• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.169-174
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• 2018

In general, the methods of the analysis of variance(ANOVA) for the continuous data and the chi-square test for the discrete data are used for statistical analysis of the effect and the association. In multidimensional data, analysis of hierarchical structure is required and statistical linear model is adopted. The structure of the linear model requires the normality of the data. A multidimensional categorical data analysis methods are used for causal relations, interactions, and correlation analysis. In this paper, Bayesian network model using probability distribution is proposed to reduce analysis procedure and analyze interactions and causal relationships in categorical data analysis.

• 한국노년학
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• v.32 no.2
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• pp.611-629
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• 2012

This research examines the participation experience of a Focusing group program dealing with elderly depression, with the aim of providing a groundwork for developing and improving such programs. Qualitative analysis is performed based interviews conducted with 9 elderly clients with depression symptoms that participated in a 10 week Focusing group program. The results summarize into 3 themes, 3 categories per theme, and 3 sub-categories per category. The first theme is "program effectiveness" with three associated categories: Category 1) The reduction effect of the depression ; Category 2) Increased self-awareness, self-respect and acceptance experience; Category 3) Everyday life changes. The second theme is "expectation and difficulties of the program", with 3 related categories: Category 1) Expectation of program; Category 2) Difficulties of program; Category 3) Personal difficulties. The third theme is "program enhancement methods" with 3 affiliated categories: Category 1) Differentiation with other programs; Category 2) Improvement of program; Category 3) Post program direction. Based on the results of the analysis, the effectiveness of the Focusing group program for elderly depression is examined and suggestions are provided for further program improvements and applications.

• Proceedings of the Korea Association of Information Systems Conference
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• 1997.10a
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• pp.217-233
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• 1997

정보시스템계획을 수립할 때 발생하는 많은 문제들은 성공적인 정보시스템의 구축 에 장애요인이 되고 있다. 본 연구는 정보시스템계획 문제에 영향을 미치는 요인들을 살펴 보고 정보시스템계획과정상의 범주, 정보시스템의 전략적 역할상의 범주로 나누었다. 또한, 각 범주와 관련한 요인들이 정보시스템계획문제를 감소시키는데 있어 어떤 영향을 미치는가 를 살펴보기 위한 이론적 모형을 제시하였으며 이들 요인데 대한 전략적 방안을 제시하기 위해 몇 가지 가설을 제시하여 추후 실증분석을 위한 토대로 마련하였다.

• Science of Emotion and Sensibility
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• v.2 no.1
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• pp.77-94
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• 1999

직물 및 직물 관련 제품에서 주로 사용되는 감성 어휘들의 관계 및 구조를 분석하기 위해 잡지 및 설문 조사 과정을 통해 어휘를 수집하였다. 수집된 어휘의 빈도를 조사하고, 어휘 적절성을 평가하여 감성어라고 생각될 수 있는 어휘들만을 정리하였다. 여기서 추출된 372개의 어휘는 직물 및 직물 관련 상황에서의 감성어로 사용될 수 있을 분만 아니라 유사 분야의 감성어 모형에 대한 기본 자료로 활용될 수 있을 것이다. 어휘들 간 관계구조에 대한 분석은 몇 가지 면에서 이뤄졌다. 자유연상 과제를 실시하여 어휘들 간 관계의 연결망(network)을 확인할 수 있었다. 어휘들이 내포하고 있는 의미의 여러 측면에서 어휘들 간 관계를 파악할 수 있도록 어휘들에 대해 다차원 분석을 실시한 결과 어휘 간 관계는 3차원이면 충분히 설명될 수 있는 것으로 나타났다. 두 개의 주차원을 중심으로 어휘들의 공간 분포를 그리고 이들 어휘를 범주로 분류한 결과 대략 11개의 범주로 어휘들을 나눠볼 수 있었다.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.223-230
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• 1999

본 논문에서는 결합범주문법으로 한국어를 처리할 때 구문분석과정에서 복잡도를 높이는 역할을 하는 spurious ambiguity와 구조적 모호성이 있는 명사구 접속에 대해서 논한다. 통사적 처리와 의미적 처리가 동시에 수행되는 결합범주문법의 특징을 사용해서 spurious ambiguity로 인해 발생하는 복잡도를 줄이는 방안을 제시하고 접속항에서 접속의 중심이 되는 명사들 간의 공기유사도를 이용해서 접속항 선정에서 발생하는 복잡도와 오분석을 줄이는 방안을 제시한 뒤 이의 개선방안을 논의한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.221-222
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• 2017

본 논문에서는 문헌 고찰과 전문가 검증을 통해 정보 교사가 가지는 신념을 정의하고 신념 체계의 범주화를 위한 준거를 분석하였다. 신념은 대상에 대해 개인이 가지고 있는 정보를 뜻하는 개념으로 개인의 지식 체계를 구성하고 개인의 행동을 특정 방향으로 유도하는 성향을 가진다. 따라서 정보 교육에 대한 정보 교사의 신념은 정보 교육의 목적과 성격, 교수 방법이나 학습 방법 등을 내면화하고 교육적 행위를 결정하는데 큰 영향을 주게 된다. 본 연구의 결과는 정보 교육에 대한 정보 교사의 신념 형성요인 및 신념 형성 과정 분석을 위한 후속 연구의 이론적 기초를 제공할 것이다.

• Cross-Cultural Studies
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• v.46
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• pp.297-325
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• 2017

In this paper, I would like to reconsider the evidential category (or the mediation category) in languages with language specific values, especially in Korean and French evidentials. We tried to analyze how the evidentials are represented in both languages including their linguistic markers (grammatical, lexical or discursive) and their semantic meanings. According to the precedent studies from the general linguistic point of view, we would like to reconsider the semantic meanings of both languages' grammatical markers, the so-called Korean retrospective marker '-te-' and French conditionals in the framework of the enunciative operation theory suggested by $Descl{\acute{e}}s$ & $Guentch{\acute{e}}va$ (2000), which proposed to classify the type of discourse by the language-independent description tools conceived after the enunciation theory suggested by Bally (1965), Benveniste (1956), Culioli (1973). Through this approach, we would like to contribute to establishing the linguistic basis not only for the general linguistic research to determine the invariant meaning of linguistic evidentials and their system, but also for the applied linguistics to the language engineering field.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.139-148
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• 2010

This paper shows a reinforcement post-processing method and feedback algorithm for improvement of assigning method in classification. Especially, we focused on complex documents that are generally considered to be hard to classify. A basis factors in traditional classification system are training methodology, classification models and features of documents. The classification problem of the documents containing shared features and multiple meanings, should be deeply mined or analyzed than general formatted data. To address the problems of these document, we proposed a method to expand classification scheme using decision boundary detected automatically in our previous studies. The assigning method that a document simply decides to the top ranked category, is a main factor that we focus on. In this paper, we propose a post-processing method and feedback algorithm to analyze the relevance of ranked list. In experiments, we applied our post-processing method and one time feedback algorithm to complex documents. The experimental results show that our system does not need to change the classification algorithm itself to improve the accuracy and flexibility.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.13-20
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• 2011

The spatio-temporal pattern in precipitation is a significant element in defining characteristics of precipitation. In this study, a new scheme on regionalization utilizing temporal information was introduced on the basis of existing approaches that is mainly based on simple moments of data and geographical information. Given the identified spatio-temporal pattern, this study was extended to characterize regional pattern of annual maximum rainfall over Korea. We have used circular statistics to characterize the temporal distribution on the precipitation, and the circular statistics allow us to effectively assess changes in timing of the extreme rainfall in detail. In this study, a modified K-means method was incorporated with derived temporal characteristics of extreme rainfall in order to better characterize hydrologic pattern for regional frequency analysis. The extreme rainfall was reasonably separated into five categories that considered most attributes in both quantitative and temporal changes in extremes. The results showed that the proposed approach is a promising approach for regionalization in term of physical understanding of extreme rainfall.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.117-124
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• 2013

This study examined that how precisely MFCC, LPC, energy, and pitch related parameters of the speech data, which have been used mainly for voice recognition system could predict the vocal emotion categories as well as dimensions of vocal emotion. 110 college students participated in this experiment. For more realistic emotional response, we used well defined emotion-inducing stimuli. This study analyzed the relationship between the parameters of MFCC, LPC, energy, and pitch of the speech data and four emotional dimensions (valence, arousal, intensity, and potency). Because dimensional approach is more useful for realistic emotion classification. It results in the best vocal cue parameters for predicting each of dimensions by stepwise multiple regression analysis. Emotion categorizing accuracy analyzed by LDA is 62.7%, and four dimension regression models are statistically significant, p<.001. Consequently, this result showed the possibility that the parameters could also be applied to spontaneous vocal emotion recognition.