• 한국응급구조학회지
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• 제23권1호
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• pp.87-99
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• 2019

Purpose: The aim of this study was conducted to assess the proficiency of both direct laryngoscopy and video laryngoscopy and the usefulness of each laryngoscope, thereby provide basic data for further education using video laryngoscopy. Methods: Forty one paramedic subjects participated in this study. Usability was measured with the System usability scale. The Macintosh direct laryngoscope and $C-MAC^{(R)}$ video laryngoscope were two instruments evaluated in the study. Results: Training with video laryngoscopy showed significantly better results within the categories of dental injury (p=.004), esophageal intubation (p=.001), and proper depth placement of intubation tubes (p=.019). The results of the System usability scale questionnaire and the degrees of visibility based on the Cormack & Lehane classification were also found to be better achieved with the video laryngoscopy (p=.000). Conclusion: This study suggests enhancing education with video laryngoscopy, which could reduce the risk of complications and duration of intubation while increasing the success rate among students and emergency medical technicians with little experience, rather than the existing method of only using direct laryngoscope, which requires considerable experience and skills.

• 대한후두음성언어의학회지
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• 제7권1호
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• pp.43-49
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• 1996

In this study, remote articulation training system which connects the hearing disabled trainee and the speech therapist via B-ISDN is introduced. The hearing disabled does not have the hearing feedback of his own pronuciation, and the chance of watching his speech organs movement trajectory will offer him the self-training of articulation. So the system has two purposes of self articulation training and trainer's on-line checking in remote place. We estimate the vocal tract articultory movements from the speech signal using inverse modelling and display the movement trajectoy on the sideview of human face graphically. The trajectories of trainees articulation is displayed along with the reference trajectories, so the trainee can control his articulating to make the two trajectories overlapped. For on-line communication and ckecking training record the system has the function of video conferencing and tranferring articulatory data.

• 대한물리의학회지
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• 제8권3호
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• pp.351-360
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• 2013

PURPOSE: The purpose of this study was to investigate the effects of observed action gait training on stroke patients. METHODS: 22 subjects were randomized into two groups. The observed action gait training performed that watched a video of normal gait before gait training and the general gait training without watching it. The experimental group(n=11) performed observed action gait training and the control group(n=11) performed general gait training. Both group received gait training for 3 times per week during 8 weeks. RESULTS: The experimental group showed significant differences in the cadence, gait velocity, stride, step, single limb support, double limb support, stride length and step length(p<.05). The control group showed significant differences only in the stride(p<.05). CONCLUSION: The observed action gait training affected coordination and weight shift, as well as symmetry of the body. Plasticity of the brain was facilitated by repetitive visual and sensory stimulation. The observed action gait training promoted the normal gait by watching the normal gait pattern. In conclusion, motor learning through the sensory stimulation promotes brain plasticity that could improve motor function, and observed action gait training indirectly identified stimulated brain activities.

• 한국전문물리치료학회지
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• 제18권2호
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• pp.27-34
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• 2011

The aim of this study was to determine the effect of action-observation training on arm function in people with stroke. Fourteen chronic stroke patients participated in action-observation training. Initially, they were asked to watch video that illustrated arm actions used in daily activities; this was followed by repetitive practice of the observed actions for 3 times a week for 3 weeks. Each training session lasted 30 min. All subject participated 12 training session on 9 consecutive training days. For the evaluation of the clinical status of standard functional scales, Wolf motor function test was carried out at before and after the training and at 2 weeks after the training. Friedman test and Wilcoxon signed rank test was used to analyze the results of the clinical test. There was a significant improvement in the upper arm functions after the 3-week action-observation training, as compared to that before training. The improvement was sustained even at two weeks after the training. This result suggest that action observation training has a positive additional impact on recovery of stroke-induced motor dysfunctions through the action observation-action execution matching system, which includes in the mirror neuron system.

• 대한의용생체공학회:의공학회지
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• 제30권2호
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• pp.153-161
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• 2009

Mammogram is one of the important techniques for mass detection, which is the early diagnosis stage of a breast cancer. Especially, the CAD(Computer Aided Diagnosis) using mammogram improves the working performance of radiologists as it offers an effective mass detection. There are two types of CAD systems using mammogram; automatic and semi-automatic CAD systems. However, the automatic segmentation is limited in performance due to the difficulty of obtaining an accurate segmentation since mass occurs in the dense areas of the breast tissue and has smoother boundaries. Semi-automatic CAD systems overcome these limitations, however, they also have problems including high FP (False Positive) rate and a large amount of training data required for training a classifier. The proposed system which overcomes the aforementioned problems to detect mass is composed of the suspected area selection, the level set segmentation and SVM (Support Vector Machine) classification. To assess the efficacy of the system, 60 test images from the FFDM (Full-Field Digital Mammography) are analyzed and compared with the previous semi-automatic system, which uses the ANN classifier. The experimental results of the proposed system indicate higher accuracy of detecting mass in comparison to the previous systems.

• 전자통신동향분석
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• 제35권4호
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• pp.91-102
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• 2020

Recently, generative adversarial networks (GANs) is a field of research that has rapidly emerged wherein many studies conducted shows overwhelming results. Initially, this was at the level of imitating the training dataset. However, the GAN is currently useful in many fields, such as transformation of data categories, restoration of erased parts of images, copying facial expressions of humans, and creation of artworks depicting a dead painter's style. Although many outstanding research achievements have been attracting attention recently, GANs have encountered many challenges. First, they require a large memory facility for research. Second, there are still technical limitations in processing high-resolution images over 4K. Third, many GAN learning methods have a problem of instability in the training stage. However, recent research results show images that are difficult to distinguish whether they are real or fake, even with the naked eye, and the resolution of 4K and above is being developed. With the increase in image quality and resolution, many applications in the field of design and image and video editing are now available, including those that draw a photorealistic image as a simple sketch or easily modify unnecessary parts of an image or a video. In this paper, we discuss how GANs started, including the base architecture and latest technologies of GANs used in high-resolution, high-quality image creation, image and video editing, style translation, content transfer, and technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.4026-4040
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• 2019

In this paper, we present an approach for detecting slide transitions in lecture videos by introducing the spatio-temporal residual networks. Given a lecture video which records the digital slides, the speaker, and the audience by multiple cameras, our goal is to find keyframes where slide content changes. Since temporal dependency among video frames is important for detecting slide changes, 3D Convolutional Networks has been regarded as an efficient approach to learn the spatio-temporal features in videos. However, 3D ConvNet will cost much training time and need lots of memory. Hence, we utilize ResNet to ease the training of network, which is easy to optimize. Consequently, we present a novel ConvNet architecture based on 3D ConvNet and ResNet for slide transition detection in lecture videos. Experimental results show that the proposed novel ConvNet architecture achieves the better accuracy than other slide progression detection approaches.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 춘계학술발표대회
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• pp.35-38
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• 2009

The paper presents an effective method to detect fire in video surveillance and monitoring system. The main contribution of this work is that we successfully use the Hidden Markov Models in the process of detecting the fire with a few preprocessing steps. First, the moving pixels detected from image difference, the color values obtained from the fire flames, and their pixels clustering are applied to obtain the image regions labeled as fire candidates; secondly, utilizing massive training data, including fire videos and non-fire videos, creates the Hidden Markov Models of fire and non-fire, which are used to make the final decision that whether the frame of the real-time video has fire or not in both temporal and spatial analysis. Experimental results demonstrate that it is not only robust but also has a very low false alarm rate, furthermore, on the ground that the HMM training which takes up the most time of our whole procedure is off-line calculated, the real-time detection and alarm can be well implemented when compared with the other existing methods.

• 문화기술의 융합
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• 제8권6호
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• pp.67-77
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• 2022

본 연구에서는 디지털가면을 화상상담에 활용한 가면화상상담을 진행한 상담자들의 경험을 탐색하는데 그 목적이 있다. 이를 위하여 총 10사례에 대한 가면화상상담을 경험한 4명의 상담사와의 초점집단면접 자료가 주제분석방법을 활용하여 분석되었다. 상담사들은 가면화상상담에 대한 우려가 있었으나 점차 적응해나갔으며 편안함과 재미를 느꼈다. 그러나 화상상담에서보다 더 큰 피로와 부담감을 느껴 가면화상상담을 위한 추가적인 교육훈련이 필요하다고 보았다. 또한 내담자들의 신속한 자기개방과 상담과정을 관찰하면서 디지털가면이 상담매체로 활용될 가능성을 긍정적으로 전망하였다. 본 연구의 결과에 기초하여 우리는 온라인 상담매체 활용을 위한 상담자 지원이 필요함을 제언하였다.