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생애사 접근을 활용한 노인미술교육 사례연구: 노년기 정체성 형성을 중심으로
김송희(Songhee KIM),안혜리(Hyeri AHN) 한국조형교육학회 2020 造形敎育 Vol.0 No.73
이 연구는 노년기 정체성 확립이라는 관점에서 생애사 접근을 활용한 노인미술교육 프로그램을 설계 및 실행해보고 그 학습 성과를 고찰하고자 한다. 2018년에 서울시의 한 종합사회복지관에서 만70세 이상 노인 참여자 7명을 대상으로 질적 사례연 구를 진행하였다. 연구 결과는 다음과 같다. 첫째, 노인학습자들의 자발적인 자기표현에 대한 자신감이 향상되었다. 둘째, 노인학습자들의 억압된 감정이 표현되고 해소됨으로써 자기를 수용하게 되었다. 셋째, 동질적인 생애사 경험의 공유와 공감 을 통해 노인학습자 간에 사회적 유대감을 형성하게 되었다. 넷째, 노인학습자들은 전시회와 ‘작가와의 만남’을 통해 지역사 회 내의 세대공동체 교육에 참여하게 되었다. 이러한 학습성과는 노인학습자로 하여금 자기를 성찰하고 인생의 의미를 발견 하도록 이끌어 궁극적으로 노년기 정체성을 형성하는데 이바지할 수 있다 This study seeks to design and implement an art education program for older adults using a life history approach, and to explore learning outcomes of the program. This qualitative case study involved seven older adults participants, age 70 and over in a social welfare center in Seoul. The result of the study is as follows: firstly, the older adult learners became confident in spontaneous self-expression; secondly, the older adult learners came to accept themselves through expressing and relieving their repressed emotions; thirdly, the older adult learners formed social ties through sharing and empathizing with their similar life histories; fourthly, the older adult learners came to participate in intergenerational education through an exhibition and “meet the author” book talk. These learning outcomes led the old adult learners toward self reflection and discovering meaning and ultimately constructing their identities in old age.
중국에서 개인적 영성추구 활동의 등장원인과 의미 ― ‘상하이 리푸 심령센터(上海丽夫心灵中心)’의 활동을 중심으로
김송희 ( Kim Songhee ) 고려대학교 중국학연구소 2021 中國學論叢 Vol.- No.71
The purpose of this thesis is to examine the reason and meaning of emergence of personal spiritual activities in China. To this end, the analysis targets the spiritual activities conducted at the “Shanghai Lifu Psychic Center”. China’s personal spiritual activities have a view of the universe and a world view, which are the basis of their ideology, and are experiencing spiritual awareness. In other words, they are engaged in a religious activity that pursues their own ultimate enlightenment and truth. From this perspective, personal spiritual activity can be seen as a new form of religious activity emerging in China. The reason for the emergence of personal spiritual activities in China is that the Chinese people’s interest in self has increased and a social environment has been created for this. In the void of the value system created by the dissolution of the ‘unit’ and ‘commune’ after the reform and opening up, Chinese think that they are the only ones who can protect themselves. As the self becomes the criterion for value judgment, Chinese are more focused on how they can discover and realize their true nature or their potential nature. And the Chinese people chose the alternative form of pursuit of personal spirituality because of its skepticism and unfamiliarity with the institutional religion itself. Due to the traditional religious customs of the Chinese people and the characteristics of the socialist state system, Chinese are not trained in religious practices within institutionalized religious organizations and religious systems. And recently, the formation of a market for religious and cultural contents such as yoga, meditation has become a social platform to further revitalize spiritual activities.
차량 센서 데이터 조합을 통한 딥러닝 기반 차량 이상탐지
김송희(Songhee Kim),김선혜(Sunhye Kim),윤병운(Byungun Yoon) 한국산학기술학회 2021 한국산학기술학회논문지 Vol.22 No.3
4차산업혁명 시대에는 대량의 데이터를 학습하여 예측과 분류의 정확성을 향상시킬 수 있는 인공지능의 활용이 핵심적이다. 그러나, 기존 이상탐지를 위한 방법은 제한된 데이터를 다루는 전통적인 통계 방법에 의존하고 있어, 정확한 이상탐지가 어렵다. 그러므로, 본 연구는 인공지능 기반 이상탐지 방법을 제시하여 예측 정확도를 높이고, 새로운 데이터 패턴을 정의하는 것을 목적으로 한다. 특히, 자동차의 경우 공회전 기간의 센서 데이터가 이상 탐지에 활용될 수 있다는 관점에서 데이터를 수집하고 분석하였다. 이를 위해, 예측 모델에 입력되는 데이터의 적정 시간 길이를 결정하고, 공회전 기간 데이터와 전체 운행 데이터의 분석 결과를 비교하며, 다양한 센서 데이터 조합에 의한 최적 예측 방법을 도출하였다. 또한, 인공지능 방법으로 선택된 CNN의 예측 정확성을 검증하기 위해 LSTM 결과와 비교하였다. 분석 결과, 공회전 데이터를 이용하고, 공회전 기간보다 1.5배 많은 기간의 데이터를 이용하며 LSTM보다는 CNN을 활용하는 것이 더 좋은 예측결과를 보였다. In the Industry 4.0 era, artificial intelligence has attracted considerable interest for learning mass data to improve the accuracy of forecasting and classification. On the other hand, the current method of detecting anomalies relies on traditional statistical methods for a limited amount of data, making it difficult to detect accurate anomalies. Therefore, this paper proposes an artificial intelligence-based anomaly detection methodology to improve the prediction accuracy and identify new data patterns. In particular, data were collected and analyzed from the point of view that sensor data collected at vehicle idle could be used to detect abnormalities. To this end, a sensor was designed to determine the appropriate time length of the data entered into the forecast model, compare the results of idling data with the overall driving data utilization, and make optimal predictions through a combination of various sensor data. In addition, the predictive accuracy of artificial intelligence techniques was presented by comparing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) as the predictive methodologies. According to the analysis, using idle data, using 1.5 times of the data for the idling periods, and using CNN over LSTM showed better prediction results.
김송희(Kim, Songhee) 한국어문학회 2017 語文學 Vol.0 No.136
The purpose of this article is to explore the meaning and function of an adverb ‘geoui’ and its following elements. ‘Geoui’ requires bounded words to be included in the following predicate. Therefore, the predicate following ‘geoui’ usually consists of a bounded adjective or a telic verb, which is semantically bounded. In addition, the adverb ‘geoui’ involves negative references and contextual boundary especially when it is followed by unbounded adjectives or atelic verbs. In these cases, ‘geoui’ is a degree adverb that designates proximity. On the other hand, ‘geoui’ is used with the quantificational expression in a form of noun, adverb, or determiner. In those cases, ‘geoui’ quantifies the case of the sentence and functions as a frequency adverb.