• Journal of the Korean Academy of Esthetic Dentistry
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• v.3 no.1
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• pp.23-31
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• 1995

The All-Bond system is a unique development in the field of adhesive dentistry. It is a universal bonding system that will bond composite to all dental-related surfaces: dentin, enamel, metal alloy (precious and nonprecious), amalgam, porcelain, and composite. It is also the only system that allows use of both the conservative and all-etch techniques. The main purpose of this paper is to explain the features of the All-Bond system. Its chemistry and a working hypothesis are shown as well.

• Journal of The Korean Association For Science Education
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• v.23 no.3
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• pp.215-228
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• 2003

The present study is to analyze the arguments about the generation of declarative scientific-knowledge in the philosophy of science and invent a structured model of the process of scientific-knowledge generation with the types of the generated scientific-knowledge. The invented model shows that scientific-knowledge generation is a distinctive process with the processes of inductive, abductive, and deductive thinking. Furthermore, inductive process is included with observation, which is consisted of simple observation and operative observation, and rule-discovery which is involved with the processes of commonness discovery, classification, pattern discovery, and hierarchical relationship. Also, abductive process has two components. One component generates question and second component generates hypothesis in which the process consists of representing question situation, identifying experienced situation, identifying causal explicans, and generating hypothetical explicans. Finally, deductive process is involved with logical inventing test method and evaluation criteria, concrete inventing test method and evaluation criteria, evaluating hypothesis, and making conclusion.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.133-140
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• 2011

Recently, Web applications, such as Stock Image and Image Library, are developed to provide the integrated management for user's images. Image hash techniques are used for the image registration, management and retrieval as the identifier and many researches have been performed to raise the hash performance. This paper proposes GLOCAL image hashing method utilizing the hierarchical histogram which based on histogram bin population method. So far, many researches have proven that image hashing techniques based on histogram are robust image processing and geometrical attack. We modified existing image hashing method developed by our research team. The main idea is that it makes more fluent hash string if we have histogram bin of specific length as shown in the body of paper. Finally, we can raise the magnitude of hash string within same context or feature and strengthen the robustness of hash.

• Journal of the Korean earth science society
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• v.42 no.5
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• pp.571-587
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• 2021

This study aims to investigate the problem recognition and clue capture processes of the observation stage in a geological field trip using abductive inquiry. To this end, eight outdoor geological programs were developed in the order of diagnostic evaluation, outdoor geological fieldwork, and review. Six middle-school students participated in these programs The geological field trip was conducted twice, followed by data provision, observation, rule generation, hypothesis generation, and final hypothesis presentation. Outdoor geological fieldwork recordings and student activity sheets were collected and analyzed qualitatively. From these data, three aspects of student observations emerged during the geological fieldwork: The characteristics of each pattern were subdivided into the geological importance of the clues, attention, type of clues, observation characteristics (attention factor), clue utilization, and clue deletion. Here, by combining these results, we propose educational applications that correspond to each aspect.

• Journal of Hydrogen and New Energy
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• v.21 no.5
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• pp.425-434
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• 2010

Integrated gasification combined cycle (IGCC) is an efficient and environment-friendly power generation system which is capable of burning low-ranked coals and other renewable resources such as biofuels, petcokes and residues. In this study some process modeling on a conceptual entrained flow gasifier was conducted using the ASPEN Plus process simulator. This model is composed of three major steps; initial coal pyrolysis, combustion of volatile components, and gasification of char particles. One of the purposes of this study is to develop an effective and versatile simulation model applicable to numerous configurations of coal gasification systems. Our model does not depend on the hypothesis of chemical equilibrium as it can trace the exact reaction kinetics and incorporate the residence time calculation of solid particles in the reactors. Comparisons with previously reported models and experimental results also showed that the predictions by our model were pretty reasonable in estimating the products and the conditions of gasification processes. Verification of the accuracy of our model was mainly based upon how closely it predicts the syngas composition in the gasifier outlet. Lastly the effects of change oxygen are studied by sensitivity analysis using the developed model.

• Journal of Distribution Science
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• v.17 no.8
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• pp.25-34
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• 2019

Purpose - Investigate the association of internal and external factors of consumers and analysing the role of moderating comparative marketing aspects, especially the part of YouTuber and celebgram in influencing purchase decisions. Apart from that, it provides an overview of the pattern of purchase decision making in forming Millennials and Y generation consumer culture Research design, data, and methodology - This study uses a quantitative research approach with descriptive, predictive, and prospective data analysis on 300 eligible Millennials and Y aged 20-35 years who are bachelor-educated. Data collection using online surveys with final statistical analysis using the Partial Least Square (PLS) approach Results - All hypothesis are declared accepted, indirect testing the dominant internal consumer factors have a positive and significant effect on consumers' purchase decisions. Through testing Moderating, aspect marketing comparative is also authoritative able to moderate internal consumer factors towards purchase decision making. Conclusions - Digital technology is changing the paradigm and perceptions of the millennials and Y generations in terms of behaving as a generation of technology connoisseurs who also influence and shape the culture of that generation and the generations to come in the future.

• Mycobiology
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• v.44 no.1
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• pp.38-47
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• 2016

The ascomycete fungus Mycosphaerella graminicola (synonym Zymoseptoria tritici) is an important pathogen of wheat causing economically significant losses. The primary nutritional mode of this fungus is thought to be hemibiotrophic. This pathogenic lifestyle is associated with an early biotrophic stage of nutrient uptake followed by a necrotrophic stage aided possibly by production of a toxin or reactive oxygen species (ROS). In many other fungi, the genes CREA and AREA are important during the biotrophic stage of infection, while the NOXa gene product is important during necrotrophic growth. To test the hypothesis that these genes are important for pathogenicity of M. graminicola, we employed an over-expression strategy for the selected target genes CREA, AREA, and NOXa, which might function as regulators of nutrient acquisition or ROS generation. Increased expressions of CREA, AREA, and NOXa in M. graminicola were confirmed via quantitative real-time PCR and strains were subsequently assayed for pathogenicity. Among them, the NOXa over-expression strain, NO2, resulted in significantly increased virulence. Moreover, instead of the usual filamentous growth, we observed a predominance of yeast-like growth of NO2 which was correlated with ROS production. Our data indicate that ROS generation via NOXa is important to pathogenicity as well as development in M. graminicola.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.2
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• pp.123-129
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• 2009

Aprotinin is used clinically in cardiopulmonary bypass surgery to reduce transfusion requirements and the inflammatory response. The mechanism of action for the anti-inflammatory effects of aprotinin is still unclear. We examined our hypothesis whether inhibitory effects of aprotinin on cytokine-induced inducible nitric oxide synthase (iNOS) expression (IL-$l\beta$ plus TNF-$\alpha$), reactive oxygen species (ROS) generation, and vascular smooth muscle cell (VSMC) proliferation were due to HO-l induction in rat VSMCs. Aprotinin induced HO-l protein expression in a dose-dependent manner, which was potentiated during inflammatory condition. Aprotinin reduced cytokine mixture (CM)-induced iNOS expression in a dose dependent manner. Furthermore, aprotinin reduced CM-induced ROS generation, cell proliferation, and phosphorylation of JNK but not of P38 and ERK1/2 kinases. Aprotinin effects were reversed by pre-treatment with the HO-l inhibitor, tin protoporphyrin IX (SnPPIX). HO-l is therefore closely involved in inflammatory-stimulated VSMC proliferation through the regulation of ROS generation and JNK phosphorylation. Our results suggest a new molecular basis for aprotinin anti-inflammatory properties.

• Korean Journal of Biological Psychiatry
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• v.15 no.3
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• pp.175-185
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• 2008

Accumulating evidence has suggested the existence of reciprocal communication between immune, endocrine, and neurotransmitter system. Cytokine hypothesis of depression implies that increased pro-inflammatory cytokine such as -1, IL-6, IL-12, TNF-${\alpha}$, and IFN-${\gamma}$ in major depression, acting neuromodulators, play a key role in the mediation of behavioral, neuroendocrine, and neurochemical disturbances in depression. Concerning the relation between cytokines and serotonin metabolism, pro-inflammatory cytokines have profound effects on the metabolism of brain serotonin through the enzyme indoleamine-2,3-dioxygenase(IDO) that metabolizes tryptophan, the precursor of 5-HT to neurodegenerative quinolinate and neuroprotective kynurenate. The neurodegeneration process is reinforced by the neurotoxic effect of the hypercortisolemia during depression. From this perspective, it is possible that efficacy of antidepressants in the treatment of depression may, at least in part, rely on downregulation of pro-inflammatory cytokine synthesis. So, the use of cytokine synthesis inhibitors or cytokine antagonists may be a new treatment approach in depression. However, at present the question whether cytokines play a causal role in the onset of depression or are mere epiphenomena sustaining depressive symptoms remains to be elucidated. Nevertheless, cytokine hypothesis has created new perspectives in the study of psychological and pathophysiological mechanism that are associated with major depression, as well as the prospect for developing a new generation antidepressants.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1003-1013
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• 2016

This paper proposes a framework of superpixel-based vehicle detection method using plane normal vector in disparity space. We utilize two common factors for detecting vehicles: Hypothesis Generation (HG) and Hypothesis Verification (HV). At the stage of HG, we set the regions of interest (ROI) by estimating the lane, and track them to reduce computational cost of the overall processes. The image is then divided into compact superpixels, each of which is viewed as a plane composed of the normal vector in disparity space. After that, the representative normal vector is computed at a superpixel-level, which alleviates the well-known problems of conventional color-based and depth-based approaches. Based on the assumption that the central-bottom of the input image is always on the navigable region, the road and obstacle candidates are simultaneously extracted by the plane normal vectors obtained from K-means algorithm. At the stage of HV, the separated obstacle candidates are verified by employing HOG and SVM as for a feature and classifying function, respectively. To achieve this, we trained SVM classifier by HOG features of KITTI training dataset. The experimental results demonstrate that the proposed vehicle detection system outperforms the conventional HOG-based methods qualitatively and quantitatively.