• Journal of Microbiology and Biotechnology
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• v.19 no.8
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• pp.765-773
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• 2009

Edwardsiella tarda is a pathogen with a broad host range that includes human and animals. The E. tarda hemolysin (Eth) system, which comprises EthA and EthB, is a noted virulence element that is widely distributed in pathogenic isolates of E. tarda. Previous study has shown that the expression of ethB is regulated by iron, which suggests the possibility that the ferric uptake regulator (Fur) is involved in the regulation of ethB. The work presented in this report supports the previous findings and demonstrates that ethB expression was decreased under conditions when the E. tarda Fur ($Fur_{Et}$) was overproduced, and enhanced when $Fur_{Et}$ was inactivated. We also identified a second ethB regulator, EthR, which is a transcription regulator of the GntR family. EthR represses ethB expression by direct interaction with the ethB promoter region. In addition to ethB, EthR also modulates, but positively, luxS expression and AI-2 production by binding to the luxS promoter region. The expression of ethR itself is subject to negative autoregulation; interference with this regulation by overexpressing ethR during the process of infection caused (i) drastic changes in ethB and luxS expressions, (ii) vitiation in the tissue dissemination and survival ability of the bacterium, and (iii) significant attenuation of the overall bacterial virulence. These results not only provide new insights into the regulation mechanisms of the Eth hemolysin and LuxS/AI-2 quorum sensing systems but also highlight the importance of these systems in bacterial virulence.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.800-812
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• 2018

In this study, we reviewed recent trends for enhancing human cognitive accessibility to social VR platform. We also proposed a practical method to predict VR sickness and improve the cognitive accessibility. In doing so, we investigated subtle changes in human body sway unconsciously made before, during, and after being exposed to extreme VR experience. The scientific assumption that VR sickness would be correlated with the subtle changes in body sway was validated. We found that participants who showed sensitive changes in the body sway before VR experience, felt more severe VR sickness than others. The findings can be practically applied in predicting susceptibility to VR sickness prior to VR experiences.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.469-476
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• 2022

As the 3D modeling technology and conversational algorithm is developed, digital humans are being used in various fields, and also virtual bankers have begun to appear in banks, including major banks such as Shin-Han Bank and Nong-Hyup Bank. However, most of the research of digital human mainly focus on its appearance, and research on robot persona that should be considered in anthropomorphizing a robot is insufficient. In this study, an experiment was conducted to find out the user experience of three scenarios (student ID receipt, deposit and withdrawal account opening, leasehold loan consultation) in which the level of anthropomorphism of the speech strategy and the level of personal information use differed in the specific context of banking. As a result of the study, social presence and usefulness had an interactive effect on the scenario and the level of anthropomorphism. There was no interaction effect on intimacy, trustworthiness, and perceived intelligence, but a tendency could be confirmed.

• Journal of the HCI Society of Korea
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• v.13 no.2
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• pp.31-44
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• 2018

In the IoT environment, various things could be connected. Those connected things learn and operate themselves, by acquiring data. As human being, they have self-learning and self-operating systems. In the field of IoT study, therefore, the key issue is to design communication system connecting both of the two different types of subjects, human being(user) and the things. With the advent of the IoT environment, much research has been done in the field of UI design. It can be seen that research has been conducted to take complex factors into account through keywords such as multi-modality and interusability. However, the existing UI design method has limitations in structuring or testing interaction between things and users of IoT environment. Therefore, this paper suggests a new UI prototyping method. In this paper, the major analysis and studies are as follows: (1) defined what is the behavior process of the things (2) analyzed the existing IoT product (3) built a new framework driving personality types (4) extracted three representative personality models (5) applied the three models to the smart home service and tested UI prototyping. It is meaningful with that this study can confirm user experience (UX) about IoT service in a more comprehensive way. Moreover, the concept of the personality of things will be utilized as a tool for establishing the identity of artificial intelligence (AI) services in the future.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1424-1436
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• 2020

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.

• Journal of Christian Education in Korea
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• v.66
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• pp.413-437
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• 2021

Humans are created as spiritual beings that can relate to God. However, when a human spirit refuses to transform through confronting God, it experiences a crisis. A spiritual crisis results from disconnecting with God, who is the ultimate foundation, but we humans try to overcome such absence through accomplishments and efforts. In this technological age, the ethics issues of AI (Artificial Intelligence), robots, and cloning are related to anthropology. The development of the mind, heart, and logic cannot suggest a basis for destruction and confusion as much as the development of the world. In fact, education focused on the human mind cannot be considered holistic. Mind, together with thought, will, and belief, plays a crucial role in making choices and leading a human life. So it is actively studied in other domains other than Christian education. However, although the human spirit takes care of some territory of humanity, unlike the mind, it can neither be partial nor fragmentary. Instead, it manages the transformation that influences the core of human life. Therefore, Christian education must clearly concentrate on the spirit rather than on other human elements, intentionally concerning spiritual transformation through encounters with God. In other words, Christian education is the passage connecting a human spirit to God's presence at work, which enables us to understand the human being as a whole. For this, we must put our efforts to increase the chances of encountering God through Christian education. While "Encounter" requires both parties' interaction, "Transformation" stresses God as the main agent and His proactive nature. I also want to emphasize "worship" as the opportunity to communicate and experience God in our daily lives. By examining the preparation and the process of the spiritual transformation of humans, this paper would offer a theological foundation for continued transformation of the human spirit in the faith community, rather than personal experience or conviction.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.267-286
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• 2023

The conversational agents such as AI speakers utilize voice conversation for human-computer interaction. Voice recognition errors often occur in conversational situations. Recognition errors in user utterance records can be categorized into two types. The first type is misrecognition errors, where the agent fails to recognize the user's speech entirely. The second type is misinterpretation errors, where the user's speech is recognized and services are provided, but the interpretation differs from the user's intention. Among these, misinterpretation errors require separate error detection as they are recorded as successful service interactions. In this study, various text separation methods were applied to detect misinterpretation. For each of these text separation methods, the similarity of consecutive speech pairs using word embedding and document embedding techniques, which convert words and documents into vectors. This approach goes beyond simple word-based similarity calculation to explore a new method for detecting misinterpretation errors. The research method involved utilizing real user utterance records to train and develop a detection model by applying patterns of misinterpretation error causes. The results revealed that the most significant analysis result was obtained through initial consonant extraction for detecting misinterpretation errors caused by the use of unregistered neologisms. Through comparison with other separation methods, different error types could be observed. This study has two main implications. First, for misinterpretation errors that are difficult to detect due to lack of recognition, the study proposed diverse text separation methods and found a novel method that improved performance remarkably. Second, if this is applied to conversational agents or voice recognition services requiring neologism detection, patterns of errors occurring from the voice recognition stage can be specified. The study proposed and verified that even if not categorized as errors, services can be provided according to user-desired results.