• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1606-1611
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• 2005

The goal of this paper is to develop a self localization of mobile robot using UHF RFID landmark. We present landmark, a location sensing archetype system that uses UHF Radio Frequency Identification (UHF RFID) technology for locating objects inside buildings. The major advantage of landmark is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that passive UHF RFID is a viable and cost-effective candidate for indoor location sensing. We conduct a series of experiments to evaluate performance of the positioning of the landmark System. In the standard setup, we place RF Reader which has two antennas and 25 tags in our lab. This research uses the assumption-based coordinates (ABC) algorithm[3] for determining the localization of robot. Also, we show how Radio Frequency Identification (UHF RFID) can be used in robot-assisted indoor navigation for the visually impaired. The experiments illustrate that passive UHF RFID tags can act as reliable landmark that trigger local navigation behaviors to achieve global navigation objectives.

• Journal of Pharmacopuncture
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• v.27 no.3
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• pp.199-210
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• 2024

Objectives: Few studies have examined the impact of healthy sleep among general workers on individuals and society. Therefore, the status and risk factors of sleep disturbances among general workers were investigated. In addition, this study assessed the degree to which cold and heat symptoms are associated with sleep disturbances. Methods: A nationwide cross-sectional study was conducted through an online questionnaire focused on sleep disturbances of the general public in 2021. The degree of cold-heat pattern Identification (CHPI) of the general public was also surveyed. Descriptive statistics and multivariate logistic regression were used to derive the study results. Results: Data from 2,822 workers out of 3,900 valid questionnaires were analyzed. Approximately half of the respondents (49.93%) had sleep disturbances. Among the types of work, self-employed, two-shift work, and working more than 53 hours were associated with sleep disturbances. Sleep disturbances were positively associated with six cold and heat symptoms: three cold symptoms (coldness of the abdomen, coldness of body, and pale face) and three heat symptoms (body feverishness, feverishness of the limbs, and drinking cold water). Conclusion: Customized policies to maintain healthy work are needed for self-employed work, two-shift work, and long working hours, which are risk factors for workers' sleep disturbances. In addition, medical personnel can effectively diagnose and treat sleep disturbances considering the worker's cold and heat symptoms.

• Journal of Korean Academy of Nursing Administration
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• v.11 no.3
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• pp.243-254
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• 2005

Purpose: The purpose of this study was to analyze the effects of motivation and hygiene factors on nurse's job satisfaction, organizational commitment, and organizational identification. Methods: The subject hospital was 4 tertiary general hospital located in Seoul and Incheon, Korea. The participants of this study were 521 nurses working in the subject hospitals. The data were collected by self-reporting questionnaires from April 1 to June 30, 2004. The data were analyzed using SAS 8.0 program for descriptive statistics and stepwise multiple regression. Results: The mean score of variables were as follows. The motivation factor's total was 3.22, hygiene factor's total was 2.98, job satisfaction was 2.94. organizational commitment was 2.94, and organizational identification was 3.62. The statistically significant predicting factors of job satisfaction were achievement, work itself and salary. In organizational commitment, the significant predicting factors were achievement, advancement, work itself, policy and administration, working conditions, and interpersonal relations. In organizational identification, the significant predicting factors were work itself, responsibility, interpersonal relations, and personal life. Conclusion: With these results, it was identified that the predicting factors of nurse's job satisfaction based on Herzberg's two-factor theory. The most statistically significant factors were salary on job satisfaction, policy and administration on organizational commitment and work itself on organizational identification. So these results will be used to develop the more effective strategy of nursing staff management. And also these will be contributed to developing the nurse's motivation enhancement plans.

• Child Health Nursing Research
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• v.26 no.2
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• pp.309-322
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• 2020

Purpose: The purpose of this integrative review was to synthesize previous research on perceptions of school health care among school-aged children and adolescents with chronic diseases. Methods: This study was performed in accordance with Whittemore and Knafl's stages of an integrative review (problem identification, literature search, data evaluation, data analysis, and presentation of the results). Four databases (PubMed, CINAHL, Embase, and Web of Science) were used to retrieve relevant articles. Results: Eighteen articles were included in this review. We identified five thematic categories: peer-related issues, a safe school environment, self-perception of an existing disease, self-management, and a supportive school environment. Conclusion: It is necessary to establish a school health care system with a supportive environment for children and adolescents with chronic diseases.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.124-129
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• 2005

The Growing Self-Organizing Map (GSOM), an extended type of the Self-Organizing Map, is a widely accepted tool for clustering high dimensional data. It is also suitable for the clustering of short DNA sequences of phylogenetic genomes by their oligonucleotide frequency. The GSOM presents the result of the clustering process visually on a coloured map, where the clusters can be identified by the user. This paper describes a proposal for automatic cluster detection on this map without any participation by the user. It has been applied with good success on 20 different data sets for the purpose of species separation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1254-1259
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.327-331
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• 1989

This paper concerned about a study on the direct pole placement PID self-tuning controller design for Robot manipulator control system. The method of a direct pole placement self-tuning PID control for a DC motor of robot manipulator tracks a reference velocity in spite of the parameters uncertainties in nonminimum phase system. In this scheme, the parameters of controller are estimated by the recursive least square(RLS) identification algorithm, the pole placement method and diophantine equation. A series of simulation in which minimum phase system and nonminimum phase system are subjected to a pattern of system parameter changes is presented to show some of the features of the proposed control algorithm. The proposed control algorithm which shown are effective for the practical application, and experiments of DC motor speed control for Robot manipulator by a microcomputer IRH-PC/AT are performed and the results are well suited.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.189-199
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• 1999

This paper presents an optimization algorithm for a stable Self Dynamic Neural Network(SDNN) using genetic algorithm. Optimized SDNN is applied to a problem of controlling nonlinear dynamical systems. SDNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real-time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDW has considerably fewer weights than DNN. Since there is no interlink among the hidden layer. The object of proposed algorithm is that the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed optimized SDNN considering stability is demonstrated by case studies.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.41-44
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• 1988

This paper represents the study of an effective self-tuning PID control for a robot manipulator to track a reference trajectory in spite of the presence of nonlinearities and parameters uncertainties in robot dynamic models. In this control scheme, an error model of the manipulator is established, for the first time, by difference between joint reference trajectory and tracked trajectory. It's model Parameters are estimated by the recursive least-square identification algorithm, and classical controller parameters are determined by pole placement method. A computer simulation study was conducted to demonstrate performance of the proposed self-tuning PID control in joint-based coordinates for a robot with payload.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.3
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• pp.434-447
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• 1995

This research was intended to identify variables influencing on risk perception and risk reduction behavior in clothing purchase situations. Responses from 631 female adults living in Seoul area were collected and analyzed. Towner for social occasions or working in office was used as clothing stimulus. The analysis included three product variables(price, style, type of clothing), 4 personality variables(generalized self-confidence, specific self-confidence, generalized informativeness, fashion informativeness), 2 clothing attitude variables(clothing importance, clothing interest), 4 demographic variables(age, educational level, occupation, income), and 3 situational variables(purchase planning, time pressure, effects of shopping company). Multiple regression revealed the fact that each type of clothing risk and each type of risk reduction behavior was influenced by the set of different variables. Generalized self- confidence and age and time pressure had more effects on clothing risk perception, while clothing risk reduction behavior was more influenced by clothing risk type, clothing interest, price of clothing and fashion informativeness. Implications for marketing strategies planning were also provided.