• 로봇학회논문지
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• 제8권4호
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• pp.266-272
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• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권3호
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• pp.1390-1403
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• 2016

Facial expression recognition (FER) plays a very significant role in computer vision, pattern recognition, and image processing applications such as human computer interaction as it provides sufficient information about emotions of people. For video-based facial expression recognition, depth cameras can be better candidates over RGB cameras as a person's face cannot be easily recognized from distance-based depth videos hence depth cameras also resolve some privacy issues that can arise using RGB faces. A good FER system is very much reliant on the extraction of robust features as well as recognition engine. In this work, an efficient novel approach is proposed to recognize some facial expressions from time-sequential depth videos. First of all, efficient Local Binary Pattern (LBP) features are obtained from the time-sequential depth faces that are further classified by Generalized Discriminant Analysis (GDA) to make the features more robust and finally, the LBP-GDA features are fed into Hidden Markov Models (HMMs) to train and recognize different facial expressions successfully. The depth information-based proposed facial expression recognition approach is compared to the conventional approaches such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) where the proposed one outperforms others by obtaining better recognition rates.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• 제35권4호
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• pp.199-204
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• 2009

Purpose: The purpose of this study is to investigate the epithelial-mesenchymal transition (EMT) induced by Snail transcription factor and Snail-transfected in vivo tumors with histopathological features. Materials and methods: We induced in vivo xenografted tumorigenesis in the oral vestibules of nude mice by a Snail transfected HaCaT cell line and investigated morphological and immunohistochemical features in Snail expressive tumors. Results: We identified tumor masses in 14 out of 15 nude mice in the HaCaT-Snail cell inoculation group, but no tumors were present in any of the HaCaT cell inoculation group. Induced tumors showed features of poorly differentiated carcinoma with invasion to neighboring muscles and bones. The HaCaT-Snail tumors showed decreased expressions of E-cadherin and cytokeratin, but showed increased expressions of vimentin and N-cadherin. Discussion: The Snail transfected xenograft can improve productivity of malignant tumors, show various histopathological features including invasive growth, and aid in the investigation of tumor progression and the interaction with surrounding tissues.

• 천문학회보
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• 제39권1호
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• pp.43.1-43.1
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• 2014

It has been suggested that only the most luminous AGNs ($L{\geq}$ [10] $^{45}L_{\odot}$ ) are triggered by galaxy mergers, while less luminous AGNs (L~ [10] $^{43}L_{\odot}$) are driven by other internal processes. Lack of merging features in low luminosity AGN host galaxies has been a main argument against the idea of merger triggering of low luminosity AGNs, but merging, especially a rather minor one, might still have played an important role in low luminosity AGNs since minor merging features in low luminosity are more difficult to identify than major merging features. Using SNUCAM on the 1.5m telescope at Madanak observatory, we obtained deep images of NGC 7743 which is a barred spiral galaxy classified as a Seyfert 2 AGN with a low bolometric luminosity of $5{\times}$ [10] $^{42}L_{\odot}$. Surprisingly, we newly discovered merging features around the galaxy, which indicate past merging activity on the galaxy. This example indicates the merging fraction of low luminosity AGNs may be much higher than previously thought, hinting the importance of galaxy merger even in low luminosity AGN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2768-2787
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• 2023

As an important research direction of the application of computer science in the medical field, the automatic generation technology of radiology report has attracted wide attention in the academic community. Because the proportion of normal regions in radiology images is much larger than that of abnormal regions, words describing diseases are often masked by other words, resulting in significant feature loss during the calculation process, which affects the quality of generated reports. In addition, the huge difference between visual features and semantic features causes traditional multi-modal fusion method to fail to generate long narrative structures consisting of multiple sentences, which are required for medical reports. To address these challenges, we propose a multi-feature optimization Transformer (MFOT) for generating radiology reports. In detail, a multi-dimensional mapping attention (MDMA) module is designed to encode the visual grid features from different dimensions to reduce the loss of primary features in the encoding process; a feature pre-fusion (FP) module is constructed to enhance the interaction ability between multi-modal features, so as to generate a reasonably structured radiology report; a detail enhanced attention (DEA) module is proposed to enhance the extraction and utilization of key features and reduce the loss of key features. In conclusion, we evaluate the performance of our proposed model against prevailing mainstream models by utilizing widely-recognized radiology report datasets, namely IU X-Ray and MIMIC-CXR. The experimental outcomes demonstrate that our model achieves SOTA performance on both datasets, compared with the base model, the average improvement of six key indicators is 19.9% and 18.0% respectively. These findings substantiate the efficacy of our model in the domain of automated radiology report generation.

• 한국게임학회 논문지
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• 제11권4호
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• pp.37-48
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• 2011

최근 많은 사람들이 온라인 게임을 즐김에 따라 플레이어의 온라인 게임 이용 시간을 늘리기 위해 새로운 형태의 다양한 게임을 시장에 출시하고 있다. 하지만 왜 플레이어가 온라인 게임을 지속적으로 플레이하는지에 대한 연구는 그렇게 많지 않다. 본 연구는 플레이어의 온라인 게임 이용 시간의 주요한 요인이 되는 즐거운 경험의 이유를 분석하고자 한다. 이를 위해 본 연구에서는 몰입의 경험과 고객충성도간의 관계를 기초로 몰입을 증가시키기 위한 내적, 외적 보상의 종류에 대해 분석하였다. 먼저 Personal Interaction을 통해 플레이어가 얻고자 하는 외적 보상은 문제해결에 따른 보상의 형평성이며, 이를 통해 플레이어는 현재 자신이 목표성취를 잘 하고 있다고 느끼는 인지적 성과를 높게 경험하는 것으로 분석되었다. 두 번째, Social Interaction을 통해 플레이어는 타 플레이어로부터 긍정적인 평가를 받기를 원하며, 이를 통해 자아존중감이 높아지는 것으로 분석되었다. 결국 인지적 성과와 자아존중감은 온라인 게임을 통해 플레이어에게 몰입을 경험하게 만드는 주요한 요인이며, 이를 통해 게임을 계속 이용하겠다는 고객 충성도가 높아진다는 것을 알 수 있었다.

• 대한화학회지
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• 제61권5호
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• pp.251-262
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• 2017

이 연구에서는 협력적 멘토링에서 나타나는 멘토의 상호작용 특징과 멘토의 멘토링 경험에 따른 상호작용 특징의 변화에 대하여 알아보았다. 연구참여자는 교직경력 17년 이상의 멘토 3명과 초임중등과학교사 6명을 선정하였다. 일대일 멘토링 대화 녹음본 및 전사본을 수집하였고 이를 상호작용 분석틀을 이용하여 분석하였다. 협력적 멘토링 과정에서 나타나는 멘토의 상호작용의 특징을 분석 결과, 대체로 멘토들은 대화를 시작할 때 지원과 단순질문의 방법을 가장 많이 쓰고 있었다. 협력적 멘토링 과정에서 나타나는 멘토의 상호작용의 특징 변화를 보면, 멘토 3명의 멘토링 대화에서 대체로 1년차 멘토링에 비해 2년차 멘토링에서 사고질문이 많아졌으며, 이로 인하여 멘티의 반성 및 반성적 실천이 나타난 비율이 높아졌다. 멘토 인터뷰를 통하여 멘토들은 자신의 멘토링이나 멘티의 수업 변화를 보고 자신의 멘토링을 돌아보는 모습을 보였으며 이는 멘토링 프로그램을 통하여 멘토의 반성이 일어났음을 확인할 수 있다.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2007년도 International Conference
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• pp.640-645
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• 2007

In theese day, games are often referred as the most potential media to have artistic and entertaining features of digital technology, In this study, used to derive the factors of enjoyment and immersion that users experience from interaction and narrative levels in games were derived The framework of interaction and narrative levels in games was adopted from Marie-Laure Ryan's(2002) and Hyewon Han's(2005) study. The framework was used as the basic instrument for focus group interviews. The result of this study provides a practical model for game-design.

• Wind and Structures
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• 제5권2_3_4호
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• pp.101-114
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• 2002

Both a Finite Volume and a Discrete Vortex technique to solve the unsteady Navier-Stokes equations have been employed to study the air flow around long-span bridge decks. The implementation and calibration of both methods is described alongside a quasi-3D extension added to the DVM solver. Applications to the wind engineering of bridge decks include flow simulations at different angles of attack, calculation of aerodynamic derivatives and fluid-structure interaction analyses. These are being presented and their specific features described. If a numerical method shall be employed in a practical design environment, it is judged not only by its accuracy but also by factors like versatility, computational cost and ease of use. Conclusions are drawn from the analyses to address the question of whether computer simulations can be practical design tools for the wind engineering of bridge decks.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2012년도 제45회 KOSCO SYMPOSIUM 초록집
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• pp.85-87
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• 2012

We present a numerical investigation on gaseous (ethylene-air mixture) detonation in the elastoplastical metal tubes to understand the wall effects associated with the developing detonation instability. The acoustic disturbances originating from the rapidly expanding tube walls reach the detonating flame surface, thereby causing flame distortions and total energy losses. The compressible Navier-Stokes equations with equation of state for gas and elasto-plastic deformation field equations for inert tubes are solved simultaneously to understand the complex multi-material interaction in the rapidly expanding gas pipe. In order to track governing variables across the material interface, we use the hybrid particle level-set and ghost fluid methods to precisely estimate the interfacial quantities. Features observed from the deforming (thin) tube show substantially different behavior when a detonation propagates in the rigid (thick) tube with no acoustically responding wall conditions.