• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.253-262
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• 2008

This paper presents a framework for decentralized control of self-organizing swarm systems based on the artificial potential functions (APFs). The framework explores the benefits by associating agents based on position information to realize complex swarming behaviors. A key development is the introduction of a set of association rules by APFs that effectively deal with a host of swarming issues such as flexible and agile formation. In this scheme, multiple agents in a swarm self-organize to flock and achieve formation control through attractive and repulsive forces among themselves using APFs. In particular, this paper presents an association rule for swarming that requires less movement for each agent and compact formation among agents. Extensive simulations are presented to illustrate the viability of the proposed framework.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.382-389
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• 2009

Recently, knowledge management has been required in companies as a tool of competitiveness. Companies have constructed Enterprise Resource Planning(ERP) system in order to manage huge knowledge. But, it is not easy to formalize knowledge in organization. We focused on data mining system by genetic programming(GP). Data mining system by genetic programming can be useful tools to derive and extract the necessary information and knowledge from the huge accumulated data. However when we don't have enough amounts of data to perform the learning process of genetic programming, we have to reduce input parameter(s) or increase number of learning or training data. In this study, an enhanced data mining method combining Genetic Programming with Self organizing map, that reduces the number of input parameters, is suggested. Experiment results through a prototype implementation are also discussed.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.1-23
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• 2012

Advances in information technology has brought many benefits to businesses, but at the same time, businesses are facing serious problems caused by its use such as information leakage. In order to cope with problems, companies have established information security policies, demanding workers of a company to be compliant with the policies. This study proposes a research model that includes information security awareness, information security attitude, self-efficacy, standard belief and social influences as factors that affect the compliance of information security policy among the workers of shipping and port organization. The results of this study showed that there was a positive relationship not only between the information security awareness and the information security attitude, but also between the information security attitude and the information security policy among the workers of shipping and port organization. It was also found that there was a positive relationship between the self-efficacy and the compliance of information security policy, and between the social influence and the compliance of information security policy. However, there was no meaningful relationship between the standard belief and the compliance of information security policy. This study examined to what extent the workers of shipping and port organization that have a high possibility of the information leakage were compliant with the information security policy. The findings will contribute to organizations of shipping and port who attempt to establish strategies related to information security.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.24 no.4
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• pp.286-295
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• 2017

Purpose: The World Health Organization identifies spiritual care as a component of health and thus nursing care. There is a need to identify how self-esteem, communication and existential well-being affects spiritual care competence in nurses. Methods: The participants were 189 nurses in G metropolitan city. The survey was conducted from March 21 to April 8, 2016, with a self-report questionnaire. Data were analyzed using descriptive statistics, independent t-test, one-way ANOVA, $Scheff{\acute{e}}$ test, Pearson correlation coefficient and stepwise multiple regression analysis using SPSS version 21.0. Results: Differences in spiritual care competence were statistically significant according to education level, work department, position, having received spiritual care education, experience of providing spiritual care, experience of asking religionist to provide spiritual care for a patient and recognition of need for spiritual care. The spiritual care competence of nurses showed a significantly positive correlation with self-esteem, communication and existential well-being. Factors influencing spiritual care competence were communication, experience of providing spiritual care and existential well-being which explained about 37.5% of spiritual care competence. Conclusion: It's necessary for nurses to develop intervention programs to strengthen spiritual care competence through improving communication, providing opportunities for spiritual care and existential well-being.

• Korean Journal of Artificial Intelligence
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• v.8 no.1
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• pp.7-9
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• 2020

In this paper, a study was conducted to find a self-diagnosis method to prevent the spread of COVID-19 based on machine learning. COVID-19 is an infectious disease caused by a newly discovered coronavirus. According to WHO(World Health Organization)'s situation report published on May 18th, 2020, COVID-19 has already affected 4,600,000 cases and 310,000 deaths globally and still increasing. The most severe problem of COVID-19 virus is that it spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, which occurs in everyday life. And also, at this time, there are no specific vaccines or treatments for COVID-19. Because of the secure diffusion method and the absence of a vaccine, it is essential to self-diagnose or do a self-diagnosis questionnaire whenever possible. But self-diagnosing has too many questions, and ambiguous standards also take time. Therefore, in this study, using SVM(Support Vector Machine), Decision Tree and correlation analysis found two vital factors to predict the infection of the COVID-19 virus with an accuracy of 80%. Applying the result proposed in this paper, people can self-diagnose quickly to prevent COVID-19 and further prevent the spread of COVID-19.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• Korean Journal of Adult Nursing
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• v.26 no.5
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• pp.553-562
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• 2014

Purpose: The purpose of this study was to identify factors influencing workplace bullying among Korean hospital nurses. Methods: Subjects in this study included 178 hospital nurses who attended two nationwide nursing educational conferences in 2013. The data was collected using self-report questionnaires which were used to identify the subjects' characteristics, self-esteem, perception of nursing organizational culture, and workplace bullying experience. Results: The results showed that 19.1% of study subjects reported being victims of workplace bullying and mostly experienced person-related and work-related bullying. Multiple regression analysis was done to identify factors affecting workplace bullying. The perception of relation-oriented culture, task-oriented culture and self-esteem turned out to be variables that explained nurses' workplace bullying, and these factors accounted for 32.0% of the variance. Conclusion: The findings suggest that nurses experience more workplace bullying in task-oriented cultures. However, they experience less bullying and report higher self-esteem and awareness in relation-oriented cultures. Interventions focused on the characteristics of the organization need to be developed to prevent workplace bullying in hospital nurses.

• Journal of Agricultural Extension & Community Development
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• v.12 no.1
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• pp.69-81
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• 2005

The objectives of this study were to measure role conflict of 4-H leaders and to verify the differences of role conflict and self-efficacy according to individual characteristics. The data were collected from 99 leaders who took charge of guiding 4-H youth organization in school as teacher advisor. The statistical techniques used for this study were frequency, t-test, one-way analysis of variance and correlation. The major findings of this study were as follows; 1) The 4-H leaders had some role conflict and role ambiguity in guiding youth activities in the school. 2) The leader advisor group with teaching experience of $5{\sim}9$ years showed higher role conflict and lower role ambiguity. 3) The 4-H leaders with age over 45 felt higher role conflict and lower role ambiguity. 4)The leaders' self-efficacy was positively correlated with self esteem, and negatively associated with role ambiguity.

• Journal of Korean society of Dental Hygiene
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• v.17 no.2
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• pp.259-269
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• 2017

Objectives: The purpose of this study was to review the correlation between self-concept and organization of socialization in professional settings among dental hygienists. Methods: Statistical analysis was carried out on the collected data to identify any correlation between frequency and percentages. Cronbach's alpha value and one-way ANOVA were conducted. SPSS 12.0 was used to conduct a correlation analysis on self-concept and socialization in professional settings. Validity of the research tools was also confirmed. Results: There was a correlation between the identity and job satisfaction, with the figures showing great variance. Satisfaction was correlated with the nature of the corporation and job performance. In addition, communication had a negative correlation between job characteristics and identities, job performance, while, organizational commitment and positive correlation showed a statistically significant difference. Conclusions: The study reviewed the impact on organizational socialization. The dental hygienist is believed to be on going research into developing more effective and systematic training programs so that they can be effectively socialized society organizations to improve the professional self-concept.