• Informatization Policy
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• 제24권1호
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• pp.100-112
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• 2017

This study verified the relationship between internet use, family relationship, and cyber violence victimization by comparing models. 2013 The survey of Internet addiction of National Information Society Agency was used in this study to verify relationship between variables. We compared the model which internet use impact cyber violence victimization through mediating fully family relationship and other model which internet use influence cyber violence victimization through mediating partially family relationship. Based on final model (model 1), More internet use was related to lower family bond and lower family bond was associated with more cyber violence victimization. This results imply that family relationship have an important role in relationship between internet use and cyber violence victimization rather than internet use impact directly cyber violence victimization.

• Journal of Korea Port Economic Association
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• 제38권2호
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• pp.153-164
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• 2022

In this study, we estimate the quantile-regression framework of the shipping industry for the Capesize used ship, which is a typical raw material transportation from January 2000 to December 2021. This research aims two main contributions. First, we analyze the relationship between the Capesize used ship, which is a typical type in the raw material transportation market, and the freight market, for which mixed empirical analysis results are presented. Second, we present an empirical analysis model that considers the structural transformation proposed in the Hyunsok Kim and Myung-hee Chang(2020a) study in quantile-regression. In structural change investigations, the empirical results confirm that the quantile model is able to overcome the problems caused by non-stationarity in time series analysis. Then, the long-run relationship of the co-integration framework divided into long and short-run effects of exogenous variables, and this is extended to a prediction model subdivided by quantile. The results are the basis for extending the analysis based on the shipping theory to artificial intelligence and machine learning approaches.

• Journal of Korean Society of Transportation
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• 제17권3호
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• pp.117-130
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• 1999

Earthquakes damage roadway bridges and structures, resulting in significant impacts on transportation system Performance and regional economy. Seismic risk analysis (SRA) procedures establish retrofit priorities for vulnerable highway bridges. SRA procedures use average daily traffic volumes to determine the relative importance of a bridge. This research develops a cost-effective transportation network analysis (TAN) procedure for evaluating numerous traffic flow analyses in terms of the additional system cost due to failure. An important feature of the TNA Procedure is the use of an associative memory (AM) approach in the artificial intelligence held. A simple seven-zone network is developed and used to evaluate the TNA procedure. A subset of link failure system states is randomly selected to simulate synthetic post-earthquake network flows. The performance of different AM model is evaluated. Results from numerous link-failure scenarios demonstrate the applicability of the AM models to traffic flow estimation.

• Journal of the Korean Institute of Intelligent Systems
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• 제21권2호
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• pp.171-177
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• 2011

Accuracy and computing time are considerable issues in machine learning. In general, the computing time for data analysis is increased in proportion to the size of given data. So, we need a sampling approach to reduce the size of training data. But, the accuracy of constructed model is decreased by going down the data size simultaneously. To solve this problem, we propose a new statistical sampling method having similar performance to the total data. We suggest a rule to select optimal sampling techniques according to given data structure. This paper shows a sampling method for reducing computing time with keeping the most of accuracy using cluster sampling, stratified sampling, and systematic sampling. We verify improved performance of proposed method by accuracy and computing time between sample data and total data using objective machine learning data sets.

• The Journal of the Korea Contents Association
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• 제18권2호
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• pp.569-582
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• 2018

The purpose of this study is to examine the mediating effect of personality and emotional intelligence in the relationship with job stress of teachers and burnout to prevent the burnout of teachers and provide primary data for counseling intervention. Thus, the survey was conducted on 488 teachers and the hypothesis of this study was verified using structural equation model. The research findings are as shown below. First, the job stress, neuroticism and burnouts were positively related while the extroversion, conscientiousness, emotional intelligence were negatively related. And the neuroticism was negatively related with emotional intelligence but positively related with burnout. And the extroversion, openness, conscientiousness had positive relationship with emotional intelligence but negative relationship with burnout. However, the agreeableness did not have significant relationship with emotional intelligence and burnout. Second, the emotional intelligence partially mediated in the relationship with job stress and burnout. Third, the neuroticism, extroversion and conscientiousness partially mediated in the relationship with job stress and burnout, but the openness and agreeableness were found not to mediate. Based on these results, the practicability of counselling and further research was discussed in this study.

• Journal of the Korean Institute of Intelligent Systems
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• 제8권3호
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• pp.33-40
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• 1998

This paper presents an Modified Orthogonal Neural Network(MONN), new modified model of Orthogonal Neural Network(0NN) based on orthogonal functions, and applies it to nonlinear system approximator. ONN proposed by Yang and Tseng, doesn't have the problems of traditional multilayer feedforward neural networks such as the determination of initial weights and the numbers of layers and processing elements. And tranining of ONN converges rapidly. But ONN cannot adapt its orthogonal functions to a given system. The accuracy of ONN, in terms of the minimal possible deviation between system and approximator, is essentially dependent on the choice of basic orthogonal functions. In order to improve ability and effectiveness of approximate nonlinear systems, MONN has an input transformation layer to adapt its basic orthogonal functions to a given nonlinear system. The results show that MONN has the excellent performance of approximate nonlinear systems and the input transfnrmation makes the ability of MONN better than one of ONN.

• Journal of Gifted/Talented Education
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• 제26권2호
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• pp.281-297
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• 2016

The purpose of this study was to investigate the structural relationships between gifted preschool children and their related variables(creativity, motivation, family system). 230 preschool children, parents and teachers from U-city have participated in this study. the collected data were analyzed with SPSS and AMOS. The goodness of fit was evaluated using the SRMR, RMSEA, CFI, and TLI. The results of this study were as follows: First, family system(adaptability, cohesion) were found to have a statistically significant direct impact on gifted preschool children. Second, creativity were found to have a significant direct effects on gifted preschool children. moreover they also had an indirect effect on gifted preschool children through family system. Third, motivation were found to have a statistically significant direct impact on gifted preschool children.

• Journal of the Korean Society of Food Science and Nutrition
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• 제39권12호
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• pp.1880-1892
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• 2010

The purposes of this study were to: a) provide evidence concerning the effects of emotional intelligence on job outcomes, b) examine the impacts of emotional intelligence on employee-related variables such as 'job satisfaction', 'organizational commitment', 'organizational performance', and 'turnover intention' c) identify the conceptual framework underlying emotional intelligence. A survey was conducted to collect data from foodservice managers (N=231). Statistical analyses were completed using SPSS Win (16.0) for descriptive analysis, reliability analysis, factor analysis, t-test, correlation analysis, cluster analysis and AMOS (16.0) for confirmatory factor analysis and structural equation modeling. The concept of emotional intelligence (EI) has been on the radar screens of many leaders and managers over the last several decades. The emotional intelligence is generally accepted to be a combination of emotional and interpersonal competencies that influence behavior, thinking and interaction with others. The main results of this study were as follows. The four EI (Emotional Intelligence) dimensions correlated significantly with age. The means of job satisfaction score were above the midpoint (3.04 point) scale. The organizational commitment score was above the midpoint (3.41 point) scale and was higher at 'loyalty' factor than 'commitment' factor. The means of organizational performance score were above the midpoint (3.34) scale. The correlations among the four EI (emotional intelligence) factors were significant with job satisfaction; organizational commitment, organizational performance and turnover intention. The test of hypothesis using structural equation modeling found that emotional intelligence produced positive effects on job attitude and job performance. Emotional intelligence enhanced organizational commitment, and in turn, managers' attitude produced positive effects on organizational performance; emotional intelligence also had a direct impact on organizational performance. This study has identified the effect of emotional intelligence on organizational performance and attitudes toward one's job.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.201-204
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• 1997

최근 주소를 자동으로 인식하여 우편물 분류와 같은 업무를 효과적으로 수행하기 위한 연구가 진행되고 있다. 기존 연구들은 낱자 단위의 인식을 수행한 후 사전 형태의 간단한 DB를 통해 최종의 결과를 생성한다. 그러나 한글과 같은 복잡한 구조의 필기 문자에 대한 인식기의 성능은 아직도 미흡한 상태이다. 따라서 낱자 인식기의 성능에 의존하는 현재와 같은 방법으로는 만족할 만한 결과를 얻기가 힘들 것으로 생각된다. 본 논문에서는 낱자 인식 결과에 크게 의존하지 않고 주소에 나타나는 단어의 낱자들 사이간 연결 정보를 이용하여 단어를 인식할 수 있는 시스템을 제안한다. 본 시스템은 통계적 인식기를 사용하여 낱자를 인식하는 부분과 낱자 인식 결과를 조합하여 단어 수준의 인식과정을 통해 최종의 결과를 생성하는 부분으로 구성된다. 통계적 인식기는 Nearest neighborhood 방법을 사용하여 간단한 형태로 구현하였다. 단어인식 모듈은 단어에서 모든 문자간의 관계를 표현할 수 있도록 HMM 모형을 사용하여 어휘정보 네트워크를 구성하고 이를 이용하여 주소에 나타나는 단어를 인식하도록 하였다. PE92 한글 문자 데이터를 이용하여 실험을 수 璿\ulcorner 결과, 통계적 인식기의 성능이 저조함에도 불구하고 HMM을 이용한 어휘정보 네트워크가 이를 보완함으로써 좋은 결과를 얻었다. 이러한 단어 인식 방법을 주소 이외의 다른 단어 집합에 대해서도 쉽게 적용될 수 있을 것으로 예상된다.

• Journal of Digital Convergence
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• 제19권4호
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• pp.185-192
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• 2021

The purpose of this study is to investigate the relationship between emotional intelligence and convergence factors of hospital administrative staff. During the survey period from From May 1st to May 31st, 2019, anonymous self-administered responses to 212 administrative staffs of 19 hospitals randomly selected in J area were used as analysis data. According to hierarchical multiple regression analysis, the higher the ego-resiliency, the higher the organizational loyalty, and the higher the organizational commitment, the higher the emotional intelligence, and their explanatory power was 43.0%. Based on these analysis results, efforts are needed to increase ego-resiliency, increase organizational loyalty, and increase organizational commitment in order to increase the emotional intelligence of hospital administrative jobs. The above results are expected to be applied to industrial health education and job management in the future at hospitals to enhance emotional intelligence of hospital administrative staffs. Future research requires the establishment and analysis of a structural equation model that affects the emotional intelligence of hospital administrative staffs.