• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.93-107
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• 2016

Game bot playing is one of the main risks in Massively Multi-Online Role Playing Games(MMORPG) because it damages overall game playing environment, especially the balance of the in-game economy. There have been many studies to detect game bot. However, the previous detection models require continuous maintenance efforts to train and learn the game bots' patterns whenever the game contents change. In this work, we have proposed a machine learning technique using the self-similarity property that is an intrinsic attribute in game bots and automated maintenance system. We have tested our method and implemented a system to major three commercial games in South Korea. As a result, our proposed system can detect and classify game bots with high accuracy.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.415-423
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• 2014

The purpose of this study was to investigate the level of multicultural competencies and influencing factors of multicultural competencies in nursing students. The participants of 181 subjects were recruited from three colleges in K and B. A structured questionnaire was used to collect data, and data were analyzed using descriptive statistics, t-test, one way-ANOVA and multiple regression with SPSS/WIN 17.0. Results showed that cultural competence of nursing students was middle range. There was a significant positive correlation between cultural competence, empathy, and self-efficacy. The significant factors influencing cultural competence of nursing students were empathy, self-efficacy, and education of multiple cultural. These three factors explained 51% of the variance in multicultural competencies of nursing students. The study finding suggest that to develop the learning program with achievement level of multicultural competencies for nursing students.

• Human Ecology Research
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• v.53 no.2
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• pp.119-130
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• 2015

In this study, we examined the effects of a mother's reading motivation on the home literacy environment. Seven hundred fifty-seven mothers with three to five year old children participated in this study and completed the Adult Motivation for Reading Scale and the Home Literacy Environment Questionnaire. The subcategories of the Adult Motivation for Reading Scale are "reading as part of self," "reading efficacy," "reading for recognition," and "reading to do well in other realms." The Home Literacy Environment Questionnaire has three subcategories, namely reading books, reading behavior and modeling of parents, and literacy learning. The mean, standard deviation, one-way analysis of variance (ANOVA), and hierarchical multiple regression analysis were used to analyze the data. The results showed that (1) the home literacy environment was significantly different depending on the mother's education and family income levels, (2) the mother's reading motivation also differed significantly depending on the mother's education and family income levels, and (3) the mother's reading motivation has a significant explanatory effect on the home literacy environment. In addition, the mothers falling into the reading motivation subcategories of "reading part of self" or "reading to do well in other realms" were found to enrich their home literacy environment. Therefore, this study demonstrates that the mother's reading motivation is an important factor affecting the home literacy environment.

• The Journal of Korean Physical Therapy
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• v.27 no.2
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• pp.96-105
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• 2015

Purpose: This study was conducted in order to explore self-perceived objectives, effects, determinant factors of satisfaction and demands on home-based rehabilitation service (HBRS) based on a community-based rehabilitation (CBR) model in community-dwelling disabilities. Methods: This research was conducted through in-depth interview. HBRS was conducted by four physical therapists for one hour a day, once a week, for eight weeks. After an eight-week intervention period, in-depth interviews were conducted using a semi-structured questionnaire for five recipients of HBRS and six care givers. Results: For the physical effect, some participants experienced positive effects, whereas others did not due to the short-term intervention period. For the social and emotional effects, 'occurrence of motivation for exercise', 'change of surroundings' and 'sorriness for the therapist' emerged as keywords. For the determinant factors of satisfaction, 'movement-inducing therapy', 'therapy from the specialist', 'development of friendship & social network', and 'learning the way of self-rehabilitation' emerged as keywords. For further demands on HBRS, participants stated that 'sufficient time for therapy', 'user opinion-reflected therapy', 'additional instructions for therapeutic exercise & activities of daily living', and 'active promotion for HBRS' were necessary. Conclusion: Participants were satisfied with the physical, social, emotional, and educational aspects of HBRS. In particular, the participants regarded educational aspects as the significant factor throughout self-perceived objectives, determinant factors of satisfaction and the demands. This result suggests that when providing HBRS to community-dwelling persons with disabilities, therapists should recognize the necessity and significance not only of the physical, but also the educational aspect of HBRS.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.591-601
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• 2020

The self-organizing map (SOM) is a unsupervised learning method projecting high-dimensional data into low-dimensional nodes. It can visualize data in 2 or 3 dimensional space using the nodes and it is available to explore characteristics of data through the nodes. To understand the structure of data, cluster analysis is often used for nodes obtained from SOM. In cluster analysis, the optimal number of clusters is one of important issues. To help to determine it, various cluster validity indexes have been developed and they can be applied to clustering outcomes for nodes from SOM. However, while SOM has an advantage in that it reflects the topological properties of original data in the low-dimensional space, these indexes do not consider it. Thus, we propose a new cluster validity index for SOM based on connectivity between nodes which considers topological properties of data. The performance of the proposed index is evaluated through simulations and it is compared with various existing cluster validity indexes.

• The Journal of Korean Academic Society of Nursing Education
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• v.21 no.1
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• pp.54-64
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• 2015

Purpose: The purpose of this study was to investigate the effects of simulation in nursing education based on caring for elderly cognition disorder patients. The education consisted of a caring program for patients that included a process of assessment of a patient's mental status, diagnosis of the patient's health condition, and intervention to address the problems by using therapeutic communication. Methods: A nonequivalent control group pretest-posttest design was used. A total of 69 subjects (undergraduate students) participated in the education and they were assigned to two groups: the experimental group (n=32) and the control group (n=37). Data-gathering structured questionnaires that included communication competence, academic self-efficacy, and attitudes about the elderly. The data were collected from October 2013 to December 2013, and statistical analyses were conducted with-test and t-test using the SPSS 21.0 program. Results: With respect to education, there was significant improvement in communication competence in the experiment group (t=2.41, p=.022) compared with in the control group (t=.69, p=.494). However, there was no statistically significant difference in academic self-efficacy and attitude about the elderly. Conclusion: Simulation-based education should continue to be developed further for better elderly-patient care. Integrated education in particular using a high-fidelity simulator will contribute to improvements in nursing competence in this area.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.205-211
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• 2012

The retrieved documents have to be transformed into proper data structure for the clustering algorithms of statistics and machine learning. A popular data structure for document clustering is document-term matrix. This matrix has the occurred frequency value of a term in each document. There is a sparsity problem in this matrix because most frequencies of the matrix are 0 values. This problem affects the clustering performance. The sparseness of document-term matrix decreases the performance of clustering result. So, this research uses the factor score by factor analysis to solve the sparsity problem in document clustering. The document-term matrix is transformed to document-factor score matrix using factor scores in this paper. Also, the document-factor score matrix is used as input data for document clustering. To compare the clustering performances between document-term matrix and document-factor score matrix, this research applies two typed matrices to self organizing map (SOM) clustering.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.55-65
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• 2004

When a neural network is used to solve a given problem it is necessary to match the complexity of the network to that of the problem because the complexity of the network significantly affects its learning capability and generalization performance. Thus, it is desirable to have an algorithm that can find appropriate network structures in a self-organizing way. This paper proposes algorithms which automatically organize feed forward multi-layer neural networks with sigmoid hidden neurons for given problems. Using both constructive procedures and pruning procedures, the proposed algorithms try to find the near optimal network, which is compact and shows good generalization performance. The performances of the proposed algorithms are tested on four function regression problems. The results demonstrate that our algorithms successfully generate near-optimal networks in comparison with the previous method and the neural networks of fixed topology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.567-569
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• 2017

This is an example of ABSTRACT format Free-choice activity is child-directed time that young children decide to planning and acting for themselves.It is important time for young children to communicate freely with peers and activities through self-selecting, self-motivated and self-directed activity.Teachers want to maintain connectivity with young children and to work on specific learning goals and supporting friendships and modeling social skills and to make young children feel comfortable to explore in the classroom.However it is hard to gathering information about all children's activities fully by 1 teacher within limited class time and teaching environment.This study was conducted to monitoring system of free-choice activity and time selected by young children that make teachers to analysis the young children's activities effectively using NFC tags.