system and reduce the risk involved, by giving the right experimental and/or numerical data to a machine learning regression, such as SVR. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The results show that the performance of the technique can be predicted by reducing the number of real data input features. Further, performance enhancement was achieved by optimizing the RBF kernel and SVR parameters through grid search.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.194-198
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• 2017

In this paper, we propose a revised Deep Convolutional Neural Network (DCNN) model to extract Protein-Protein Interaction (PPIs) from the scientific literature. The proposed method has the merit of improving performance by applying various global features in addition to the simple lexical features used in conventional relation extraction approaches. In the experiments using AIMed, which is the most famous collection used for PPI extraction, the proposed model shows state-of-the art scores (78.0 F-score) revealing the best performance so far in this domain. Also, the paper shows that, without conducting feature engineering using complicated language processing, convolutional neural networks with embedding can achieve superior PPIE performance.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.60.2-60.2
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• 2018

We present the near infrared JHK photometric properties and the spatial distribution of red supergiants(RSGs) of NGC 3623, NGC 3627 and NGC 3628 in the Leo Triplet system using the data obtained with 3.8m UKIRT(United Kingdom Infra-Red Telescope) at Hawaii. We checked interaction between the three galaxies by making a spatial density map of RSGs. From (J-K,K)0 Color-Magnitude Diagram which include resolved stars in three galaxy and control field with PARSEC isochrone, we figured out the RSG candidates of the Leo triplet are at 0.9<(J-K)0<1.2, mK<17.5 and separated them from background and foreground sources. Using gaussian kernel density estimation, we drew spatial density map of RSGs in the Leo triplet with an assumption that all RSGs are an identical population. The density map shows extended features of NGC 3628 to NGC 3627 along the declination direction. The asymmetries between NGC 3627 and NGC 3628 might be evidence for that the distribution of actual star components(RSGs) follows the neutral hydrogen distribution and also for interaction between two galaxies. And the extended features along the right ascension direction might be a supporting evidence for the existence of a TDG(Tidal Dwarf Galaxy). In case of NGC 3623, we could not see any sign of interaction in density map.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.9_10 s.157
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• pp.1366-1377
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• 2006

The purposes of this study was to find out 1) the difference in the importance degree of store attribute according to interaction between fashion product types and task situations, 2) the difference in the importance degree of store attribute according to the patronized store types on the basis of fashion product types. The subjects were female adults who lived in Seoul. The sampling method was quota sampling. The data was obtained from 391 questionnaires. The data were analyzed using frequency, one-way ANOVA, Duncan test, and two-way ANOVA by means of SPSS. The results were as follows; 1. According to fashion product types and task situations, there were significant differences in factors of product features, services, physical environments of the store, and price. 2. According to interaction between fashion product types and task situations, there were significant differences in factors of product features, services, physical environments of the store, and price. 3. There were significant differences in factors of product features, services, physical environments of the store, and location of store according to patronized store types, when a consumer purchased a suit, casual wear and inner wear.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.96-104
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• 2017

As new smart devices are evolved into the intelligent agent who can reflect user intention and use context, user experience design for easy and convenient usability becomes a core competitive edge. Under the assumption that human centered natural interaction is necessary for the optimal smart TV experience, this study explores the types of voice interaction which are peculiar to TV watching context. In order to build a model for the users to naturally interact with Smart TV, conversation patterns were collected by requesting key features of Smart TV to intelligent agent. Collected sentences were applied to CfA model and classified by responses to activate features. The classified conversation patterns were divided into feature activation and information search. This study has identified that CfC1 occurred when voice interaction between Smart TV and users was vague and CfC2 occurred when the requests were complex or conditional. In conclusion, Simple Request Type is the most efficient model and voice interaction is more appropriate to use to clarify users' vague requests.

• Journal of Korea Game Society
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• v.16 no.1
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• pp.43-50
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• 2016

This research tried to evaluate the competitiveness of a mobile game in the aspect of emotional value which was developed on the purpose of improving specific emotional features. An evaluation of emotional value of a game before its commercial service will provide an effective advice for its marketing and service. The target game to be evaluated on this research is a mobile puzzle game of match-3 genre. We compared the game with Candy crush saga and Poko pang, and the indicators used to evaluate emotional features were flow, challenge, and intention of use. The importance values of indicators were calculated using AHP. And the three games were evaluated by pair-wise comparison method. Finally, the importance values of each indicators were applied to the evaluated results to make overall game quality value.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.179-184
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• 2021

In this study, the conversation behavior of users is investigated by using in-vehicle voice interaction system. The purpose of this study is to identify the elements of conversations that the users expect in voice interactions with systems and present the structural improvements to enable the voice interactions similar to those between people. To observe the users' behavior of voice interaction in the vehicle, the data through contextual inquiry are collected and the interview contents are analyzed by using the open coding. We have been able to explore the usefulness of voice interaction features, which are of great importance in that they increase the user's satisfaction with the features and their usage persistence. This study is meaningful in analyzing the user's empirical needs for the technology of interpersonal model from the perspective of conversation.