• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2002년도 추계학술대회 논문집
• /
• pp.80-84
• /
• 2002

In this study, researchers developed the est algorithm for artificial defects in the semic packages and performed to it by pattern recogn technology. For this purpose, this algorithm was I that researcher made software with matlab. The so consists of some procedures including ultrasonic acquistion, equalization filtering, self-organizing backpropagation neural network. self-organizing ma backpropagation neural network are belong to metho neural networks. And the pattern recognition tech has applied to classify three kinds of detective pa semiconductor packages. that is, crack, delaminat normal. According to the results, it was found estimative algorithm was provided the recognition r 75.7%( for crack) and 83.4%( for delamination) 87.2 % ( for normal).

• 고전문학과교육
• /
• 제15호
• /
• pp.245-264
• /
• 2008

This study considers Huewa悔窩 Anjung-gwan安重觀's self-consciousness and the recognition of the world. Anjung-gwan resents that fact that Qing淸 rules over China. He insists that Chosun朝鮮 must remain faithful to Ming明. But Chosun served Qing in those days. He holds strongly to his belief until his death. So he chooses living in retirement in his life. In Anjung-gwan's poems, we can see that a certain circle of Chosun Confucianists believe in Sojunghwa小中華, which is small-Sinocentrism. In the first half of the eighteenth-century, some Chosun Confucianists feel sad about the situation that stops them from realizing their ideals. But they take pride in natural beauty and configuration of Chosun. And they pay attention to the life of Chosun masses. They recognize Chosun, which is Hwa華, has to keep self-respect to the last.

• 한국학교수학회논문집
• /
• 제19권1호
• /
• pp.83-102
• /
• 2016

본 연구에서는 수학과 독서를 활용한 수학 수업이 학생들에게 정의적으로 어떠한 영향을 미치는지 탐구하였다. 중학교 2학년 100명의 남학생을 대상으로 정의적 특성요소로 흥미, 자신감, 가치인식, 자기조절력, 수학 불안 5개 요인을 조사해보고, 상 중 하 수준별 학생들에게 수학과 독서수업이 미치는 영향을 탐구하였다. 또 사전 사후 검사 결과와 학생의 인터뷰를 통해 바람직한 독서를 활용한 수업 방안을 모색하였다.

• 대한간호학회지
• /
• 제30권5호
• /
• pp.1170-1180
• /
• 2000

This study was a quasi-experimental study to confirm the effects of a memory training program using efficacy sources. The purpose was to develop an effective memory training program for elderly people and to identify the effects of the memory training program. This study was carried out between February 24 and July 18, 1999 and the subjects of the study were 102 elderly people who were participants at a welfare institute in Seoul. The experimental group (51) and the control group (51) were assigned by means of participation order. The control group was matched to the experimental group and was selected considering age, sex, and religion. The experimental group participated in the memory training program. The memory training program was based on the literature of Fogler & Stern (1994), Wang & Lee (1990), Lee (1991) and Lee (1993). The memory training program was given twice a week for two weeks with each program lasting two hours. Task centered memory self-efficacy was measured using the Memory Self-Efficacy Scale developed by Berry & Dennehey (1989) and Meta Memory was measured by the MIA developed by Dixon et al. (1988) Memory performance was measured by the word list developed by Cho Sung Won (1995) and the face recognition task (Face Recognition Task developed for this study). Data were analyzed by SPSS PC and the results are described below. 1. The experimental group which participated in the Memory Training Program showed higher task centered memory self-efficacy scores as compared to the control group (t=4.354, P=.0001). 2. The experimental group which participated in the Memory Training Program showed higher metamemory scores as compared to the control group (t=4.733, P=.0001). 3. The experimental group which participated in the Memory Training Program showed higher memory performance scores as compared to the control group (t=7.500, P=.0001). The memory performance involved an immediate word recall task, a delayed word recall task, a word recognition task, and the face recognition task. 4. In the experimental group, there was significant correlation between the task centered memory self-efficacy scores and the metamemory scores (r=.382, P=.006), but the correlation between the task centered memory self-efficacy scores and the memory performance scores and between the metamemory scores and the memory performance scores were not significant. The results showed that task centered memory self-efficacy, meta memory and memory performance improved following the Memory Training Program including the memory process, changes in memory with aging, and appropriate use of memory strategies. Memory Training Program is an effective nursing intervention for improving memory in elderly people and, also, in people with complaints of memory loss.

• 한국지능시스템학회논문지
• /
• 제12권1호
• /
• pp.52-60
• /
• 2002

최근 컴퓨터의 사용이 보편화되면서 악의적 사용자에 의해 발생하는 컴퓨터 바이러스와 해킹에 의한 피해가 급속히 증가하고 있다. 남의 컴퓨터에 침입하는 해킹이나 데이터를 파괴하는 컴퓨터 바이러스에 의한 피해를 막기 위해 최근에 생명체의 면역시스템의 특징을 이용해 인공면역계를 구성해 시스템 침입탐지와 바이러스 탐지 및 치료에 대한 연구가 활발히 진행 중에 있다. 생체 면역계는 외부에서 침입해 세포나 장기에 피해를 주는 물질인 항원을 스스로 자기세포와 구분해 인식.제거하는 기능이 있다. 이러한 면역계의 특징인 항원을 인식하는 기능은 자기세포의 확실한 인식을 가지고 있는 상태에서 다른 물질을 구분하는 자기.비자기 인식방법으로 똘 수 있다. 본 논문에서는 생체 면역계에서 세포독성 T세포의 생성과정의 하나인 Negative 및 Positive Selection을 모델링하여 침입에 의한 데이터 변경과 바이러스에 의한 데이터 감염 등을 탐지할 때 가장 중요한 요소인 자기 인식 알고리즘을 구현한다. 제안한 알고리즘은 큰 파일에서의 Detection을 구성하기 용이한 점을 가지며 국소(cell)변경과 블록(string)변경에 대한 자기인식률을 통해 알고리즘의 유효성을 검증한다.

• 한국지능시스템학회논문지
• /
• 제16권1호
• /
• pp.49-54
• /
• 2006

현재의 지문 인식 시스템은 지문 패턴의 복제와 지문 특징점의 해킹이라는 불안한 요소가 잠재되어 있어, 시스템 오동작의 주요 원인이 되기도 한다. 이에 본 논문에서는 신체의 일부인 지문을 주 핵심 인식기로 사용하고, 여기에 최근 널리 이용 되고 있는 화자 인증을 이용하여 직렬 형태의 다중 생체인식 시스템을 구현하였다. 구현된 시스템은 다중생체인식시스템으로 먼저 음성에 대한 인증과정이 성공하면 지문에 대한 인식과정을 수행하는 구조로 되어있다. 또한 효율적인 실시간 인증 처리를 위해 기존의 음성 인식 알고리즘 중에서 화자 종속형인 DTW(Dynamic Time Waning) 알고리즘을 사용하였으며, 지문 인식 알고리즘으로는 계산량을 고려하여 인공지능 기법인 KSOM(Kohonen Self-Organizing feature Map) 알고리즘을 적용하였다. 본 논문에서 구현한 다중생체 인식시스템을 실험한 결과 지문과 음성을 각각 이용한 단일인식시스템보다 본인거부율은 $2\~7\%$정도 떨어졌지만, 인식시스템에서 가장 중요한 요소인 타인수락율은 전혀 발생하지 않음을 확인하였다. 아울러 인식테스트 시간 또한 기존의 단일 생체 인식 시스템과 차이가 거의 없었으며, 인식에 걸린 시간은 평균 1.5초 정도였다. 이에 구현된 다중 생체 인의 시스템은 여러 가지 실험 결과 단일 인식 시스템보다 더 효율적인 보안 시스템임을 증명하였다.

• 한국학교보건학회지
• /
• 제22권1호
• /
• pp.17-32
• /
• 2009

Purpose: This study was performed to investigate the attitude and recognition on how to describe the elderly of elementary school students. Methods: The subject of this study was total 806 students of 4, 5, 6 grade at 2 elementary schools in Gyunggi-do. The data were collected through self-reporting questionnaires for a month. Results: First, the score of attitude about the elderly was 107.8 and image score was the highest. Second, there were significant differences in the attitude about the elderly according to grade, birth order of siblings, domestic atmosphere, and economic status, domestic education on respect about the elderly, and education about the elderly at school. Third, there were significant differences in the attitude about the elderly according to parent-grandparent relationship, health and economic status of grandparents, meeting frequency with grandparents. Fourth, the score of word recognition about the elderly was 43.3 and social score was the highest. fifth, there were significant differences in recognition on how to describe the elderly according to grade, birth order of siblings of students and parents, domestic atmosphere, and economic status, domestic education on respect about the elderly. Sixth, there were significant differences in recognition on how to describe according to parent-grandparent relationship, health status and economic status of grandparents, meeting frequency with grandparents. Lastly, The attitude and recognition about the elderly showed significant positive relationship. Conclusion: We should provide qualitative education programs to improve the attitude and recognition about the elderly of elementary school students.

• 보건행정학회지
• /
• 제20권3호
• /
• pp.157-172
• /
• 2010

This study was conducted to evaluate the effects of health-behavioral change for the elderly group after community based education of chronic diseases management. We measured self recognition of health status, medication administration of hypertension and diabetes, regular check for blood pressure and blood sugar level, recognition of body indicators (weight, hight, blood pressure, blood sugar etc), knowledge level for chronic diseases management and smoking and alcohol habitation before and after education of chronic diseases management for participants. The subjects of this study consist of 432 people with community-dwelling Seoul citizen being active churches. Education programs designed essential parts of fundamental chronic diseases management, physical exercises for health promotion, diet and nutrition etc. All data collection completed for 5 months from Aug. 2008 to Dec. 2008 by trained surveyors via interview survey. The data obtained were analyzed using descriptive statistics, Wilcoxon Singed Rank test, McNemar test and Paired t-test. The results showed that self recognition of health status, knowledge level for chronic diseases management, recognition of body indicators were statistically significantly increased after the education of chronic diseases management. Also, blood pressure were statistically significantly decreased in elderly with hypertension and blood sugar were statistically significantly decreased in elderly of high-risk group. Based on these results, it was suggested that preventive education policy of chronic diseases management should be considered with priority coming true for successful aging society.

• Journal of Information Processing Systems
• /
• 제14권6호
• /
• pp.1494-1507
• /
• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권6호
• /
• pp.1833-1848
• /
• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.