• 중환자간호학회지
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• 제17권1호
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• pp.1-16
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• 2024

Purpose : This study aimed to explore and describe intensive care unit (ICU) nurses' experience of clinical adaptation. Methods : The participants were 14 ICU nurses with more than two years of working experience in the ICU. Data were collected through in-depth individual interviews conducted between July and October 2021. Theoretical sampling was used to the point of theoretical saturation. Data were analyzed using the Strauss and Corbin method. Results : A total of 79 concepts, 37 subcategories, and 16 categories were identified through open coding. Axial coding based on the paradigm model revealed that the central phenomenon was "The harsh adversity faced in the nursing field where life and death are determined" and the core category was "Enduring the adversity of caring for critically ill patients and achieving self-realization." ICU nurses' clinical adaptation process was explained in five phases: "confrontation period," "turbulent period," "seeking period," "struggling period," and "stabilized period." The five phases that affect interventional conditions were "Support from reliable people," "Recognition of administrative and financial support." Conclusion : This study provided novel insights for a comprehensive understanding of ICU nurses' clinical adaptation processes. Furthermore, the findings are expected to be used as basic data to develop multifaceted strategies to help ICU nurses' adaptation to critical care.

• 한국치위생학회지
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• 제10권4호
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• pp.735-744
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• 2010

Objectives : The purpose of this study was to examine the stressors and stress-adaptation patterns of students preparing for the national dental hygiene certification examination. Methods : The subjects in this study were dental hygiene juniors in four selected colleges located in the metropolitan area. After a survey was conducted, the collected data were analyzed. Results : 1. Concerning motivation of choosing the department of dental hygiene, the largest group that accounted for 72.2 percent chose it due to employment prospects. As to satisfaction level with the department, 40.4 percent were satisfied. In relation to employment prospects, 54.1 percent thought the prospects were bright. 2. They got a mean of 3.23 in stressors. To be specific, they felt the most stress due to test anxiety(3.70), followed by leisure insufficiency (3.21), the uncertainty of the future(3.18) and parental pressure(2.64). 3. They got a mean of 2.02 in stress-adaptation method. They got 2.31 and 1.72 in long-term and short-term adaptation respectively, which showed that long-term stress adaptation method were more prevailing than short-term ones. 4. As for the relationship of the stressors, there was positive correlation among all the test anxiety, future uncertainty, leisure insufficiency and parental pressure, and their correlation was statistically significant(p<0.000). 5. Regarding connections between general characteristics and the stressors, whether they spent two years or more for college admission, satisfaction level with the dental hygiene department, employment prospects and health status made significant differences to the stressors (p<0.05), and there were significant gaps in adaptation patterns according to academic standing, satisfaction level with the department and health state(p<0.05). Conclusions : The dental hygiene students were under great pressure since they had to prepare for the national dental hygiene certification examination to become a certified dental hygienist, one of professional health care workers. Therefore stress counseling programs and stress-coping programs should be developed to relieve the stress of dental hygiene students who are going to take the national dental hygiene certification examination. And they should be assisted to stay away from stress and to handle their stress in a more active manner.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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• pp.81-86
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• 2002

In current CBR(Case-Based Reasoning) systems, the case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck similar to those found in traditional expert system design. In this thesis, 1 present a model for learning method of case adaptation knowledge using case base. The feature difference of each pair of cases are noted and become the antecedent part of an adaptation rule, the differences between the solutions in the compared cases become the consequent part of the rule. However, the number of rules that can possibly be discovered using a learning algorithm is enormous. The first method for finding cases to compare uses a syntactic measure of the distance between cases. The threshold fur identification of candidates for comparison is fixed th the maximum number of differences between the target and retrived case from all retrievals. The second method is to use similarity metric since the threshold method may not be an accurate measure. I suggest the elimination method of duplicate rules. In the elimination process, a confidence value is assigned to each rule based on its frequency. The learned adaptation rules is applied in riven target Problem. The basic. process involves search for all rules that handle at least one difference followed by a combination process in which complete solutions are built.

• 디지털융복합연구
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• 제16권2호
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• pp.313-325
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• 2018

본 연구는 집단미술치료 프로그램이 여고생의 자아존중감 및 학교생활적응에 미치는 영향력을 파악하는데 연구의 목적을 두었다. 이를 위하여 충남 S시에 소재하는 S여자고등학교에서 집단미술치료 프로그램을 실시하였고 양적 및 질적 통합적 방법을 통하여 분석하였다. 주요 연구결과를 살펴보면 다음과 같다. 첫째, 집단미술치료 프로그램은 여고생들의 자아 존중감 향상에 긍정적인 영향을 미치고 있는 것으로 나타났다. 둘째, 집단미술치료 프로그램은 여고생들의 학교생활적응을 높이는 데에도 긍정적인 영향을 미치는 것으로 나타났다. 하지만 통합적 분석 결과 자아존중감이 양적 분석 시에만 유의한 변화가 있는 경우가 있었다. 반면, 학교생활적응은 질적 분석 시에만 유의한 변화가 있는 경우도 있었다. 끝으로 본 연구 결과를 바탕으로 여고생들의 자아존중감 및 학교생활적응을 향상시키기 위한 정책적 방안을 논의하였다.

• 한국콘텐츠학회논문지
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• 제11권12호
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• pp.307-316
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• 2011

본 연구에서는 결혼이민여성의 지역사회 적응의 특성을 밝히고, 이를 토대로 결혼이민여성의 지역사회 적응 향상을 위한 실천적 함의를 도출하고자 하였다. 이를 위하여 2010. 4월부터 5개월간 8명의 참여자를 대상으로 면접을 실시하였다. 연구방법은 현상학적 연구 중 Colaizzi방법론을 채택하였는데, 심층면접을 통하여 녹취한 진술을 텍스트화 한 후, 유의미한 진술내용을 코딩하여, 주제(themes), 주제묶음(theme cluster)으로 범주화하였다. 분석결과, '내적역량의 강화', '문화적응', '제한적 수혜자 되기', '인적네트워크 없음', '미래를 낙관할 수 없음' '지역사회 안착을 염원함', '한국을 떠날 수 있음'으로 총 7개의 주제묶음과 17개의 주제, 47개의 의미를 도출하였다. 이러한 결과를 토대로 지역사회에서 결혼이민여성의 적응력 향상을 위한 사회복지실천의 함의를 제시하였다.

• 대한임베디드공학회논문지
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• 제19권2호
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• pp.73-81
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• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• 대한전기학회논문지
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• 제37권12호
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• pp.884-893
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• 1988

Adaptive controllers for linear unknown coefficient system, that is corrupted by disturbance, are designed by parameter adaptation model reference adaptive control(MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the convergence rate of the design, an indirect-suboptimal control law is derived. Proper compensation for the effects of time-varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

• ETRI Journal
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• 제36권3호
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• pp.429-438
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• 2014

Semantic role labeling (SRL) is a task in natural-language processing with the aim of detecting predicates in the text, choosing their correct senses, identifying their associated arguments, and predicting the semantic roles of the arguments. Developing a high-performance SRL system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Constructing SRL training data for a new domain is very expensive. Therefore, domain adaptation in SRL can be regarded as an important problem. In this paper, we show that domain adaptation for SRL systems can achieve state-of-the-art performance when based on structural learning and exploiting a prior model approach. We provide experimental results with three different target domains showing that our method is effective even if training data of small size is available for the target domains. According to experimentations, our proposed method outperforms those of other research works by about 2% to 5% in F-score.

• 한국음향학회지
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• 제38권1호
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• pp.47-50
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• 2019

본 논문에서는 잡음 환경에서 효과적인 음성 인식을 위하여 DNN(Deep Neural Network) 기반의 잡음 오염 함수 예측을 이용한 음향 모델 적응 기법을 제안한다. 깨끗한 음성과 잡음 정보를 입력으로 하고 오염된 음성에 대한 특징 벡터를 출력으로 하는 DNN을 학습하여 비선형 관계를 갖는 잡음 오염 함수를 예측한다. 예측된 잡음 오염 함수를 음향모델의 평균 벡터에 적용하여 잡음 환경에 적응된 음향 모델을 생성한다. Aurora 2.0 데이터를 이용한 음성 인식 성능 평가에서 본 논문에서 제안한 모델 적응 기법이 기존의 전처리, 모델 적응 기법에 비해 일치, 불일치 잡음 환경에서 모두 평균적으로 우수한 성능을 나타낸다. 특히 불일치 잡음 환경에서 평균 오류율이 15.87 %의 상대 향상률을 나타낸다.

• 한국정보통신학회논문지
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• 제19권5호
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• pp.1047-1054
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• 2015

본 논문에서는 음성 인식 성능 향상을 위해 미전사된 음성 데이터베이스를 이용한 효과적인 음향 모델 변환 기법을 기술한다. 본 논문에서 기술하는 모델 변환 기법에서는 기존의 적응 기법을 이용하여 환경에 적응된 GMM을 얻는다. HMM의 가우시안 요소와 유사한 요소를 선택하여 선택된 가우시안 요소의 변환 벡터를 구하고 이를 평균 파라미터 변환에 이용한다. GMM 적응 기반의 모델 변환 기법을 기존의 MAP, MLLR 적응 기법과 결합하여 적용한 결과, 자동차 잡음과 음성 Babble 잡음 환경에서 기존의 MAP, MLLR을 단독으로 사용할 경우보다 높은 음성 인식성능을 나타낸다. 온라인 음향 모델 적응 실험에서도 MLLR과 결합할 경우 기존의 MLLR을 단독으로 사용할 때보다 효과적인 모델 적응 성능을 나타낸다. 이와 같은 결과는 본 논문에서 소개한 GMM 적응 기반의 모델 변환 기법을 채용함으로써 미전사된 음성 데이터베이스를 음향 모델 적응 기법에 효과적으로 활용할 수 있음을 입증한다.