• Journal of the Korean Society of Combustion
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• v.20 no.4
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• pp.1-9
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• 2015

The object of this study is a deriving the relations according to the measuring locations between the chemiluminescence and the flame state at commercial burner. In this study, the flame chemiluminescence of the flame of commercial burner is measured using a photomultiplier tube and the optical band-pass filter. In addition, the contour of the chemiluminescence of the flame is measured using the common CCD camera and the optical band-pass filters, and the acquired images is converted by the simple image processing as a matrix form. The results showed that certain relationship between optical data and equivalence ratio exists, and the contour according to the measuring location of the flame chemiluminescence is different by equivalence ratio.

• Journal of Fisheries and Marine Sciences Education
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• v.22 no.1
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• pp.99-112
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• 2010

This study was conducted to test the effect of Burns' cognitive-behavioral group counseling on depression and anxiety of industrial high school students. For this purpose, an experimental group and comparative group which was composed of 15 students respectively were assigned. The independent sample t-test between experimental group and comparative group about the degree of pre-test and after-test and the opposition sample t-test within each experimental group and comparative group were conducted. Analysis of Covariance was also applied. Results of the analyses showed that Burns' cognitive-behavioral group counseling program was effective in decreasing depression and anxiety. Implications of these results on student guidance and counseling were discussed. Suggestions for future research were presented and limitations were indicated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.2
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• pp.349-355
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• 2001

Human have a notable ability to recognize faces, which is one of the most common visual feature in our environment. In regarding face pattern, just like other natural object, a geometrical interpretation of face is difficult to achieve. In this paper, we present wavelet based approach to extract the face features. Proposed approach is similar to the feature based scheme, where the feature is derived from the intensity data without detecting any knowledge of the significant feature. Topological graphs are involved to represent some relations between facial features. In our experiments, proposed approach is less sensitive to the intensity variation.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.161-164
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• 2004

The object of this study is vibrating compaction and curing method in the production process of Design concrete for precast concrete(Design-PC) product. From change of vibrating compaction time and pre-curing time, curing temperature which would be factors of product quality in Design-PC concrete production, and research of optimized steam curing condition from relations between curing condition and strength development, basic data of vibrating compaction time and concrete steam curing method for Design-PC will be presented.

• Journal of the Korean Institute of Rural Architecture
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• v.1 no.1
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• pp.77-86
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• 1999

The object of this study is to look for how to develop the style of residence formed spontaneously on the steep area by looking into the street-network and resident character in residence area and analysing fundamental style of residence. Specially, It is not easy to find out a study of a sea-village in the steep area. So, it is urgent to be developed a road-system and a style of residence which are able to be adapted to special circumstances and situation of ground. Therefore, th found out characters that a steep area contains, contents that are analyzed in this study are as follows : First, the order and the style of road-net formed to be adapted to circumstances of ground. Second, the style of road which is formed by directions. Third, the style of alley. Fourth, the relations with which alley and Madang are confronted each other.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.883-885
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• 2005

비디오 데이터에서 의미적 인식을 위해 활용되는 요소 중 하나가 객체에 대한 움직임 정보로 이는 비디오 데이터에 대한 색인과 내용 기반 검색을 수행하는데 중요한 역할을 한다. 본 논문에서는 효율적인 객체기반 비디오 검색과 비디오의 움직임 해석을 위한 시공간 관계 표현 방법을 제시한다. 비디오의 객체표현 방법은 Polygon-based Bounding Volume의 3차원 Mesh 모델을 생성한 후 이를 이용하여 비디오 내 개체의 구조적 내용을 저차원적 속성과 움직임에 대한 기본 구조로 활용하였다. 또한, 움직임 객체에 대해 시공간적 특성과 시각적 특성을 동시에 고려하여 표현되도록 하였다. 각 Vertex는 시각적 특징 중 일부분이고, 비디오 내 개체의 공간적 특성과 개체의 움직임은 Volume Trajectory로 모델링되고, 개체와 개체간의 시공간적 관계를 표현하기 위한 Operation을 정의한다.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1668-1675
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• 2008

In this paper, we propose a post-processing technique developed for the subjective improvement of color resolution in DCT-coded color images. The high frequency components caused by complex object parts are compressed and impaired through DCT-based image processing, so color distortions such as blurs in high saturated regions are observed. It's mainly due to the severe loss of color data as Cb and Cr. Generally, the activities of chroma elements in DCT domain correlate strongly with that of luminance as spatial frequency gets higher, and based on the relations between chroma and luma AC activities, we compensate destructed Cb, Cr coefficients using modifications from Y coefficients. Simulation results show that the proposed method enhances color resolution in high saturated region, and improves the visual quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.434-440
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• 2010

In this paper, we define generalized induced linguistic aggregation operator called generalized induced linguistic ordered weighted harmonic mean(GILOWHM) operator. Each object processed by this operator consists of three components, where the first component represents the importance degree or character of the second component, and the second component isused to induce an ordering, through the first component, over the third components which are linguistic variables and then aggregated. It is shown that the induced linguistic ordered weighted harmonic mean(ILOWHM) operator and linguistic ordered weighted harmonic mean(LOWHM) operator are the special cases of the GILOWHM operator. Based on the GILOWHM and LWHM operators, we develop an approach to group decision making with linguistic preference relations. Finally, a numerical example is used to illustrate the applicability of the proposed approach.

• Child Health Nursing Research
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• v.25 no.1
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• pp.65-73
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• 2019

Purpose: This study aimed to identify factors associated with maternal attachment of breastfeeding mothers, with a focus on the mothers' breastfeeding characteristics. Methods: Data were collected from 217 mothers who breastfed their healthy baby for 1 month after childbirth and had no postpartum complications. The data were analyzed by hierarchical regression analysis. Results: The factors significantly associated with maternal attachment were an emotional exchange with one's baby (${\beta}=.41$, p<.001), breastfeeding confidence (${\beta}=.20$, p=.022), depression ('quite a bit or more', ${\beta}=-.18$, p=.005), and depression ('a little', ${\beta}=-.14$, p=.024). The model explained 38.4% of variance in maternal attachment. Conclusion: In order to improve attachment, nurses should be actively supported in helping mothers in the first month postpartum adapt to breastfeeding. Interventions to prevent postpartum depression should also be conducted.

• ETRI Journal
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• v.44 no.3
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• pp.438-449
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• 2022

This study proposes a dependency grammar-based self-attention multilayered bidirectional long short-term memory (DG-M-Bi-LSTM) model for subject-predicate-object (SPO) tuple recognition from natural language (NL) sentences. To add recent knowledge to the knowledge base autonomously, it is essential to extract knowledge from numerous NL data. Therefore, this study proposes a high-accuracy SPO tuple recognition model that requires a small amount of learning data to extract knowledge from NL sentences. The accuracy of SPO tuple recognition using DG-M-Bi-LSTM is compared with that using NL-based self-attention multilayered bidirectional LSTM, DG-based bidirectional encoder representations from transformers (BERT), and NL-based BERT to evaluate its effectiveness. The DG-M-Bi-LSTM model achieves the best results in terms of recognition accuracy for extracting SPO tuples from NL sentences even if it has fewer deep neural network (DNN) parameters than BERT. In particular, its accuracy is better than that of BERT when the learning data are limited. Additionally, its pretrained DNN parameters can be applied to other domains because it learns the structural relations in NL sentences.