• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.359-371
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• 2011

Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.

• Science of Emotion and Sensibility
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• v.10 no.2
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• pp.155-168
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• 2007

Social and psychological experiences in human-agent interactions are becoming more important than the task-oriented efficiency, as the influence of computer agents increases and human-agent interaction develops similarly with interpersonal interaction. Many previous studies aimed to increase social presence in human-agent interaction, in order to derive users' positive psychological experiences, by applying the factors of interpersonal communication to verbal and non-verbal communication of the agents. This study examined the effects of the exchanges of mutual self-disclosure, one of the most important communication acts in interpersonal communication, between users and interface agents. Users' attachment styles towards the perception of social presence, the evaluations toward the agents, user experiences, and the intentions for future interaction were also studied. The mediating role of social presence in dependent variables was, also, examined in this research. The results showed that exchanging self-disclosures with an agent increased the perceptions of social experience, friendly evaluations toward the agent, positive user experience, and the intentions for future interaction. Participants' attachment styles, also, affected the perceptions of the dependent variables. The effects of the exchanges of self-disclosure and participants' attachment styles were mediated by perceived social presence toward the agent. The findings of this study imply that the social and communicational aspects need to be considered in design of the agents seriously. The results also suggest that there may be differences in the psychological effects of agents on users according to the users' personality.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.1
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• pp.106-113
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• 2002

In this paper, breakdown characteristics of pure Kr, Ar and $N_2$gas with gas pressure range were investigated, and the measured values were compared with those in Ar/$N_2$and Kr/$N_2$gas mixtures with pressure varying. Also, various characteristics with gas mixtures in practical incandescent lamps were investigated. Summarizing the experimental results, the breakdown voltages of $N_2$gas were increased than those of Kr and Ar gas with large molecular weight, and the breakdown voltage increased with gas pressure increasing. The breakdown voltages of Ar/$N_2$and Ar/$N_2$gas mixtures were decreased with decreasing the mixtures ratio of $N_2$gas, and corona inception voltage of Kr/$N_2$gas mixtures under non-uniform fields were increased than those of Ar/$N_2$gas mixtures. In case of tactical incandescent lamps, luminous and lifetime of Kr(70%)/$N_2$(30%) gas mixtures were increased about 94[lm] and 380[hr] than those of Ar(70%)/$N_2$(30%) gas mixtures. and injection pressure of gas mixtures with cooling temperature of 20[$^{\circ}C$] in incandescent lamps were increased about 13[%] than those with cooling temperature of 40[$^{\circ}C$].

• Proceedings of the Korean Association for Survey Research Conference
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• 2005.12a
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• pp.91-113
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• 2005

본 연구는 청년들의 취업 및 실업 경험이 정신건강에 어떠한 영향을 미치는지 종단적으로 알아보는 데 목적이 있다. 구체적으로 대학을 졸업하고 난 이후에 지속적으로 미취업 상태로 남아있는 사람들의 정신건강의 문제 그리고 취업에 성공하는 경험이 정신건강에 미치는 영향을 미치는지 알아보고자 한다. 이를 위해서 국내 대학교 4학년생들을 대상으로 1차 조사를 실시하고 이후 약 6개월 간격으로 2차 조사, 3차 및 4차 조사를 실시하였다. 네 시점에서 모두 응답자들의 취업여부와 정신건강 수준을 측정하였다. 4차 조사까지 모두 응답한 560명 중에서 2차, 3차, 및 4차 시점의 취업여부에 의해서 집단을 다음과 같이 나누었다: 2차, 3차 및 4차 시점 순서대로, 모두 취업 상태인 집단('취업-취업-취업 집단'), 3차 시점에서 취업에 성공한 집단('미취업-취업-취업 집단'), 4차 집단에서 취업에 성공한 집단('미취업-미취업-취업집단') 그리고 모두 미취업 상태인 집단('미취업-미취업-미취업 집단'). 그 결과를 보면, 취업-취업-취업 집단의 경우에는 취업에 성공한 2차 시점에서 정신건강 수준이 상당히 좋아졌다가 3차 및 4차 시점에서 다시 본래 수준으로 돌아가는 경향을 보였다. 미취업-취업-취업 집단의 경우에는 취업에 성공한 3차 시점 이후로, 미취업-미취업-취업 집단의 경우에는 취업에 성공한 4차 시점에서 정신건강 수준이 좋아지는 경향을 보였다. 지속적으로 미취업 상태였던 집단에서는 3차 시점에서 정신건강 수준이 상당히 나빠졌다가 여전히 미취업 상태인 4차 시점에서 오히려 완화되는 경향을 보였다. 본 연구의 시사점과 제한점 및 장래 연구의 과제가 논의되었다.iments and numerical analysis of luminescence efficiency in the hole carrier transport layer's thicknes. 나아갈 것이며, 아울러 향후에도 아직 미흡한 분야인 IT 아웃소싱에서 적정수준의 대가지급 방안 및 바람직한 Relationship 에 영향을 미치는 여러 가지 요인에 대해서도 살펴 봄으로써 IT분야의 Outsourcing을 검토하거나, 추진할 때 도움이 될 수 있도록 하고자 한다.개의 총 297개의 데이터를 추출하여 사용하였다. 실험과는 좌측공격 91.7%, 우측공격 100%, 중앙공격 87.5%, 코너킥 97.4%, 프리킥 75%로서 매우 양호한 인식율을 보였다. 사용경험정도가 가입직후 해지에만 영향을 미치는 요인임을 보여준다. 또한 매체의 정보전달 풍부성 (media richness)이 상대적으로 높은 소매점이나 웹사이트를 통해 서비스에 가입한 소비자일수록 가입 직후뿐만 아니라 서비스사용 이후에도 낮은 해지성향을 나타냈다. 이러한 분석결과를 바탕으로 인터넷전화 서비스에 적합한 고객지원 프로그램 설계와 마케팅 매체선정과 관련한 전략적 시사점을 도출한다. 그리고 국내에서 최근 이슈가 되고 있는 차세대 무선인터넷 서비스인 와이브로 출시에 따른 마케팅 및 고객관리와 관련된 시사점을 논의한다.는 교합면에서 2, 3, 4군이 1군에 비해 변연적합도가 높았으며 (p < 0.05), 인접면과 치은면에서는 군간 유의차를 보이지 않았다 이번 연구를 통하여 복합레진을 간헐적 광중합시킴으로써 변연적합도가 향상될 수 있음을 알 수 있었다.시장에 비해 주가가 비교적 안정적인 수준을 유지해 왔다고 볼

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.7
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• pp.550-559
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• 2018

The effectiveness of deep neural networks (DNNs) for detection and classification of micro-Doppler signals generated by human walking and background noise sources is investigated. Previous research included a complex process for extracting meaningful features that directly affect classifier performance, and this feature extraction is based on experiences and statistical analysis. However, because a DNN gradually reconstructs and generates features through a process of passing layers in a network, the preprocess for feature extraction is not required. Therefore, binary classifiers and multiclass classifiers were designed and analyzed in which multilayer perceptrons (MLPs) and DNNs were applied, and the effectiveness of DNNs for recognizing micro-Doppler signals was demonstrated. Experimental results showed that, in the case of MLPs, the classification accuracies of the binary classifier and the multiclass classifier were 90.3% and 86.1%, respectively, for the test dataset. In the case of DNNs, the classification accuracies of the binary classifier and the multiclass classifier were 97.3% and 96.1%, respectively, for the test dataset.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.745-756
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• 2009

An autonomous virtual character can conduct itself like a human after recognizing and interpreting the virtual environment. Artificial vision is mainly used in the recognition of the environment for a virtual character. The present artificial vision that has been developed takes all the information at once from everything that comes into view. However, this can reduce the efficiency and reality of the system by saving too much information at once, and it also causes problems because the speed slows down in the dynamic environment of the game. Therefore, to construct a vision system similar to that of humans, a visual observation system which saves only the required information is needed. For that reason, this research focuses on the descriptive artificial intelligence engine which detects the most important information visually recognized by the character in the virtual world and saves it into the memory by degrees. In addition, a visual system is constructed in accordance with an image transaction theory to make it sense and recognize human feelings. This system finds the attention area of moving objects quickly and effectively through the experiment of the virtual environment with three dynamic dimensions. Also the experiment enhanced processing speed more than 1.6 times.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.268-273
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• 2017

Recently, deep learning encoder-based approach has been actively applied in the field of sentiment classification. However, Long Short-Term Memory network deep learning encoder, the commonly used architecture, lacks the quality of vector representation when the length of the documents is prolonged. In this study, for effective classification of the sentiment documents, we suggest the use of attention method-based deep learning encoder that generates document vector representation by weighted sum of the outputs of Long Short-Term Memory network based on importance. In addition, we propose methods to modify the attention method-based deep learning encoder to suit the sentiment classification field, which consist of a part that is to applied to window attention method and an attention weight adjustment part. In the window attention method part, the weights are obtained in the window units to effectively recognize feeling features that consist of more than one word. In the attention weight adjustment part, the learned weights are smoothened. Experimental results revealed that the performance of the proposed method outperformed Long Short-Term Memory network encoder, showing 89.67% in accuracy criteria.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.357-373
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• 2006

Virtual reality (VR) provides a virtual experiment (VE) context consisting of information presented to the senses of the user. The user perceiver and interprets the VE context, and then naturally recognizes a level of realism in the VE. Presence is often thought of as the sense of 'being there' in the n. Presence includes overall feelings about the information conveyed from a virtual avatar to the user. Therefore, there must be brain mechanisms for integrating sensory information about presence.'Feeling of presence' is related with the user's cognition and perception about information on communication through medium. Thus 'feeling of presence' may characterize perceptual mechanisms in the brain. We studied these mechanisms by presenting a VR that consisted of an avatar telling a story about a social conversation. We performed covariance analysis on subjective brain activity (fMRI) during the story presentation with a presence score. The data analysis revealed that activity in several brain areas was correlated with the presence store. A positive correlation was shown in the right lingual gyrus, right cuneus, left lingual gyrus, right fusiform gyrus, left inferior temporal gyrus, anterior cingulate cortex and right posterior cingulate cortex of the brain. This study showed the brain mechanism to be related the feeling of presence and brain activities in our subjects, using VR to communicate information.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.17-35
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• 2011

The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.863-872
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• 2015

Kernel rootkit is recognized as one of the most severe and widespread threats to corrupt the integrity of an operating system. Without an external monitor as a root of trust, it is not easy to detect kernel rootkits which can intercept and modify communications at the interfaces between operating system components. To provide such a monitor isolated from an operating system that can be compromised, most existing solutions are based on external hardware. Unlike those solutions, we develop a kernel introspection system based on the ARM TrustZone technology without incurring extra hardware cost, which can provide a secure memory space in isolation from the rest of the system. We particularly use a secure timer to implement an autonomous switch between secure and non-secure modes. To ensure integrity of reference, this system measured reference from vmlinux which is a kernel original image. In addition, the flexibility of monitoring block size can be configured for efficient kernel introspection system. The experimental results show that a secure kernel introspection system is provided without incurring any significant performance penalty (maximum 6% decrease in execution time compared with the normal operating system).