• Journal of KIISE:Computing Practices and Letters
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• v.13 no.2
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• pp.119-130
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• 2007

Home service networked systems require a high-availability service with a proactive and practical fault management. However, as the system complexity grows, it is not easy to meet the requirement. Moreover, user may want to pay no attention to a sequence of complex or nervous maintenance jobs for system fault managements. Therefore, the home service networked systems must have self & remote fault management capability with a minimal human intervention for meeting high-availability requirement of the integrated systems that consist of the networked appliances or devices. In this paper, we present an autonomic healing utility equipped with a remote self-managing mechanism in order to both increase the availability of home service networked systems and decrease the maintenance cost.

• Journal of the Semiconductor & Display Technology
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• v.17 no.4
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• pp.6-10
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• 2018

Organic light emitting devices have attracted the attention of many people because of their high potential for self-emission and flexible display devices. However, due to limitations in device efficiency and lifetime, partial commercialization is underway. In this paper, we have investigated the electrical conduction mechanism of the organic light emitting device by the temperature and the thickness of the light emitting layer through the current - voltage characteristics with respect to the conduction mechanism directly affecting the efficiency and lifetime of the organic light emitting device. Through the study, it was found that the conduction in the low electric field region is caused by the movement of the heat excited charge in the ohmic region and the tunneling of the electric charge due to the high electric field in the high electric field region.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.26-26
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• 2011

Self-assembled monolayers (SAMs) prepared by sulfur-containing organic molecules on metal surfaces have drawn much attention for more than two decades because of their technological applications in wetting, chemical and biosensors, molecular recognition, nanolithography, and molecular electronics. In this talk, we will present self-assembly mechanism and two-dimensional (2D) structures of various organic thiol SAMs on Au(111), which are mainly demonstrated by molecular-scale scanning tunneling microscopy (STM) observation. In addition, we will provide some idea how to control 2D molecular arrangements of organic SAMs. For instance, the formation and surface structure of pentafluorobenzenethiols (PFBT) self-assembled monolayers (SAMs) on Au(111) formed from various experimental conditions were examined by means of STM. Although it is well known that PFBT molecules on metal surfaces do not form ordered SAMs, we clearly revealed for the first time that adsorption of PFBT on Au(111) at $75^{\circ}C$ for 2 h yields long-range, well-ordered self-assembled monolayers having a $(2{\times}5\sqrt{13})R30^{\circ}$ superlattice. Benzenethiols (BT) SAMs on gold usually have disordered phases, however, we have clearly demonstrated that the displacement of preadsorbed cyclohexanethiol self-assembled monolayers (SAMs) on Au(111) by BT molecules can be a successful approach to obtain BT SAMs with long-range ordered domains. Our results will provide new insight into controlling the structural order of BT or PFBT SAMs, which will be very useful in precisely tailoring the interface properties of metal surfaces in electronic devices.

• Journal of Korea Game Society
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• v.19 no.5
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• pp.103-114
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• 2019

We have been studying a deep-learning program that can communicate with other users in online communities since 2017. But there were problems with processing a Korean data set because of Korean characteristics. Also, low usage of GPUs of RNN models was a problem too. In this study, as Natural Language Processing models are improved, we aim to make better results using these improved models. To archive this, we use a Transformer model which includes Self-Attention mechanism. Also we use MeCab, korean morphological analyzer, to address a problem with processing korean words.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.497-504
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• 2020

Constructing speaker embeddings in speaker verification is an important issue. In general, a self-attention mechanism has been applied for speaker embedding encoding. Previous studies focused on training the self-attention in a high-level layer, such as the last pooling layer. In this case, the effect of low-level layers is not well represented in the speaker embedding encoding. In this study, we propose Masked Cross Self-Attentive Encoding (MCSAE) using ResNet. It focuses on training the features of both high-level and low-level layers. Based on multi-layer aggregation, the output features of each residual layer are used for the MCSAE. In the MCSAE, the interdependence of each input features is trained by cross self-attention module. A random masking regularization module is also applied to prevent overfitting problem. The MCSAE enhances the weight of frames representing the speaker information. Then, the output features are concatenated and encoded in the speaker embedding. Therefore, a more informative speaker embedding is encoded by using the MCSAE. The experimental results showed an equal error rate of 2.63 % using the VoxCeleb1 evaluation dataset. It improved performance compared with the previous self-attentive encoding and state-of-the-art methods.

• Journal of Broadcast Engineering
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• v.27 no.7
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• pp.1011-1020
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• 2022

Recent high-performance panoptic segmentation models are based on transformer architectures. However, transformer-based panoptic segmentation methods are basically slower than convolution-based methods, since the attention mechanism in the transformer requires quadratic complexity w.r.t. image resolution. Also, sine and cosine computation for positional embedding in the transformer also yields a bottleneck for computation time. To address these problems, we adopt three modules to speed up the inference runtime of the transformer-based panoptic segmentation. First, we perform channel-level reduction using depth-wise separable convolution for inputs of the transformer decoder. Second, we replace sine and cosine-based positional encoding with convolution operations, called conv-embedding. We also apply a separable self-attention to the transformer encoder to lower quadratic complexity to linear one for numbers of image pixels. As result, the proposed model achieves 44% faster frame per second than baseline on ADE20K panoptic validation dataset, when we use all three modules.

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.57-63
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• 2008

This study uses the identification which is one of the critical components of psychological mechanism and enables replacing one's own self because of the needs of self-expression(disclosure) and creation. The study aims to improve educational effects using the realistic by increasing sense of the virtual reality and the attention. After the computer-based contents were developed and converted to be applied into robot, and then the contents were combined the student's photo and the avatar using automatic loading. Finally each one of the contents was applied to the students. The results of the investigation indicated that there were significant effects of the contents based on identification. In other words, the contents effect on student's attention, but not their academic achievement. The study could find the effect of the identification's application using the educational robot. We suggested that improving technical ability of the augmented virtuality as a face-detection and sensitive interaction may lead to the specific suggestions for educational effects for further research.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.29-47
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• 2011

Despite the growing attention to the effective utilization of ICT system in workplace, there is an accumulation of evidence from the literature indicating that organizations do not utilize newly introduced ICT systems to their full functional potential and an amount of new implementations continue to fail. We explore the reasons for the underutilization of new ICT by focusing on the individuals' social networks. This paper investigates how the social networks influence individual adaptation to the new ICT and its related performance. Based on the coping theory, we establish a research model that explains the coping mechanism. Collected data are analyzed to test the proposed model and its hypotheses using PLS and UCINET. The results show that the coping effort mechanism of individuals can be explained in terms of their positions within social networks. We conclude the paper by discussing theoretical and practical implications for the research findings and by proposing future studies.

• Journal of the Korean Society of Combustion
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• v.8 no.1
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• pp.17-24
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• 2003

The conventional regenerative system has a high thermal efficiency as well as energy saving using the high preheated combustion air. in spite of these advantages, it can not avoid high nitric oxide emissions. Recently, flameless combustion has received much attention to solve these problems. In this research, numerical analysis is performed for flow-combustion phenomena in the self regenerative burner. In this analysis we used Fluent 6.0 code. the that is developed for commercial use, Methane gas is used as a fuel and two-step reaction model for methane and Zeldovich mechanism for NO generation are used. the velocity of the preheated combustion air is used as a parameter and we analyze the characteristics of flow-field, temperature distributions and NO emissions. Due to the increased recirculation rate, the maximum temperature of flame is significantly increased and NOx emissions is reduced.

• Fashion & Textile Research Journal
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• v.23 no.5
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• pp.586-597
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• 2021

Personalized product recommendation service is receiving attention as a new marketing strategy while supporting consumer information search and purchasing decisions. This study attempted to verify the effect of self-reference on service use behavior through the dual path of cognitive attitude and emotional attachment. Using convenience sampling, an online survey was conducted with 324 women who were in their 20s and 30s. After collecting and compiling the survey data, the reliability and validity of variables constituting the conceptual research model were verified through confirmatory factor analysis using AMOS 22.0. Next, the significance of sequentially mediated pathways was verified using Process 3.5 Model 80. The results showed that self-referencing not only significantly affects service use intention by simply mediating cognitive attitudes but also sequentially mediates cognitive attitudes and additional information search. Furthermore, self-referencing was significant as an indirect path to service use intention by mediating additional information search. However, in the path mediated by emotional attachment, self-referencing was considered as a simple mediated path leading to service usage intention. These results indicate a dual path in the psychological mechanism, through cognitive and emotional evaluation, that prompts consumer behavioral responses to the personalized product information provided in the shopping process.