• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.7-8
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• 2021

인공지능 기술과 서비스는 딥러닝을 중심으로 한 기계학습 기술의 급속한 발전에서 원인을 둔다. 딥러닝 발전 요인으로 GPU등 하드웨어 발전, 기술 공유, 대규모 학습데이터 구축 및 공개를 들 수 있다. 데이터 셋에 관련하여 센서를 이용한 데이터셋의 경우 단순히 많은 데이터셋의 확보뿐 아니라 적절한 위치 및 환경에 따른 고려가 필요하다. 본 논문에서는 UCI의 화학 가스의 데이터셋을 이용하여 위치별 시계열 데이터를 딥러닝을 이용하여 분석하고, 위치별 정확도와 손실을 계산한다. 또한 계산된 결과를 히트맵을 통하여 시각화하여 직관적인 이해를 높인다. 또한 위치별 정확도가 높은 상위 5개의 위치에서 앙상블 방법을 통한 성능의 향상을 확인 하였다.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.177-188
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• 2023

The purpose of this study is to develop and validate a scale for measuring digital literacy by identifying the factors consisting of digital literacy and extracting items for each factor. Preliminary items for the Delphi study were developed through the analysis of previous literature and the deliberation of the research team. As a result of two rounds of the expert Delphi study, 65 items were selected for the main survey. The validation of the items was carried out in the process of exploratory and confirmatory factor analyses, reliability test, and criterion validity test using the data collected in the main survey. As a result, a 4-factor structure composed of 31 questions(factor 1: digital technology & data literacy- 9 questions, factor 2: digital content & media literacy- 8 questions, factor 3: digital communication & community literacy- 9 questions, factor 4: digital wellness literacy - 5 questions) was confirmed. Also, the goodness of fit indices of the model were found to be good and the result of reliability test revealed the scale had a very appropriate level of Cronbach's alpha(α=.956). In addition, a statistically significantly positive correlations(p<.001) were found between digital literacy and internet self-efficacy and between digital literacy and self-directed learning ability, which were predicted in the existing evidence, therefore the criterion validity of the developed scale was secured. Finally, practical and academic implications of the study are provided and future study and limitations of the study are discussed.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.840-850
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• 2022

The purpose of this study is to translate The Digital Addiction Scale for Children(DASC) developed by Hawi, Samaha and Griffiths into Korean and to verify its validity. To translate and validate the original scale developed for 9-12 years old, 294 people aged 9-12 years who usually use digital devices, and exploratory factor analysis, confirmatory factor analysis, internal consistency, and validity analysis were conducted. In addition, reliability and validity analysis were conducted to confirm that this scale is a tool to measure the digital addiction of Korean children with high confidence level and validity. This study is meaningful in that it laid the foundations for related research by adapting and validating the digital addiction scale for children, which complements the limitations of the preceding measures, in accordance with the domestic situation in the situation where the digital addiction problem of children is getting serious.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.33-41
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• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.265-274
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• 2017

This paper examines the problems of big data analysis education and suggests ways to solve them. Big data is a trend that the characteristic of big data is evolving from V3 to V5. For this reason, big data analysis education must take V5 into account. Because increased uncertainty can increase the risk of data analysis, internal and external structured/semi-structured data as well as disturbance factors should be analyzed to improve the reliability of the data. And when using opinion mining, error that is easy to perceive is variability and veracity. The veracity of the data can be increased when data analysis is performed against uncertain situations created by various variables and options. It is the node analysis of the textom(텍스톰) and NodeXL that students and researchers mainly use in the analysis of the association network. Social network analysis should be able to get meaningful results and predict future by analyzing the current situation based on dark data gained.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.237-239
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• 2016

본 논문에서는 HEVC (High Efficiency Video Coding) 복호화기의 SAO (Sample Adaptive Offset)를 효율적으로 병렬화하기 위한 방법을 제안한다. HEVC 는 주관적 화질 향상 및 압축 효율 향상을 위해 디블록킹 필터 (de-blocking filter)와 샘플 적응적 오프셋 (SAO)이라는 두 가지 인-루프 필터를 사용한다. 두 종류의 인-루프 필터의 사용은 HEVC 복호화기의 복잡도를 증가시키는 요인이며, 인-루프 필터에 데이터레벨 병렬화를 적용하여 고속으로 복호화를 수행할 수 있다. 본 논문에서는 SAO 의 병렬화를 위해 CTU (Coding Tree Unit)의 행 단위로 병렬화를 수행함으로써, 병렬화로 인한 추가적으로 발생하는 라인 버퍼 사용을 줄여 SAO 병렬화 효율을 향상시켰다. 실험결과 제안하는 SAO 병렬화 방법을 사용하여 균등분할 SAO 병렬화 방법에 비해 91%의 속도를 향상시켰다.

• Journal of the Korea Institute of Building Construction
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• v.16 no.6
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• pp.487-495
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• 2016

The losses of accidents in the construction industry was significantly increased during the past decades. Therefore, the study of risk management measures in the domestic construction has become very important, and the inherent risk factors need to derive and analyze them based on the quantified method. However, most studies on the construction risk are conducted finding on the qualitative way. This study analysis the accident records from actual construction sites as a quantities study. A correlation analysis and regression analysis are adopted to identify the risk factors and develop a model. The results of this study are expected to be evolve through the accumulated effect and verification of data in the future through continuous feedback.

• Journal of Digital Convergence
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• v.8 no.2
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• pp.203-216
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• 2010

This study corresponds to an exploratory survey that identifies and organizes important decision factors for establishing R&D strategic portfolio in the application of digitalized Korean human-dataset. In the case of countries that have performed the above, the digitalized human-dataset and its visualization application development research are regarded as strategic R&D projects selected and supervised in national level. To achieve the goal of this study, we organize a professional group that reviews articles, suggests research topics, considers alternatives and answers questionnaires. With this study, we draw and refine the detailed factors; these are reflected during a strategic planning phase that includes R&D vision setting, SWOT analysis and strategy development, research area and project selection. In addition to this contribution for supporting the strategic planning, the study also shows the detailed research area's definition/scope and their priorities in terms of importance and urgency. This addition will act as a guideline for investigating further research and as a framework for assessing the current status of research investment.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.11 no.2
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• pp.65-82
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• 2000

The purpose of this study is to compare web directories and users categories, and to identify factors for organizing knowledge structure. Date was collected by questionnaires and analyzed by factor analysis and multidimensional scaling. The result shows that Yahoo！ directories and users categories are different. There are three factors, dynamic and static, visual and acoustic, relationship between hierarchic organization for differentiating knowledge structure.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.400-401
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• 2016

본 논문은 재난 리스크 평가를 위한 집계구 통계자료의 활용방안에 대한 연구를 수행하였다. 인구통계자료, 주택통계자료, 전국사업체 자료는 재난취약성분석과 리스크 평가를 위한 필수 요소이다. 재난의 분석과 평가를 위하여 GIS에 구축하는 자료로는 인구의 총인구, 평균나이, 인구밀도, 노령화지수, 교육수준 등이 있다. 이 자료들을 공간정보로 구축함으로써 기존의 넓은 수준의 데이터를 활용하는 것 보다 정밀한 분석이 가능하다고 판단된다. 또한, 인구와 관련된 데이터뿐만 아니라 집계구 통계 자료는 주택의 건축년도와, 주택의 유형(다세대, 아파트, 연립, 영업용건물주택의 정보를 가지고 있다. 이는 건물의 경제적 평가를 위한 자료로 활용될 것이다. 또한 선정된 지역의 사업체를 분류하여 각 폴리곤의 주요 사업체를 조사하여 공간정보를 구축함. 구축된 공간정보는 리스크 평가를 위한 자료로서 활용될 수 있다 판단된다.