• Journal of Korean Academy of Nursing Administration
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• v.18 no.2
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• pp.146-154
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• 2012

Purpose: The purpose of this study was to examine the effects of preceptor nurses' self-leadership on role recognition and job satisfaction. Method: The participants were 171 preceptor nurses worked in one of three general hospitals in Seoul. The data were collected from April 12 to May 12, 2011 and analyzed using descriptive statistics, t-test, ANOVA, pearson correlation, Scheffe, and regression with SPSS Win 19.0 program. Result: The results of the study were as followed. The average score for preceptor nurses' self-leadership was 3.55, for role recognition, 3.81 and for job satisfaction, 3.28. The factors of the preceptors' self-leadership affecting role recognition were self-expectation (${\beta}$=260, p=.002) and goal setting (${\beta}$=199, p=.030), and those factors accounted for 18.9% of explanatory power. The factors of self-leadership influencing job satisfaction were self-expectation (${\beta}$=18.3, p=.021), and rehearsal (${\beta}$=-168, p=.030), and those factors accounted for 31.3% of explanatory power. Among the factors of self-leadership, self-expectation influenced both role recognition and job satisfaction. Conclusions: The results of the study indicate that to improve preceptor's role recognition and job satisfaction, there should be special training programs to enhance preceptor's self leadership.

• Anxiety and mood
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• v.10 no.1
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• pp.37-43
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• 2014

Objective : Social Phobia is associated with extensive disability and reduced quality of life. The concept of 'social self' is a representation of the self-reflected in the eyes of others, and is recruited during self-face recognition, which is closely related to self-esteem. The aim of this study was to identify the relationship of face recognition for self and others using measures of social anxiety and self-esteem in patients with social phobia. Methods : Twenty-seven patients with social phobia and twenty-three normal controls were evaluated with scales of self-esteem, depression, anxiety and other psychiatric symptoms. All participants completed the self-face recognition task. Nine self-faces, nine other faces and eighty-one morphed faces were presented randomly for each trial. The participants were instructed to make a decision as to whether the stimuli were self-face or not. The responses and reaction times were recorded during the task. Results : There were no group differences of the morphing composition at the recognition start point as self-face. In patients with social phobia, the mean reaction time at the start point of recognizing as a self-face was 1,037.6 ms, which was significantly longer than that of normal controls (911.3 ms, p<0.05). Patients with social phobia showed a significant negative correlation between the mean reaction time and the severity of depression when the stimuli were recognized as a self-face (r=-0.421, p<0.05). Conclusion : A difficulty in attention rather than avoidance may be an important factor of face recognition in patients with social phobia. When considering self-face recognition in such patients, many factors, such as anxiety, depression, working memory and theory of mind, need to be considered.

• Korean Journal of Child Studies
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• v.26 no.5
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• pp.351-365
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• 2005

This study investigates student teacher's recognition of professionalism as they relate to self-concept and conflict. Subjects were 190 student teachers in Seoul and Gyeonggi Province. Subjects responded to self-report questionnaires. Data were analyzed by regression analysis using the SPSS computer program. The Major result of this study are as follows : First, there were significant positive relationships between self-concept and recognition of professionalism in four sub areas. Second, there were also significant negative relationships between conflict and recognition of professionalism in four sub areas. Consequently, self-concept and conflict were statistically significant factors in predicting student teacher's recognition of professionalism.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.453-458
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• 2003

The anomaly-detection algorithm based on negative selection of T cells is representative model among self-recognition methods and it has been applied to computer immune systems in recent years. In immune systems, T cells are produced through both positive and negative selection. Positive selection is the process used to determine a MHC receptor that recognizes self-molecules. Negative selection is the process used to determine an antigen receptor that recognizes antigen, or the nonself cell. In this paper, we propose a novel self-recognition algorithm based on the positive selection of T cells. We indicate the effectiveness of the proposed algorithm by change-detection simulation of some infected data obtained from cell changes and string changes in the self-file. We also compare the self-recognition algorithm based on positive selection with the anomaly-detection algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2824-2838
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• 2013

There has been a lot of attention paid recently to analyze dynamic human gestures that vary over time. Most attention to dynamic gestures concerns with spatio-temporal features, as compared to analyzing each frame of gestures separately. For accurate dynamic gesture recognition, motion feature extraction algorithms need to find representative features that uniquely identify time-varying gestures. This paper proposes a new feature-extraction algorithm using temporal self-similarity based on a hierarchical human model. Because a conventional temporal self-similarity method computes a whole movement among the continuous frames, the conventional temporal self-similarity method cannot recognize different gestures with the same amount of movement. The proposed model-based temporal self-similarity method groups body parts of a hierarchical model into several sets and calculates movements for each set. While recognition results can depend on how the sets are made, the best way to find optimal sets is to separate frequently used body parts from less-used body parts. Then, we apply a multiclass support vector machine whose optimization algorithm is based on structural support vector machines. In this paper, the effectiveness of the proposed feature extraction algorithm is demonstrated in an application for taebo gesture recognition. We show that the model-based temporal self-similarity method can overcome the shortcomings of the conventional temporal self-similarity method and the recognition results of the model-based method are superior to that of the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.201-207
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• 2019

The purpose of this study is to suggest some implications by empirical testing the relationships between children's self-perception and human rights recognition in local children's center. For this study, Total 438 children were sampled and surveyed. The analytical results are the followings. First, personal characteristics was shown to have a significant effect to human right recognition. Second, self-perception was shown to have a significant effect to human right recognition. Third, right guarantee of center was shown to moderate the relationship between self-perception and human right recognition. This study provides some theoretical and polcy implications basing on these analytical results.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.70-81
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• 2017

The aim of this study is to understand the effects of a self-leadership program on career recognition and self-efficacy in adolescents under probation. As a result, it was discovered that the self-leadership program had statistically significant differences in self-understanding, the understanding of work and the job world, setting a career goal and strategies in the sub-area of career recognition in adolescents under probation while there was no significant difference in the area of attitudes and values of work. The self-leadership program had statistically significant differences in confidence, self-regulated efficacy among the sub-area of self-efficacy of the subjects while there were no significant differences in the difficulty of the challenge. These results suggest that the self-leadership program had significant effects on career recognition and self-efficacy in adolescents under probation. In order to improve the career recognition and self-efficacy in adolescents under probation, further studies on the self-leadership program are needed and care should be paid to its usability.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.1
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• pp.119-128
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• 2022

Purpose : The purpose of this study was to examine the effects of applying occupational therapy that uses motion recognition on the physical self-efficacy, visual-motor integration ability, and play skills of children who have neurodevelopmental disorder before and after treatment. Methods : This The study chose 16 children with neurodevelopmental disorder as research subjects who were randomly and evenly allocated into an experimental group and a control group. The experiment followed a pretest-posttest design. As an intervention, the experimental group received motion recognition-based occupational therapy and a separate sensory integration program. The control group only participated in the separate sensory integration program. The eight-week experiment duration included 24 intervention sessions where the a 50-minute session was implemented three times a week for eight weeks. To compare the physical self-efficacy, visual-motor integration ability, and play skills before and after the intervention, measurement tools including the Physical self efficacy, Beery VMI-6, and Penn interactive peer play scale were used. All measured variables were analyzed and expressed as mean, standard deviation and percentage. Results : The motion recognition-based occupational therapy demonstrated a significant effect on improving the physical self-efficacy, visual-motor integration ability, and play skills of the experimental group. The intervention also caused a significant difference between the experimental group and control group in terms of the physical self-efficacy, visual-motor integration ability, and play skills. Conclusion : We confirmed the possibility motion recognition-based occupational therapy could be effective in improving the physical self-efficacy, visual-motor integration ability, and play skills for patients who have neurodevelopmental disorder. Based on the study result, further future studies are expected based on this study result that prove the application effect of the motion recognition-based occupational therapy using disabled and non- disabled children as subjects are expected in the future.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1052-1057
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• 1994

Dynamically localized self-organizing map model (DLSMM) is a new speech recognition model based on the well-known self-organizing map algorithm and dynamic programming technique. The DLSMM can efficiently normalize the temporal and spatial characteristics of speech signal at the same time. Especially, the proposed can use contextual information of speech. As experimental results on ten Korean digits recognition task, the DLSMM with contextual information has shown higher recognition rate than predictive neural network models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1743-1758
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• 2023

Automatic modulation classification is a critical algorithm for non-cooperative communication systems. This paper addresses the challenging problem of closed-set and open-set signal modulation classification in complex channels. We propose a novel approach that incorporates a self-learning filter and center-loss in Deep Residual Shrinking Networks (DRSN) for closed-set modulation classification, and the Opendistance method for open-set modulation classification. Our approach achieves better performance than existing methods in both closed-set and open-set recognition. In closed-set recognition, the self-learning filter and center-loss combination improves recognition performance, with a maximum accuracy of over 92.18%. In open-set recognition, the use of a self-learning filter and center-loss provide an effective feature vector for open-set recognition, and the Opendistance method outperforms SoftMax and OpenMax in F1 scores and mean average accuracy under high openness. Overall, our proposed approach demonstrates promising results for automatic modulation classification, providing better performance in non-cooperative communication systems.