• Journal of Chest Surgery
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• v.34 no.7
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• pp.552-555
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• 2001

Noonan syndrome is characterized by a Turner-like phenotype and a normal karyotype associated with congenital abnormalities, such as short stature, variable mental retardation, hypertelorism, webbed neck, low posterior hair line, skeletal malformation and congenital cardiovascular defect. Two third of Noonan syndrome have cardiac anormalies, half with pulmonary stenosis. We have experienced two cases of pulmonary stenosis associated with other cardiac anomalies in Noonan syndrome. The first 31-year-old male patient had characteristic appearance of Noonan syndrome with severe infundibular pulmonic stenosis and patent foramen ovate. The second 28-year-old male patient had valvular and subvalvular Pulmonary stenosis with typical Noonan\`s face and stature. Pulmonary valvotomy and hypertrophied muscle bundles in the right ventricular cavity were resected in both cases. Patent foramen ovate was closed directly in the first case. Postoperative follow-up examinations revealed no symptoms and successful outcome.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6708-6714
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• 2015

Various types of multimedia contents have been widely spread and distributed with the Internet that is easy to use. Meanwhile, Multimedia contents can bright a social problem because juveniles can access such harmful contents easily through the Internet. This paper proposes a method to determine if an input image is harmful or not, using an neural network. The proposed method first detects a face region from an input image through MCT features. The method then extracts skin color regions using color features and obtains candidate nipple areas from the extracted skin regions. Subsequently, we determine if the input image is harmful, by filtering out non-nipple regions using the artificial neural network. Experimental results show that the proposed method can effectively determine the harmfulness of input images.

• Conservation Science in Museum
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• v.6
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• pp.47-54
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• 2005

The elements of the pigments used on the wall painting in Ssangyeongchong (Tomb of Two Pillars) from Goguryeo in the Nampo area of Pyeongyang were analyzed to confirm their mineral compositions and features of the painting. Specifically, the non-destructive X-ray fluorescence spectrometer (XRF) was used. On the other hand, the mineral composition of the background and pigment layers were analyzed using an X-ray diffractometer (XRD). The results of these analyses suggested that the lips of the characters in the painting were painted with HgS, and their faces, painted with HgS(Cinnabar/ vermilion) mixed with CaCO₃. Note that lead white pigment [2PbCO₃·Pb(OH)₂] was found only on the bottom layer of the painting, indicating that the wall painting was likely to have been created using the Secco method.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.563-571
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• 2017

The purpose of this paper is to establish an emotional expression factors of digital eye contents that can be applied to digital environments. The emotion which can be applied to the smart doll is derived and we suggest guidelines for expressive factors of each emotion. For this paper, first, we research the concepts and characteristics of emotional expression are shown in eyes by the publications, animation and actual video. Second, we identified six emotions -Happy, Angry, Sad, Relaxed, Sexy, Pure- and extracted the emotional expression factors. Third, we analyzed the extracted factors to establish guideline for emotional expression of digital eyes. As a result, this study found that the factors to distinguish and represent each emotion are classified four categories as eye shape, gaze, iris size and effect. These can be used as a way to enhance emotional communication effects such as digital contents including animations, robots and smart toys.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• Journal of Genetic Medicine
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• v.8 no.2
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• pp.130-134
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• 2011

Saethre-Chotzen syndrome is an autosomal dominant craniosynostosis syndrome, usually involving unior bilateral coronal synostosis and mild limb deformities, and is induced by loss-of-function mutations of the TWIST1 gene. Other clinical features of this syndrome include ptosis, low-set ears, hearing loss, hypertelorism, broad great toes, clinodactyly, and syndactyly. The authors of the present study report 2 children with clinical features of Saethre-Chotzen syndrome who showed mutations in the TWIST1 gene, and is the first molecular genetic confirmation of Saethre-Chotzen syndrome in Korea. The molecular genetic testing of the TWIST1 gene for patients with coronal synostoses is important to confirm the diagnosis and to provide adequate genetic counseling.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.1-9
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• 2015

In this paper, a study on facial movements are analyzed in terms of opposite emotion stimuli by image processing of Kinect facial image. To induce two opposite emotion pairs such as "Sad - Excitement"and "Contentment - Angry" which are oppositely positioned onto Russell's 2D emotion model, both visual and auditory stimuli are given to subjects. Firstly, 31 main points are chosen among 121 facial feature points of active appearance model obtained from Kinect Face Tracking SDK. Then, pixel changes around 31 main points are analyzed. In here, local minimum shift matching method is used in order to solve a problem of non-linear facial movement. At results, right and left side facial movements were occurred in cases of "Sad" and "Excitement" emotions, respectively. Left side facial movement was comparatively more occurred in case of "Contentment" emotion. In contrast, both left and right side movements were occurred in case of "Angry" emotion.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1053-1065
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• 2020

With the recent development of hardware performance and artificial intelligence technology, sophisticated fake videos that are difficult to distinguish with the human's eye are increasing. Face synthesis technology using artificial intelligence is called Deepfake, and anyone with a little programming skill and deep learning knowledge can produce sophisticated fake videos using Deepfake. A number of indiscriminate fake videos has been increased significantly, which may lead to problems such as privacy violations, fake news and fraud. Therefore, it is necessary to detect fake video clips that cannot be discriminated by a human eyes. Thus, in this paper, we propose a deep-fake detection model applied with Bidirectional Convolution LSTM and Attention Module. Unlike LSTM, which considers only the forward sequential procedure, the model proposed in this paper uses the reverse order procedure. The Attention Module is used with a Convolutional neural network model to use the characteristics of each frame for extraction. Experiments have shown that the model proposed has 93.5% accuracy and AUC is up to 50% higher than the results of pre-existing studies.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.565-567
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• 2022

질병을 앓고 있는 환자는 상태에 따라 병실, 주거지, 요양원 등 조호환경 내 생활 시 의료 인력의 지속적인 추적 및 관찰을 통해 신체에 이상이 생긴 경우 이를 감지하고, 신속하게 조치할 수 있도록 해야 한다. 의료 인력이 직접 환자를 확인하는 방법은 의료 인력의 반복적인 노동이 요구되며 실시간으로 환자를 확인해야 한다는 특성상 의료 인력이 상주해야 하기에 이는 곧, 의료 인력의 부족과 낭비로 이어진다. 해당 문제 해결을 위해 의료 인력을 대신하여 조호환경 내 환자의 상태를 실시간으로 모니터링할 수 있는 딥러닝 모델들이 연구되고 있다. 딥러닝 모델은 데이터의 수가 많을수록 강인한 모델을 설계할 수 있으며, 데이터셋의 배경, 객체의 특징 분포 등 다양한 조건에 영향을 받기 때문에 학습에 필요한 도메인을 가지는 많은 양의 전처리된 데이터를 수집해야 한다. 따라서, 조호환경 내 환자에 대한 데이터셋이 필요하지만, 공개된 데이터셋의 경우 양이 매우 적으며 이를 반전, 회전기법 등을이용할 경우 데이터의 수를 늘릴 수 있지만, 같은 분포의 특징을 가지는 데이터가 생성되기에 데이터 증강 기법을 단순하게 적용하면 딥러닝 모델의 과적합을 야기한다. 또한, 조호환경 내 이미지 데이터셋은 얼굴 노출과 같은 개인정보가 포함 될 수 있으며 이를 보호하기 위해 정보들을 비식별화 해야 한다는 문제점이 있다. 따라서 본 논문에서는 조호환경에서 수집된 데이터 증강을 위한 Style-Generative Adversarial Networks 기법을 적용하여 조호환경 데이터셋 수집에 효과적인 증강 기법을 제안한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1779-1786
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• 2009

Due to increased terrors and crimes, the use of surveillance camera systems including CCTV is also increasing. Private information such as faces or behavior patterns can be recorded in CCTV and when it is exposed, it may cause infringement to privacy and crimes. This paper analyses conventional methods on protection of privacy in surveillance camera system and then suggests an RFID-based surveillance camera system that can both watch crimes and protect privacy. The proposed system protects privacy and watches crimes using scrambling and an RFID system.