• Proceedings of the Korean Society for Information Management Conference
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• 2001.08a
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• pp.29-34
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• 2001

영상자료 및 소리자료의 색인과 검색을 위해서는 감정동사 및 감정형용사 등의 감정 어휘를 필요로 한다. 그러나 감정어휘는 그 뉘앙스가 미묘하여 분명한 분류체계가 없이는 체계적인 정리가 불가능하다. 이에 따라 본 연구에서는 국어학과 분류사전의 분류체계를 고찰하고 새로운 감정어휘의 분류방안을 연구하였으며, 감정에 따른 기쁨, 슬픔, 놀람, 공포, 혐오, 분노의 6가지 기본유형을 제시하였다.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.617-627
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• 2012

Objective: The aim of the study was to develop a most widely used Korean dictionary of emotion expressing idioms. This is anticipated to assist the development of software technology that recognizes and responds to verbally expressed human emotions. Method: Through rigorous and strategic classification processes, idiomatic expressions included in this dictionary have been rated in terms of nine different emotions (i.e., happiness, sadness, fear, anger, surprise, disgust, interest, boredom, and pain) for meaning and intensity associated with each expression. Result: The Korean dictionary of emotion expression idioms included 427 expressions, with approximately two thirds classified as 'happiness'(n=96), 'sadness'(n=96), and 'anger'(n=90) emotions. Conclusion: The significance of this study primarily rests in the development of a practical language tool that contains Korean idiomatic expressions of emotions, provision of information on meaning and strength, and identification of idioms connoting two or more emotions. Application: Study findings can be utilized in emotion recognition research, particularly in identifying primary and secondary emotions as well as understanding intensity associated with various idioms used in emotion expressions. In clinical settings, information provided from this research may also enhance helping professionals' competence in verbally communicating patients' emotional needs.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.1
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• pp.5-16
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• 2007

Purpose: This study is to verify the validity and reliability of classified items and criteria of the patient classification system(PCS) based on Park's definition of nursing intensity. Methods: An expert group of 8 persons verified the content validity of the tools. The 1817 inpatients at a tertiary hospital in Seoul, Korea were classified into 4 groups according to two tools for verifying concurrent validity and interraters' reliability. These verifications were performed from September to October, 2004. Results: Nursing domains of the tools have been divided into 12 items: hygiene, nutrition, elimination, exercise & activity, education & counseling, emotional support, communication & consciousness, treatment & examination, medication, measurement & observation, coordination of multidisciplinary team, admission & discharge & transfer management. Content validity was verified by the content validity index(above 0.75 in all 12 areas). Interraters' reliability was no significant difference in the results of the patient classification between the two raters(A group 93.75%. B group 88.24%). Concurrent validity was also verified by the agreement of two tools(73.7%). Conclusion: These results showed that the reliability and validity of the PCS based on the nursing intensity were verified. These will use an data for nursing productivity in the future.

• 대한예방의학회:학술대회논문집
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• 1994.02b
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• pp.137-141
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• 1994

The purpose of this paper is to examine what is meant by a ralid measure of health. Guyatt, Kirshner and Jaeschke propose that health tests should be designed so as to have one of several kinds of validity: 'longitudinal construct validity' for those which are used for longitudinal research designs, and 'cross-sectional construct validity' for those which are used for cross-sectional designs. Williams and Naylor argue that this approach to test classification and validation confuses what a test purports to measure with the purpose for which it is used, and that some tests have multiple uses. A review of the meanings of validity in the psychologica test literature shows that both sets of authors use the term validity in an idiosyncratic way. Although the use of a test (evaluated by content validity) should not be conflated with whether the test actually measures a specified construct (evaluated by construct validity);' if health is actually made up of several constructs (as suggested in Hyland's interactional model) then there may be an association between types of construct and types of purpose. Evidence is reviewed that people make several, independent judgements about their health: cognitive perceptions of health problems are likely to be more sensitive to change in a longitudinal research design. whereas emotional evaluations of health provide less bias in cross-sectional designs. Thus. a classification of health measures in terms of the purpose of the test may parallel a classification in terms of what tests purport to measure.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.591-601
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• 2024

As generative AI-based educational content and services targeting child users rapidly increase, the need for research related to children's perception of generative AI is increasing. Accordingly, this study sought to determine the type of generative AI recognized by children and whether cognitive, behavioral, and emotional properties were assigned to it. To understand this, we collected responses through workshop activities to create storybooks with children, semi-structured interviews, and drawing. As a result, children viewed generative AI as an artifact with a high cognitive level, but it was not a type of existing artifact.

• Journal of Korean Clinical Nursing Research
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• v.18 no.2
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• pp.251-263
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• 2012

Purpose: It was necessary for developing a neonatal classification system based on nursing needs and direct care time. This study was, thus, aimed at identifying nursing activities and measuring the standard nursing practice time for developing a neonatal patient classification system in Neonatal Intensive Care Unit (NICU). Methods: The study was taken place in 8 general hospitals located in Seoul and Kyungi province, South Korea from Dec, 2009 to Jan, 2010. By using 'the modified Workload Management System for critical care Nurses' (WMSN), nursing categories, activities, standard time, and task frequencies were measured with direct observation. The data were analyzed by using descriptive statistics. Results: Neonatal nursing activities were categorized into 8 areas: vital signs (manual), monitoring, activity of daily living (ADL), feeding, medication, treatment and procedure, respiratory therapy, and education-emotional support. The most frequent and time-consuming area was an ADL, unlike that of adult patients. Conclusion: The findings of the study provide a foundation for developing a neonatal patient classification system in NICU. Further research is warranted to verify the reliability and validity of the instrument.

• Journal of Korean Clinical Nursing Research
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• v.15 no.1
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• pp.5-17
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• 2009

Purpose: This study was to develop a factor-type patient classification system for general nursing unit based on nursing needs (KPCS; Korean patient classification system for nurses). Method: We reviewed workload management system for nurses(WMSN) of Walter Reed Medical Center, Korean patient classification system for ICU, and nursing activities in nursing records and developed the first version of KPCS. The final version KPCS was evaluated via validity and reliability verifications based on panel discussions and data from 800 patient classifications. Content validity was performed by Delphi method and concurrent validity was verified by the correlation of two tools (r=.71). Construct validity was also tested by medical department (p<.001), patient type (p<.001), and nurse intuition (p<.001). These verifications were performed from April to October, 2008. Results: The KPCS has 75 items in classifying 50 nursing activities, and categorized into 12 different nursing area (measuring vital sign, monitoring, respiratory treatment, hygiene, diet, excretion, movement, examination, medication, treatment, special treatment, and education/emotional support). Conclusion: The findings of the study showed sound reliability and validity of KPCS based on nursing needs. Further study is mandated to refine the system and to develop index score to estimate the necessary number of nurses for adequate care.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1530-1537
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• 2007

In this paper, we implemented a speech emotion recognition system that can distinguish human emotional states from recorded speech captured by a single microphone and classify them into four categories: neutrality, happiness, sadness and anger. In general, a speech recorded with a microphone contains background noises due to the speaker environment and the microphone characteristic, which can result in serious system performance degradation. In order to minimize the effect of these noises and to improve the system performance, a MA(Moving Average) filter with a relatively simple structure and low computational complexity was adopted. Then a SFS(Sequential Forward Selection) feature optimization method was implemented to further improve and stabilize the system performance. For speech emotion classification, a SVM pattern classifier is used. The experimental results indicate the emotional classification performance around 65% in the computer simulation and 62% on the ARM platform.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.12
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• pp.85-94
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• 2018

The purpose of this paper was to propose a model that recognizes potential users' emotional response toward design by classifying Electroencephalography(EEG). Studies in neuroscience and psychology have made an effort to recognize subjects' emotional response by analyzing EEG data. And this approach has been adopted in design since it is critical to monitor users' subjective response in the preface of design. Moreover, the building design process cannot be reversed after construction, recognizing clients' affection toward design alternatives plays important role. An experiment was conducted to record subjects' EEG data while they view their most/least liked images of small-house designs selected by them among the eight given images. After the recording, a subjective questionnaire, PANAS, was distributed to the subjects in order to describe their own affection score in quantitative way. Google TensorFlow was used to build and train the model. Dataset for model training and testing consist of feature columns for recorded EEG data and labels for the questionnaire results. After training and testing, the measured accuracy of the model was 0.975 which was higher than the other machine learning based classification methods. The proposed model may suggest one quantitative way of evaluating design alternatives. In addition, this method may support designer while designing the facilities for people like disabled or children who are not able to express their own feelings toward alternatives.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.883-892
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• 2018

Recently, as interest in social robots to support physical convenience and emotional sympathy has increased, and social internet has developed, a social robot has evolved as various services simply beyond robot function. Therefore, to develop a social robot service effectively, it is required to study the functional application and methods of interaction between user and social robot service. The purpose of this study is to classify social robot services and to suggest the types of elements that need to be considered in service development. To do this, we conducted in-depth case studies and analysis based on the theoretical definitions and characteristics of social robots. Then, based on the sympathy and functions, we classified social robot services into 1) emotional support type, 2) companion type, 3) guide type, and 4) life support type. In addition, in this study, we derive the considerable factors according to the classified types for the development of effective social robot services. This study will contribute to the understanding and development of various services using a social robot.