• Journal of Home Health Care Nursing
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• v.26 no.2
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• pp.219-229
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• 2019

Purpose: This study aimed to investigate the difference between primary caregivers' self-efficacy and coping strategy according to the communication styles of home care nurses. Methods: Data were collected from 123 primary caregivers of patients who were registered at a home care nursing center in D city and who had been receiving home care for more than 3 months from January 1 to February 27, 2018. The questionnaire included items on communication style, self-efficacy, and stress coping strategy. The data were analyzed using descriptive statistics, t-test, and ANOVA. Results: Regarding primary caregivers' self-efficacy in terms of communication style, the caregivers showed higher efficacy in providing informative and friendly communication (F=14.07, p=.001). Regarding home care nurses' communication style and the stress coping strategy of the primary caregivers, the informative-friendly communication style was adopted the most for the problem-solving coping strategy (F=7.17, p=.001). Regarding the social support-seeking coping, home care nurses' friendly communication style was the most adopted (F=4.40, p=.014). Conclusion: This study suggests that home care nurses will plan to provide informative and friendly communication-oriented nursing care, and to improve self-efficacy and positively influence the coping method by using the communication styles appropriate to the state of the primary caregiver.

• Smart Structures and Systems
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• v.29 no.1
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• pp.195-206
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• 2022

Crack detection is essential for inspection of existing structures and crack segmentation based on deep learning is a significant solution. However, datasets are usually one of the key issues. When building a new dataset for deep learning, laborious and time-consuming annotation of a large number of crack images is an obstacle. The aim of this study is to develop an approach that can automatically select a small portion of the most informative crack images from a large pool in order to annotate them, not to label all crack images. An active learning method with difficulty learning mechanism for crack segmentation tasks is proposed. Experiments are carried out on a crack image dataset of a steel box girder, which contains 500 images of 320×320 size for training, 100 for validation, and 190 for testing. In active learning experiments, the 500 images for training are acted as unlabeled image. The acquisition function in our method is compared with traditional acquisition functions, i.e., Query-By-Committee (QBC), Entropy, and Core-set. Further, comparisons are made on four common segmentation networks: U-Net, DeepLabV3, Feature Pyramid Network (FPN), and PSPNet. The results show that when training occurs with 200 (40%) of the most informative crack images that are selected by our method, the four segmentation networks can achieve 92%-95% of the obtained performance when training takes place with 500 (100%) crack images. The acquisition function in our method shows more accurate measurements of informativeness for unlabeled crack images compared to the four traditional acquisition functions at most active learning stages. Our method can select the most informative images for annotation from many unlabeled crack images automatically and accurately. Additionally, the dataset built after selecting 40% of all crack images can support crack segmentation networks that perform more than 92% when all the images are used.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.365-368
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• 2005

We propose a speech act analysis method for Korean dialogue using Support Vector Machines (SVM). We use a lexical form of a word, its part of speech (POS) tags, and bigrams of POS tags as sentence features and the contexts of the previous utterance as context features. We select informative features by Chi square statistics. After training SVM with the selected features, SVM classifiers determine the speech act of each utterance. In experiment, we acquired overall $90.54\%$ of accuracy with dialogue corpus for hotel reservation domain.

• ETRI Journal
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• v.32 no.5
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• pp.766-773
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• 2010

Support vector machine (SVM) active learning plays a key role in the interactive content-based image retrieval (CBIR) community. However, the regular SVM active learning is challenged by what we call "the small example problem" and "the asymmetric distribution problem." This paper attempts to integrate the merits of semi-supervised learning, ensemble learning, and active learning into the interactive CBIR. Concretely, unlabeled images are exploited to facilitate boosting by helping augment the diversity among base SVM classifiers, and then the learned ensemble model is used to identify the most informative images for active learning. In particular, a bias-weighting mechanism is developed to guide the ensemble model to pay more attention on positive images than negative images. Experiments on 5000 Corel images show that the proposed method yields better retrieval performance by an amount of 0.16 in mean average precision compared to regular SVM active learning, which is more effective than some existing improved variants of SVM active learning.

• Journal of the Ergonomics Society of Korea
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• v.13 no.2
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• pp.33-41
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• 1994

The paper presents a new scheme and a support system for the analysis sof hyman errors in nuclear power plants based on a cognitive model. We discusse the problems identified in current managerial analysis, and propose a new approach that frames the description of human activities according to a human decision making modle, so that it could provide a better reconstruction of a sequence of event suspected of involving human errors. This sophistcated approach becomes practical for the field application with the support of a computerized aiding system. The model-based event re-construction method is expected to enable the analysts to produce more informative reports, which in turn heop to derive appropriate counter- measures to reduce the possibility of the analyzed human errors.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.830-835
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• 2005

4D models help construction planners to develop and evaluate construction plans. However, current analyses using 4D models are mainly visual and limit the quantitative comparison of construction alternatives. This paper explores the usefulness of extracting quantitative information from 4D models to support time-space analyses. We use two 4D models of an industry test case to illustrate how to analyze 4D content quantitatively (i.e., work space areas and distances between concurrent activities). This paper shows how these two types of 4D content can be extracted from 4D models to support 4D-based-analysis and novel presentation of construction planning information. We suggest further research to formalize the content of 4D models to enable comparative quantitative analyses of construction planning alternatives. Formalized 4D content will enable the development of reasoning mechanisms that automate 4D-model-based analyses and provide the information content for informative presentations of construction planning information.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.420-431
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• 2016

The purpose of this study was to examine the effect of social support from teachers and friends on the career maturity of students at technical meister high schools. The Social Support Scale adjusted by Kim, Hye-Jin(2006) and the Career Maturity Attitude Inventory Scale produced by Lee, Ki-Hak(1997) were administered. The data from 194 were ultimately included to analyze. Corrlational coefficent and multiple regression analysis were performed using SPSS 21.0 statistical package. The results were as follows. First, perceived teachers' social support was higher than friends. Second, the effect of teachers' social support on career maturity was not significant but the effect of social support from friends was found. Among sub-factors of social support from friends, emotional and informative support were found significant effect on career maturity. The implication of these results were discussed in terms of career counseling and education of technical meister high schools.

• Nuclear Engineering and Technology
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• v.40 no.1
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• pp.69-76
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• 2008

Most pressurized water reactors use Venturi flow meters to measure the feedwater flow rate. However, fouling phenomena, which allow corrosion products to accumulate and increase the differential pressure across the Venturi flow meter, can result in an overestimation of the flow rate. In this study, a soft-sensing model based on fuzzy support vector regression was developed to enable accurate on-line prediction of the feedwater flow rate. The available data was divided into two groups by fuzzy c means clustering in order to reduce the training time. The data for training the soft-sensing model was selected from each data group with the aid of a subtractive clustering scheme because informative data increases the learning effect. The proposed soft-sensing model was confirmed with the real plant data of Yonggwang Nuclear Power Plant Unit 3. The root mean square error and relative maximum error of the model were quite small. Hence, this model can be used to validate and monitor existing hardware feedwater flow meters.

• Child Health Nursing Research
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• v.25 no.2
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• pp.184-195
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• 2019

Purpose: This study aimed to characterize the relationship between parental stress and nurses' communication as perceived by parents of high-risk newborns in a neonatal intensive care unit (NICU). Methods: The participants were 54 parents of high-risk newborns in a NICU. Data were collected from January to March 2018. Parental stress and parents' perceptions of nurses' communication ability and styles were measured using a questionnaire. Results: The average scores for parental stress and nurses' communication ability were 3.39 and 4.38 respectively, on a 5-point scale. Parents most commonly reported that nurses showed a friendly communication style, followed by informative and authoritative styles. Mothers and fathers reported significantly different levels of parental stress. Parental stress showed a negative correlation with nurses' perceived verbal communication ability. Higher scores for nurses' verbal communication ability and for friendly and informative communication styles were associated with lower parental stress induced by the environment, the baby's appearance and behaviors, and treatments in the NICU. Conclusion: The findings of this study suggest that nurses need to offer proper information for parents and to support parents by encouraging them to express their emotions of stress and by providing parents with therapeutic communication and opportunities to participate in care.

• Korean Medical Education Review
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• v.17 no.1
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• pp.26-32
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• 2015

Recently, the student internship has been introduced in medical schools as a way of preparing students with training experience and medical knowledge by performing clinical practice. This study discusses student internship management and ways to operate the internship effectively. Catholic University of Daegu School of Medicine has set up a 6-week internship program for fourth-year undergraduate students. In most of the sections, students have shown their satisfaction, particularly when they have received appropriate feedback and attention from their professors. The students found that performing the evaluation and treatment of patients and individual chart recording were informative and helpful. However, they felt a lack of basic knowledge and clinical skills and had difficulty in understanding their roles and in time management. The success of an internship depends on the passion and interest that professors show for their students along with active support from the other faculty and thoughtful consideration of patients and all their friends and family members. In addition, with growing awareness of the need for the student internship, it is necessary that the school executive provide financial and administrative support to the faculty and staff, clarify roles and the work needed to perform the tasks, ensure substantiality of the individual program with professors or departments, provide enough preliminary courses, and monitor outcomes and reflection.