• 성인간호학회지
• /
• 제12권1호
• /
• pp.17-29
• /
• 2000

The purpose of this study is to find out the effects of depression on older adults' metamemory and memory performances. The subjects of the study consisted of 103 older adults over the age of 60 who are living in Kangwon Province. Some data were collected by means of the interview method, using questionnaires for metamemory (MIA questionnaire by Hultsch, et al., 1988), and depression(GDS by Yesavage and Sheikl, 1986). Other data were collected by a testing method on the memory performance, such as the immediate word recall task, the delayed word recall task, the word recognition task(Elderly Verbal Learning Test by Kyung Mi Choi, 1998), and the face recognition task(Face Recognition Task tool developed by this study). The results of this study were as follows: 1) The average point of depressed older persons' metamemory is 3.2 on a 5 point scale and was significantly lower than nondepressed older persons' point of 3.6. Looking into each sub-concept of metamemory, depressed persons' points are higher in terms of task(4.1), but are lower in terms of change(2.3), locus(2.6), and strategy(2.9) in comparison with nondepressed persons' points. 2) Depressed older persons' memory performances are all significantly lower than nondepressed person's, especially in terms of face recognition task(t=7.26, p<.0082) and word recognition task(t=6.58, p<.01). 3) In both depressed and nondepressed persons, metamemory has a close correlation with all memory tasks. In particular, depressed older persons' correlation is higher across the board, especially in memory self-efficacy of metamemory(r=.36 - .49) in comparison with nondepressed persons. 4) According to the results of analysis on the relations between metamemory and memory performances of each memory task using canonical analysis, in the case of depressed older persons, strategy, locus, capability and task have high correlation with word recognition task and delayed word recall task. Also in the case of nondepressed persons, achievement, strategy, change and locus variable have high correlation with face recognition task and immediate word recall task. As mentioned above, depression variables have a negative effect on older persons' metamemory and memory performance. In conclusion, when we care for depressed older persons with less memory ability, we have to consider the outcomes of this study are relevant. In addition, it is necessary to develop nursing intervention in order to prevent memory loss and improve memory performance in depressed older persons.

• 한국항행학회논문지
• /
• 제16권5호
• /
• pp.864-870
• /
• 2012

언어 학습 콘텐츠에서 공통적으로 가질 수 있는 문제점들을 분석하고 문제점에 대하여 음성 패턴인식기술을 적용하여 기존의 문제점을 해결하였다. 언어 학습 콘텐츠의 첫 번째 문제점은 온라인 학습 자세이다. 수업 진행은 되었지만 다른 웹 페이지를 열어 게임을 하는 등 학생들의 집중력은 떨어졌다. 두 번 째 문제점은 Speaking 학습 과정을 만들었지만 실제로 따라 읽는지 판단할 수가 없었다. 세 번 째 문제점은 학습 관리 시스템에 의한 기계적 진행이 아니라 선생님들의 평가에 의해 잘하는 학생들과 못하는 학생간의 학습 진행에 차이를 둘 필요가 생겼다. 마지막으로 가장 큰 문제는 기존에 만들어 놓은 콘텐츠들은 그대로 유지되면서 위의 문제들을 해결할 수 있어야 했다. 이러한 배경 하에 음성 패턴인식기술은 말하기 학습 전용 학습 프로그램으로 학습 진행을 위한 음성인식은 물론 학습 자체를 위한 음성인식 기능들을 모두 가지고 있으며 인식 절차에 사용된 학습자의 발화 데이터를 원하는 형태의 오디오 파일로 변경하여 서버의 특정 위치로 전송하거나 SQL서버에 등록할 수도 있으며, 또한 컴포넌트이기 때문에 그 어떠한 시스템이나 프로그램이라도 모두 적용 가능하고 이미 만들어진 콘텐츠 전체를 손상시키지 않고 쉽게 삽입하여 새로운 기능들을 사용할 수 있었다. 본 논문으로 교육 방식을 보다 인터렉티브하게 바꾸어 적극적인 수업참여가 되도록 기여하였다.

• 한국멀티미디어학회논문지
• /
• 제21권8호
• /
• pp.917-924
• /
• 2018

Recently, researches using LBP and SVM have been performed as one of the image - based methods for facial emotion recognition. LBP, introduced by Ojala et al., is widely used in the field of image recognition due to its high discrimination of objects, robustness to illumination change, and simple operation. In addition, CS(Center-Symmetric)-LBP was used as a modified form of LBP, which is widely used for face recognition. In this paper, we propose a method to detect four facial expressions such as expressionless, happiness, surprise, and anger using deep neural network. The validity of the proposed method is verified using accuracy. Based on the existing LBP feature parameters, it was confirmed that the method using the deep neural network is superior to the method using the Adaboost and SVM classifier.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.105.2-105
• /
• 2001

This paper studies continuous Korean Sign Language (KSL) recognition using color vision. In recognizing gesture words such as sign language, it is a very difficult to segment a continuous sign into individual sign words since the patterns are very complicated and diverse. To solve this problem, we disassemble the KSL into 18 hand motion classes according to their patterns and represent the sign words as some combination of hand motions. Observing the speed and the change of speed of hand motion and using state automata, we reject unintentional gesture motions such as preparatory motion and meaningless movement between sign words. To recognize 18 hand motion classes we adopt Hidden Markov Model (HMM). Using these methods, we recognize 5 KSL sentences and obtain 94% recognition ratio.

• 대한음성학회:학술대회논문집
• /
• 대한음성학회 2003년도 10월 학술대회지
• /
• pp.141-143
• /
• 2003

Speech recognition performance depends on various factors. One of the factors is the characteristic and established distance of a microphone which is used when speech data is collected. Thus, in the present experiment speech databases for tests are created through the type and established distance of a microphone. Then, acoustic models are built based on these databases, and each of the acoustic models is assessed by the data to determine recognition performance depending on various microphones and established microphone distances.

• 아동학회지
• /
• 제24권6호
• /
• pp.95-115
• /
• 2003

This research examined he effects on preschool children's recognition of and attitude towards earth's nature of an early childhood environmental education program using children's literature. The subjects were 36 four-to six-year old children. The education program lasted for 8 weeks. Children were interviewed and surveyed about earth's nature, and the meanings of children's writings about nature were analyzed. The children who participated in this research showed a positive recognition of and attitudes towards the nature of the earth. Participants became keen observers of the world around them, examined the concept of change in nature, acquired knowledge about the earth through firsthand experiences, and developed caring attitudes for the natural world of the earth.

• 한국정밀공학회지
• /
• 제20권4호
• /
• pp.223-229
• /
• 2003

Tool wear monitoring is an important technique in the flexible manufacturing system. This paper studies the end mill wear detection using CCD camera and pattern recognition method. When the end mill working in the machining center, the bottom edge of the end mill geometry change, this information is used. The CCD camera grab the new and worn tool geometry and the area of the tool geometry was compared. In this result, when the values of the subtract worn tool from new tool end in 200 pixels, it decides the tool life. This paper proposed the new method of the end mill wear detection.

• 음성과학
• /
• 제8권3호
• /
• pp.149-157
• /
• 2001

Based on the chaos theory, a new method of presentation of speech signal has been presented in this paper. This new method can be used for pattern matching such as speaker recognition. The expressions of attractors are represented very well by the logistic maps that show the chaos phenomena. In the speaker recognition field, a speaker's vocal habit could be a very important matching parameter. The attractor configuration using change value of speech signal can be utilized to analyze the influence of voice undulations at a point on the vocal loudness scale to the next point. The attractors arranged by the method could be used in research fields of speech recognition because the attractors also contain unique information for each speaker.

• 한국정보기술학회 영문논문지
• /
• 제8권2호
• /
• pp.79-87
• /
• 2018

The current PC user authentication uses character password based on user's knowledge. However, this can easily be exploited by password cracking or key-logging programs. In addition, the use of a difficult password and the periodic change of the password make it easy for the user to mistake exposing the password around the PC because it is difficult for the user to remember the password. In order to overcome this, we propose user gesture recognition and challenge-response authentication. We apply user's hand gesture instead of character password. In the challenge-response method, authentication is performed in the form of responding to a quiz, rather than using the same password every time. To apply the hand gesture to challenge-response authentication, the gesture is recognized and symbolized to be used in the quiz response. So we show that this method can be applied to PC user authentication.

• Journal of Information Science Theory and Practice
• /
• 제7권2호
• /
• pp.32-39
• /
• 2019

A convolutional neural network (CNN) has been widely used in facial expression recognition (FER) because it can automatically learn discriminative appearance features from an expression image. To make full use of its discriminating capability, this paper suggests a simple but effective method for CNN based FER. Specifically, instead of an original expression image that contains facial appearance only, the expression image with facial geometry visualization is used as input to CNN. In this way, geometric and appearance features could be simultaneously learned, making CNN more discriminative for FER. A simple CNN extension is also presented in this paper, aiming to utilize geometric expression change derived from an expression image sequence. Experimental results on two public datasets (CK+ and MMI) show that CNN using facial geometry visualization clearly outperforms the conventional CNN using facial appearance only.