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강정아,노영희,Kang, Jung A,Noh, YoungHee 한국도서관정보학회 2018 한국도서관정보학회지 Vol.49 No.1
본 연구는 국내 어린이도서관 문화프로그램의 사회적 효과를 측정하여 어린이도서관의 사회적 가치를 제시하였다. 이를 위해 초등학생 511명을 대상으로 설문조사를 실시하여 어린이도서관 문화프로그램의 사회적 효과를 측정하였다. 분석 결과 개인적 영역의 표현력/창의력, 자존감, 즐거움/기쁨/행복과 사회적 영역의 문화예술태도와 문화예술경험변화 및 사회적 상호작용으로 친구관계 증대, 지역커뮤니티 생성과 강화, 지역사회 소속감/공동체성, 지역사회참여 등의 효과가 있는 것으로 나타났다. 이를 근거로 어린이도서관은 어린이의 삶의 질을 향상하고, 사회적 상호작용 역량의 향상, 지역사회 공동체 유지 및 지역커뮤니티 생성과 강화, 지역애착과 지역 활동 참가에 영향을 미치는 중요한 사회자본으로 가치를 가진다고 볼 수 있다. The aim of this study was to assess the social impact of the cultural programs of the children's libraries in Korea and further present the libraries'social value. To this end, we have conducted a survey on 511 elementary school students to assess the social impact of the children libraries'cultural programs. As a consequence, we have ascertained the children's expressiveness / creativity within their personal realms, self-esteem, pleasure / joy / happiness as well as their attitude towards cultural arts and changes in the cultural and artistic experiences further to growth in friendship as a matter of social interaction, generation and strengthening of local communities, sense of affiliation with local community / identify, and local community participation, among the manifestations of the social impact concerned. Based on this, children's libraries can be regarded as an important social capital of the community in the following aspects. Children's libraries enhance the quality of life and children's interaction skills. It also make them feel attached to the local community. Children's libraries maintain local communities, contribute to the creation and strengthening of local communities, and encourage participation in local activities.
다양한 배양 환경에 따른 국내 수집 외생균근성 Tricholoma 속 종의 균사생장 특성
강정아 ( Jung-a Kang ),가강현 ( Kang-hyeon Ka ),김준영 ( Jun Young Kim ),김성환 ( Seong Hwan Kim ) 한국균학회 2018 韓國菌學會誌 Vol.46 No.3
The ectomycorrhizal basidiomycete Tricholoma is one of mushroom groups that cannot be cultivated artificially. To use this mushroom as applicable resource for food production, it is necessary to obtain information about their mycelial growth properties in various environmental conditions. This study investigated the mycelial growth of four domestic isolates of Tricholoma species (T. bakamatsutake, T. fulvocastaneum, T. matsutake, T. terreum) at different physical and chemical conditions. The optimal physical conditions for their mycelia growth were found to be a temperature range of 20~25℃ and a pH range of 4.0~7.0 in dark condition. The growth of T. matsutake was retarded at high temperature (30℃). Tests to determine the chemical factors that affected mycelial growth showed that the four Tricholoma spp. grew 1% saline. T. matsutake grew in up to 2% saline. In the presence of various heavy metals (50 ppm) and pesticides (suppliers’ recommended concentration), mycelial growth was inhibited the most by cadmium and emamectin benzoate, respectively. However, all the four Tricholoma spp. grew with Cu+. The growth of T. matsutake was not inhibited by abamectin, acetamiprid, and thiacloprid. Extracellular enzyme activities of amylase and β-glucosidase were detected only in T. bakamatsutake and T. fulvocastaneum. The results of the present study allowed us to determine suitable or harmful environmental conditions for the mycelial cultivation of the Tricholoma spp.
Art Nouveau 양식의 조형적 특징을 활용한 헤어디자인 연구
강정아(Jung-Ah Kang),오현주(Hyun-Ju Oh) 한국인체미용예술학회 2011 한국인체미용예술학회지 Vol.12 No.3
The style of Art Nouveau, giving us the sense of liveliness and natural beauty of curve flowing smoothly, in the contemporary industrialized society with the distinctive feature of its force of uniform and dehumanization, is now applied to and used in many areas as considered to convey the meaning of recovery of humanity. This paper is on the study and art creation of the Art Nouveau form among the art styles that appear in hair design. Based on existing studies and related literary materials, the definition and formative features of Art Nouveau, and the factors and principles of hair design was theoretically studied, and hair designs that reflected the formative features of Art Nouveau styles were analyzed for empirical research. In addition, based on the theoretical background, three hair designs were created by applying the formative features of Art Nouveau style. Symbolism was created using up-style work, composition was created using hair-by-night work, and mystique was created using deign cuts. Each work was based on the design intent, production procedure, illustration, color and the formative features of Art Nouveau. In the course of this study, there was difficulties caused by the lack of preceding studies related to art styles that integrated hair design, and thus it is judged that more wide-range research that integrates hair design in Art Nouveau form is needed. In addition, limitations of this study was the insufficiency to express the features of Art Nouveau in just three pieces.
강정아(Jeong A Kang),문선혜(Sun Hye Mun),곽영훈(Young Hoon Kwak),허정호(Jung Ho Huh) 대한설비공학회 2021 대한설비공학회 학술발표대회논문집 Vol.2021 No.6
The importance of a pleasant environment is increasing due to the increase in occupancy time of residential buildings, and the energy performance of buildings required by the government is also increasing. Residents behavior is a factor that has a considerable influence on building energy, and although there is high uncertainty, it can act as an advantage in reducing building energy. This uncertainty of resident behavior can be caused by the fact that residential buildings do not have standardized behavior patterns unlike business buildings. The purpose of this study is to classify the behavioral patterns of non-standardized residential buildings into similar patterns by using the clustering technique during machine learning, and also to analyze the characteristic conditions according to the classified patterns. It is believed that the methodology and results used can be effectively used for predicting behavioral patterns and energy according to conditions that will occur in buildings in the future. Behavior data clustering was performed based on the occupancy behavior data of residential buildings measured for 20 days in the intermediate period. Among the machine learning algorithms, K-means Time Series Clustering was used, and the characteristics of each cluster were analyzed according to the classification properties.