• Asia pacific journal of information systems
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• 제15권4호
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• pp.109-133
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• 2005

The purpose of this study is to develop and validate a model of firm's IT capability based on IT resources such as IT infrastructure, IT personnel, and IT routine. To do this, the study defined IT capability as a third-order factor model and identified three conceptual dimensions of IT capability: IT infrastructure flexibility, IT personnel expertise, IT resource management capability, IT resource management capability indicates a capacity generated by IT routines, a new IT resource type identified in this study. The validity of the proposed model is evaluated with 243 firm level data using LISREL. The results of confirmatory factor analysis(CFA) demonstrated that the model is highly reliable and valid. Additionally, it was found that IT routines have a high potential as a new IT resource category.

• 한국멀티미디어학회논문지
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• 제23권7호
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• pp.850-861
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• 2020

Hangul is a language that is composed of initial, medial, and final syllables. It has 11,172 characters. For this reason, the current method of designing all the characters by hand is very expensive and time-consuming. In order to solve the problem, this paper proposes an automatic Hangul font generation system and evaluates the standards for mapping Hangul characters to produce an effective automated Hangul font generation system. The system was implemented using character generation engine based on deep learning CycleGAN. In order to evaluate the criteria when mapping characters in pairs, each criterion was designed based on Hangul structure and character shape, and the quality of the generated characters was evaluated. As a result of the evaluation, the standards designed based on the Hangul structure did not affect the quality of the automated Hangul font generation system. On the other hand, when tried with similar characters, the standards made based on the shape of Hangul characters produced better quality characters than when tried with less similar characters. As a result, it is better to generate automated Hangul font by designing a learning method based on mapping characters in pairs that have similar character shapes.

• 수산해양교육연구
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• 제25권4호
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• pp.878-890
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• 2013

The purpose of this study is to apply the PEOE class model that can enhance students' scientific creative problem-solving ability and self-directed learning ability in the middle school science subject and analyze the effects of it on students' long- and short-term retention, scientific creative problem-solving ability, and self-directed learning characteristics. And the paper has gained the following results: First, according to the result of analysis through the pre-test, post-test, and delay test to examine the effects of PEOE-based class on learners' long- and short-term retention, it is found to be statistically significant in the significant level of .05. In other words, the class using PEOE influences learners' short-term retention significantly, but it is even more effective in transmitting the concept that students acquire into their long-term memory. Second, according to the result of analysis through the pre-test and post-test to examine the effects of PEOE-based class on learners' scientific creative problem-solving ability, it is found to be statistically significant in the significant level of .05 in general. However, 'elaboration' and 'originality', the subfactors of scientific creative problem-solving ability, do not indicate significant effects. Third, according to the result of analysis through the pre-test and post-test to examine the effects of PEOE-based class on learners' self-directed learning characteristics, it is found to be statistically significant in the significant level of .05 as a whole. However, 'openness' and 'future-oriented self-understanding', the subfactors of self-directed learning characteristics, do not exert significant effects. Based on the above study results, it can be concluded that PEOE-based class is more effective for learners' academic achievement in science, scientific creative problem-solving ability, and self-directed learning characteristics than lecture-method instruction regarding the middle school science unit of 'The Properties of Air and Weather Change'.

• 산업경영시스템학회지
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• 제41권1호
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• pp.1-10
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• 2018

Current evaluation practices for IT projects suffer from several problems, which include the difficulty of self-explanation for the evaluation results and the improperly scaled scoring system. This study aims to develop a methodology of opinion mining to extract key factors for the causal relationship analysis and to assess the feasibility of quantifying evaluation scores from text comments using opinion mining based on big data analysis. The research has been performed on the domain of publicly procured IT proposal evaluations, which are managed by the National Procurement Service. Around 10,000 sets of comments and evaluation scores have been gathered, most of which are in the form of digital data but some in paper documents. Thus, more refined form of text has been prepared using various tools. From them, keywords for factors and polarity indicators have been extracted, and experts on this domain have selected some of them as the key factors and indicators. Also, those keywords have been grouped into into dimensions. Causal relationship between keyword or dimension factors and evaluation scores were analyzed based on the two research models-a keyword-based model and a dimension-based model, using the correlation analysis and the regression analysis. The results show that keyword factors such as planning, strategy, technology and PM mostly affects the evaluation result and that the keywords are more appropriate forms of factors for causal relationship analysis than the dimensions. Also, it can be asserted from the analysis that evaluation scores can be composed or calculated from the unstructured text comments using opinion mining, when a comprehensive dictionary of polarity for Korean language can be provided. This study may contribute to the area of big data-based evaluation methodology and opinion mining for IT proposal evaluation, leading to a more reliable and effective IT proposal evaluation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• 한국학교보건학회지
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• 제29권1호
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• pp.42-52
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• 2016

Purpose: The purpose of this study was to examine effects of school-based alcohol prevention programs on drinking statuses of adolescents. Methods: The findings of this study was based on the data obtained from the '2015 11th Korea Youth Risk Behavior Web-based Survey. The number of study subjects were 68,043. Results: It was figured that 35.6% of the study subjects had experienced school-based alcohol prevention programs within the last 12 months. As the students got older, the chances to participate in the programs decreased (p<.01). For both middle and high school students, current drinking rates for the educated was lower than those of the uneducated students(6.6% vs 8.0%; 22.2% vs 25.9%) and it was statistically significant. A similar pattern was found for high-risk drinking rates. Those educated showed lower rates than the uneducated with statistical significance of p<.001. In addition, the educated had lower problem drinking rate than the uneducated for both middle (p<.05) and high school students (p<.001). The results of logistic regression analysis showed that school-based alcohol prevention programs had statistically significant effect on current drinking status of adolescents (p<.05). However, it had significant effect only on high-risk drinking status of high school students (p<.05) and had no effect on problem drinking. Conclusion: This study addressed effectiveness of school-based adolescent alcohol prevention programs and that it is important to develop means to implement school health education.

• 한국시뮬레이션학회논문지
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• 제18권1호
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• pp.17-25
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• 2009

본 논문에서는 퍼지기반 Segment-Boost 방법을 소개하고, 이를 이용한 효과적인 얼굴인식 방법을 제안한다. 퍼지기반 Segment-Boost는 기존의 Segment-Boost가 갖고 있던 문제점과 성능의 한계요소들을 제거함으로써, 향상된 학습 성능뿐만 아니라 학습 성능의 안정성과 신뢰성을 보장하여 준다. 퍼지기반 Segment-Boost는 퍼지이론을 이용함으로써 서브벡터 선택개수를 최적화하고, 이를 통해 최상의 학습 성능이 유도될 수 있도록 설계되었다. 또한, 퍼지기반 Segment-Boost 내에서의 퍼지추론을 위해 본 논문에서 설계한 퍼지 제어기는 퍼지기반 Segment-Boost의 학습 성능을 측정하고, 최적화된 서브벡터 선택개수를 추론함으로써 서브벡터 선택개수를 제어한다. 시뮬레이션 결과, 본 논문에서 설계한 퍼지 제어기는 실제 최적의 서브벡터 선택개수에 매우 근접한 값을 추론하였다. 그 결과, 퍼지기반 Segment-Boost는 비교 실험한 boosting 방법보다 높은 얼굴인식률을 보여줌과 동시에 기존 Segment-Boost 만큼의 빠른 특징선택 속도를 유지하였고, 이러한 실험결과를 통해 퍼지기반 Segment-Boost의 학습 성능과 이를 이용한 특징선택 및 얼굴인식 방법에 있어서의 성능향상 및 안정성이 입증되었다.

• 공학교육연구
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• 제26권6호
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• pp.19-29
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• 2023

This study aims to develop and apply a metaverse-based instructional design model for the education in science and technology. It analyzed the concept and characteristics of metaverse, existing non-contact education models, and major teaching strategies systematically. Based on the prior researches, an instructional design model using metaverse is developed that presents metaverse-related teaching strategies and design principles for the before-, during-, and after-lesson phases. Then, this model was applied to a project-based learning program, conducted a perception survey on instructors and learners, and revised the metaverse instructional design model based on the results of the survey. In the Metaverse Instructional Design Model, before-lesson phase is a physical and psychological preparation stage for class participation, which includes familiarization with the Metaverse learning environment, formation of expectations for education, and self-directed pre-learning. During the lesson, to effectively deliver the lesson content, it is necessary to build confidence in the learning environment, promote learning participation, provide reference materials, perform team projects and provide feedback, digest learning content, and transfer learning content. The after-lesson phase provides strategies for ongoing interaction between learners and mentors. This study introduces a new instructional design model that utilizes metaverse and shows the potential of metaverse-based education in science and technology. It also has important implications in that it provides practical guidelines for the effective design and implementation of metaverse-based education.

• 한국정보시스템학회지:정보시스템연구
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• 제29권3호
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• pp.197-214
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• 2020

Purpose This study examines the influence of product development competence and IT competence on new product development (NPD) performance in the context of Korean companies. To achieve this goal, this study presents and empirically tests a model of how NPD competence and IT competence can be exploited to positively influence NPD performance through convergence capabilities. Design/methodology/approach The NPD competence are based on the research construct developed by Zhang et al. (2013). IT competence is based on the research construct developed by Lu and Ramamurthy(2011) and the NPD performance are based on the performance construct developed by Sivadas and Dwyer (2000). To complete the investigation, we conducted a survey from Korean 1000 big companies, which enrolled in Korean stock market. Randomly contacted 171 Korean companies, including firms of all sizes and types. To test our hypotheses, structured equation model (SEM) with partial least squares (PLS) method was employed. Findings The findings indicate that NPD competence and IT competence are antecedent to convergence capabilities, while IT competence is higher influence than NPD competence. Also, convergence capabilities has very significant relationship with NPD performance. This study provides a better understanding of the relationship between NPD competence, IT competence, convergence capabilities, and NPD performance. So companies should focus on improving NPD and IT competence on NPD performance through convergence capabilities.

• 정보처리학회논문지B
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• 제15B권4호
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• pp.315-322
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• 2008

인터넷 상에 산재해 있는 사진이나 비디오 등 시각 미디어 데이터를 효과적으로 검색하는 것은 전자 미술 박물관, 전자상거래, 전자 쇼핑몰 등 여러 응용 분야에서 중요한 일이다. 이러한 분야에서는 단순한 키워드 검색이 아닌 내용 기반 또는 의미 기반의 멀티미디어 검색을 필요로 한다. 인터넷 상의 시각 미디어를 효과적으로 검색하기 위해 제안된 선행 연구에서는 시각 미디어의 메타데이터와 온톨로지를 이용하고 또한 웹서비스를 이용하여 의미 기반의 검색을 수행한다. 본 연구에서는 인터넷 상에서 여러 시각 미디어 제공자와 이 제공자들의 정보를 가지고 있는 하나의 중계자가 존재하는 상황에서 시각 미디어를 효율적으로 검색하기 위한 전 단계로 적합한 서비스 제공자를 찾는 방법을 제안한다. 제안된 방법은 사용자의 질의에 적합한 제공자들과 그 순위를 효율적으로 얻기 위하여 온톨로지의 트리 구조를 이용한다. 온톨로지 트리에서 하위 노드의 크기와 자식 노드의 크기에 기반한 이 방법은 기존의 방법에 비해 효과적으로 제공자들간의 순위를 측정한다. 실험 결과 이 방법이 속도는 비슷하게 유지하면서 정확한 결과를 도출함을 보인다.