• Animal cells and systems
• /
• 제3권2호
• /
• pp.181-185
• /
• 1999

Xenopus oocyte is one of the widely used heterologous expression systems of ion channels for electrophysiological studies. Here we describe a new method in which cRNA produced by polymerase chain reaction (PCR) and in vitro transcription is injected to express ion channels in oocytes. This method enables us (1) to eliminate all or a part of the untranslated region of the cDNA and to replace it with a known sequence which helps increase the expression level in oocytes, and (2) to use the PCR product for in vitro transcription without subcloning. Using this method, the expression level of one of the neuronal nicotinic acetylcholine receptors (nAChRs) $\alpha$$_{6}$ subtype in oocytes was systematically increased by more than 100-fold, which was confirmed both by the $\alpha$-Bungarotoxin ($\alpha$,/TEX>Bgt) binding assay and the current measurement.t.

• 한국의류학회지
• /
• 제25권4호
• /
• pp.783-794
• /
• 2001

This research focuses its study on the expressions of the visual images of the fashion illustration as a part of visual art and utilizes it to formulate the theoretical basis. Main findings of our research are as follows: The structure of communications in the fashion illustration is based on the four elements. They are the expression of the texture, drawings, composition, and the human body and dress. The characteristics in expression of texture level in fashion illustration can be the expression of creative texture in pattern or crease, and also can be expressed as various collage and photomontage by computer graphics. Secondly, the analysis on the characteristics of the drawings show that the drawing skills are imagination and sequential drawings. Thirdly, the characteristics of composition method are mainly shown as the application of plane composition which was previously used in avant-garde arts. Fourthly, most of the human body in the fashion illustrations are shown as the results of simplification, exaggeration and deformation in human body and also expressed or analyzed by the method of the body modification. Based on the above findings of this research we conclude that the way of expression in the fashion illustration is very similar in its composition as in visual art. However, they also show differences between the two in expression method or the method for the image development in specific expressions.

• Journal of Information Processing Systems
• /
• 제17권2호
• /
• pp.337-351
• /
• 2021

Automatically recognizing facial expressions in video sequences is a challenging task because there is little direct correlation between facial features and subjective emotions in video. To overcome the problem, a video facial expression recognition method using spatiotemporal recurrent neural network and feature fusion is proposed. Firstly, the video is preprocessed. Then, the double-layer cascade structure is used to detect a face in a video image. In addition, two deep convolutional neural networks are used to extract the time-domain and airspace facial features in the video. The spatial convolutional neural network is used to extract the spatial information features from each frame of the static expression images in the video. The temporal convolutional neural network is used to extract the dynamic information features from the optical flow information from multiple frames of expression images in the video. A multiplication fusion is performed with the spatiotemporal features learned by the two deep convolutional neural networks. Finally, the fused features are input to the support vector machine to realize the facial expression classification task. The experimental results on cNTERFACE, RML, and AFEW6.0 datasets show that the recognition rates obtained by the proposed method are as high as 88.67%, 70.32%, and 63.84%, respectively. Comparative experiments show that the proposed method obtains higher recognition accuracy than other recently reported methods.

• 한국컴퓨터정보학회논문지
• /
• 제27권9호
• /
• pp.41-47
• /
• 2022

본 논문에서는 자동표정인식을 위하여 얼굴 이미지 배열의 가운데 이미지를 예측하는 새롭고 간단한 자기주도학습 방법을 제안한다. 자동표정인식은 딥러닝 모델을 통해 높은 성능을 달성할 수 있으나 일반적으로 큰 비용과 시간이 투자된 대용량의 데이터 세트가 필요하고, 데이터 세트의 크기와 알고리즘의 성능이 비례한다. 제안하는 방법은 추가적인 데이터 세트 구축 없이 기존의 데이터 세트를 활용하여 자기주도학습을 통해 얼굴의 잠재적인 심층표현방법을 학습하고 학습된 파라미터를 전이시켜 자동표정인식의 성능을 향상한다. 제안한 방법은 CK+와 AFEW 8.0 두가지 데이터 세트에 대하여 높은 성능 향상을 보여주었고, 간단한 방법으로 큰 효과를 얻을 수 있음을 보여주었다.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 1999년도 하계종합학술대회 논문집
• /
• pp.651-654
• /
• 1999

In this paper we propose an emotional expression method using a comic model and special marks for effective sign-language communications. Until now we have investigated to produce more realistic facial and emotional expression. When representing only emotional expression, however, a comic expression could be better than the real picture of a face. The comic face is a comic-style expression model in which almost components except the necessary parts like eyebrows, eyes, nose and mouth are discarded. In the comic model, we can use some special marks for the purpose of emphasizing various emotions. We represent emotional expression using Action Units(AU) of Facial Action Coding System(FACS) and define Special Unit(SU) for emphasizing the emotions. Experimental results show a possibility that the proposed method could be used efficiently for sign-language image communications.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 1999년도 추계종합학술대회 논문집
• /
• pp.536-539
• /
• 1999

In this paper we propose a 3D emotional expression method using a comic model for effective sign-language communications. Until now we have investigated to produce more realistic facial and emotional expression. When representing only emotional expression, however, a comic expression could be better than the real picture of a face. The comic face is a comic-style expression model in which almost components except the necessary parts like eyebrows, eyes, nose and mouth are discarded. We represent emotional expression using Action Units(AU) of Facial Action Coding System(FACS). Experimental results show a possibility that the proposed method could be used efficiently for sign-language image communications.

• Journal of Microbiology and Biotechnology
• /
• 제12권5호
• /
• pp.841-843
• /
• 2002

Pfu DNA polymerase from Pyrococcus furiosus was expressed in the E. coli periplasm, and the fully active polymerase was partially purified by applying osmotic shock, ammonium sulfate precipitation, and heat treatment. This method represents a new way of expressing and purifying functional Pfu DNA polymerase without the use of chromatography.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
• /
• pp.473-476
• /
• 2000

The network reliability is to be computed in terms of the terminal reliability. The computation of a termini reliability is started with a Boolean sum of products expression corresponding to simple paths of the pair of nodes. This expression is then transformed into another equivalent expression to be a Disjoint Sum of Products form. But this computaion of the terminal reliability obviously does not consider the communication between any other nodes but for the source and the sink. In this paper, we derive the overall network reliability which is the probability of communication that each node in the network communicates with all other remaining nodes. For this, we propose a method to make the SOP disjoint for deriving the network reliability expression from the system success expression using the modified Sheinman's method and modified BDD method.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (C)
• /
• pp.236-241
• /
• 2008

본 논문은 표현 패턴(expression patterns)을 이용한 한국어-영어 기계 번역 방법에 대하여 논의한다. 표현 패턴은 한국어-영어 기계 번역을 위하여 의미적이고 표현적인 관점에서 한국어 표현에 적합한 영어 표현을 대응하여 정의하였다. 그리고 새로운 한국어 파싱 방법을 개발할 것을 제안하였다. 한국어 파싱 방법은 한국어의 교착어로서의 특징, 표현 패턴 개념, 문장 분할 개념, 그리고 파싱 과정에 의미 구조를 포함하는 개념 등을 포함하여 개발할 것을 주장하였다. 논문의 마지막 부분에는 간단한 한국어 문법을 정의하여 새로운 한국어 구문 분석 방법의 가능성을 제시하였다.

• 한국멀티미디어학회논문지
• /
• 제20권5호
• /
• pp.748-757
• /
• 2017

In order to recognize the facial expressions, good features that can express the facial expressions are essential. It is also essential to find the characteristic areas where facial expressions appear discriminatively. In this study, we propose a directional LBP feature for facial expression recognition and a method of finding directional LBP operation and feature region for facial expression classification. The proposed directional LBP features to characterize facial fine micro-patterns are defined by LBP operation factors (direction and size of operation mask) and feature regions through AdaBoost learning. The facial expression classifier is implemented as a SVM classifier based on learned discriminant region and directional LBP operation factors. In order to verify the validity of the proposed method, facial expression recognition performance was measured in terms of accuracy, sensitivity, and specificity. Experimental results show that the proposed directional LBP and its learning method are useful for facial expression recognition.