• 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.

• 한국간호교육학회지
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• 제27권3호
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• pp.240-250
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• 2021

Purpose: The aim of this study is to analyze the research trends of articles on just graduated Korean nurses during the past 10 years for exploring strategies for clinical adaptation. Methods: The topics of new graduate nurses were extracted from 110 articles that have been published in Korean journals between January 2010 and July 2020. Abstracts were retrieved from 4 databases (DBpia, RISS, KISS and Google scholar). Keywords were extracted from the abstracts and cleaned using semantic morphemes. Network analysis and topic modeling were performed using the NetMiner program. Results: The core keywords included 'education', 'training', 'program', 'skill', 'care', 'performance', and 'satisfaction'. In recent articles on new graduate nurses, three major topics were extracted by Latent Dirichlet Allocation (LDA) techniques: 'turnover', 'adaptation', 'education'. Conclusion: Previous articles focused on exploring the factors related to the adaptation and turnover intentions of new graduate nurses. It is necessary to conduct further research focused on various interventions at the individual, task, and organizational levels to improve the retention of new graduate nurses.

• 간호행정학회지
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• 제22권5호
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• pp.496-506
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• 2016

Purpose: This study was conducted to examine the adaptation experience of male nurses working in general wards. Methods: Experiential data was collected from 16 general ward nurses through in-depth interviews. Participants were selected from male nurses working in the general wards with over one year of clinical experience at a tertiary university hospital. The main question was "Can you describe your adaptation experience in the general ward as a nurse?" All interviews were recorded and transcribed, then analyzed using Colaizzi's method. Results: Four categories were derived from the analysis: 'difficulties from task adaptation by characteristics', 'limited nursing situation and circumstance as a male nurse', 'efforts to adapt at general nursing unit', and 'self-worth, and worry about something as a male nurse'. Conclusion: Male nurses had a difficulty adapting to work in wards due to lack of multi-tasking skills, as well as some social prejudice or negative views on male nurses. Establishing reasonable guidelines for male nurses in practice, promoting their responsibilities to patients, developing mentoring programs, and reassessing the policy of assigning male nurses to general wards are recommended to help in better adaptation.

• 인지과학
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• 제22권1호
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• pp.39-55
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• 2011

사람들은 이사, 투표, 시험, 부상, 차 구입과 같은 미래의 사건에 대한 자신의 정서 반응을 과도하게 예측한다. 충격 편향(impact bias)란 자신의 정서 반응이 강하게 오래 계속될 것으로 예상하는 것이다. 본 연구는 원자력 발전소, 유전자조작식품, 그리고 휴대폰과 같은 위험 대상에 대해 충격 편향이 관찰되는지, 그리고 관찰된다면 이 편향을 감소시키는 조작의 효과가 있는지를 검토하였다. 참여자들은 위험 대상에 대해서 현재보다 가까운 미래인 1주일 후 충격 편향을 가장 크게 보였다. 적응 과제와 탈초점 과제를 사용한 결과, 탈초점 조작이 위험 대상들에 대한 충격 편향을 감소시켰다. 본 연구의 결과들을 선행 연구들과 관련해서 논하였다.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• 제22권1호
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• pp.63-71
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• 2019

Purpose: The aim of this study was to identify the minimally meaningful dosage of inulin leading to a prebiotic effect in Indonesian infants. Methods: In a randomized controlled double-blinded, parallel, 3-arm intervention study, 164 healthy formula-fed infants aged 3 to 5 months first obtained formula-A (without inulin) during a 4-week adaptation period. Subsequently, 142 subjects were subjected to a 4-week feeding period by administering either formula-A (no inulin), formula-B (0.2 g/100 mL inulin) or formula-C (0.4 g/100 mL inulin). The primary outcome parameter was %-bifidobacteria in faecal samples determined using quantitative polymerase chain reaction analyses. Secondary outcome parameters were faecal %-lactobacilli, pH and stool frequency, and consistency. Growth and tolerance/adverse effects were recorded as safety parameters. Results: Typical %-bifidobacteria and %-lactobacilli at the end of the adaptation period in the study population were 14% and 2%, respectively. For faecal pH, significant differences between formula groups A vs. C and A vs. B were found at the end of the intervention period. Testing for differences in faecal %-bifidobacteria and %-lactobacilli between groups was hampered by non-normal data set distributions; no statistically significant differences were obtained. Comparisons within groups revealed that only in formula group C, all the three relevant parameters exhibited a significant effect with an increase in faecal %-bifidobacteria and %-lactobacilli and a decrease in pH. Conclusion: A consistent prebiotic effect along with a decrease in pH and increase in %-bifidobacteria and %-lactobacilli was found only in the group administered 0.4 g inulin/100 mL.

• 한국치위생학회지
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• 제11권5호
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• pp.811-822
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• 2011

Objectives : The purpose of this study was to examine the relationship of the self-efficacy of dental hygiene students to their stressors and ways of stress-adaptation patterns. Methods : The subjects in this study were dental hygiene juniors in four selected colleges located in the metropolitan area. Results : 1. They got a mean of 3.22 in self-efficacy. They gave the highest mark(3.50) to an item 'I can attain it if I set a primary goal.' 2. They got a mean of 3.18 in stressors. Among the stressors, task assignments(3.74) were identified as the greatest stressor, followed by the curriculum(3.25), learning environments(3.16), prospects of employment (3.07) and test anxiety(2.95). 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 a result of analyzing whether there would be any gaps in self-efficacy according to general characteristics, statistically significant gaps were found in that regard according to experience of preparing for college admission after leaving high school, academic standing, satisfaction with the department of dental hygiene and prospects of employment(p<.05). 5. As a result of checking the relationship of their self-efficacy to their stressors and ways of stress adaptation method, there were statistically significant differences in that aspect according to examinations and prospect of employment(p<0.05). As for ways of stress adaptation method, there were statistically significant differences in long-term adaptation method (p<0.05). Conclusions : As it's found that the level of the self-efficacy of the dental hygiene students was linked to the efficiency of their ways of stress adaptation method, the development and implementation of programs geared toward boosting the self-efficacy of dental hygiene students are required to teach them to successfully cope with various kinds of stress that they are likely to face after getting a job.

• 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.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.709-712
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• 1996

Generating a project network of a specific construction project is very time consuming and difficult task in the field. To effectiviely automate and support the planning process, we design a case-based project planning expert system inspired by the fact a human expert project planner uses previous cases for planning a new project. A construction project case consist of its specific characteristics and the corresponding project network (i.e. project plan). Using frame based representation. we represent the project features affecting the progress network and the entities composing the project plan such as the buildings, construction methods, WBS (work breakdown structure), activities, and resources. The project planning process runs through most similar case retrieval, case adaptation, and user requirement satisfaction. We represent the construction domain knowledge for each procedure using constraints and rules. We develop the methodology for constraint-based case adaption. Case adaptation process mainly consist of activity generation/deletion and predecence constraint satisfaction, for which we develop the dynamic constraint generation method and connect user-level requirement representation the system-level network modification knowledge. The methodology is being applied to the prototype for apartment construction project planning.

• 한국전문물리치료학회지
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• 제10권1호
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• pp.97-108
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• 2003

Slipping during various kinds of movement often leads to potentially dangerous incidents of falling. The purpose of this paper was to review some of the research performed in the field including such topics as rating scales for balance, kinematics and kinetics of slipping, adaptation to slippery conditions, postural and balance control, and protective movement during falling. Controlling slipping and fall injuries requires a multifaceted approach. Environmental conditions (state of floor surface, tidiness, lighting, etc), work task (walking, carrying, pushing, lifting, etc), and human behavior (anticipation of hazards, adaptation to risks, risk taking, etc) must be accounted for in the assessment of slip and fall-related risks. Future directions of research must deal with modeling of basic tribophysical, biomechanical, and postural control process involved in slipping and falling.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.678-680
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• 2023

본 논문은 정확하면서도 효율적인 한국어 문장 분류 기법에 대해서 논의한다. 최근 자연어처리 분야에서 사전 학습된 언어 모델(Pre-trained Language Models, PLM)은 미세조정(fine-tuning)을 통해 문장 분류 하위 작업(downstream task)에서 성공적인 결과를 보여주고 있다. 하지만, 이러한 미세조정은 하위 작업이 바뀔 때마다 사전 학습된 언어 모델의 전체 매개변수(model parameters)를 학습해야 한다는 단점을 갖고 있다. 본 논문에서는 이러한 문제를 해결할 수 있도록 도메인 적응기(domain adapter)를 활용한 한국어 문장 분류 프레임워크인 DAKS(Domain Adaptation-based Korean Sentence classification framework)를 제안한다. 해당 프레임워크는 학습되는 매개변수의 규모를 크게 줄임으로써 효율적인 성능을 보였다. 또한 문장 분류를 위한 특징(feature)으로써 한국어 사전학습 모델(KLUE-RoBERTa)의 다양한 은닉 계층 별 은닉 상태(hidden states)를 활용하였을 때 결과를 비교 분석하고 가장 적합한 은닉 계층을 제시한다.