• Digital Contents
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• no.5 s.84
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• pp.64-69
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• 2000

이 장은 Competitive intelligence를 학습과정의 한 측면으로 파악하여 Competitive intelligence와 인간자원의 관계를 설명한다. 여기서, Intelligence의 형성에 할애된 노력과 금액을 비교하여 투자 회수에 관한 사례를 고려할 수 있다. 기업 외부에 있는 정보는 기업 내부의 지식으로 구축하여 자본을 최대한 활용 보충할 수 있도록 획득되어야 한다. 이러한 점에서 지식망의 구축과 지식의 전달. 관리에 관련하여 설명한다.

• The Journal of the Acoustical Society of Korea
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• v.13 no.4
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• pp.60-68
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• 1994

In this paper we propose a new Hybrid learning rule applied to multilayer feedforward neural networks, which is constructed by combining Hebbian learning rule that is a good feature extractor and Back-Propagation(BP) learning rule that is an excellent classifier. Unlike the BP rule used in multi-layer perceptron(MLP), the proposed Hybrid learning rule is used for uptate of all connection weights except for output connection weigths becase the Hebbian learning in output layer does not guarantee learning convergence. To evaluate the performance, the proposed hybrid rule is applied to classifier problems in two dimensional space and shows better performance than the one applied only by the BP rule. In terms of learning speed the proposed rule converges faster than the conventional BP. For example, the learning of the proposed Hybrid can be done in 2/10 of the iterations that are required for BP, while the recognition rate of the proposed Hybrid is improved by about $0.778\%$ at the peak.

• Journal of the Korean GEO-environmental Society
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• v.3 no.4
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• pp.11-17
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• 2002

The purpose of this study is the prediction of pollutant loads into Seomjin river watershed using neural networks model. The pollutant loads into river watershed depend upon the water quantity of inflow from the upstream as well as the water quality of the inflow into the river. For the estimation of pollutants into river, a neural networks model which has the features of multi-layered structure and parallel multi-connections is used. The used water quality parameters are BOD, COD and SS into Seomjin river. The results of calibration are satisfactory, and proved the availability of a proposed neural networks model to estimate short-term water quality pollutants into river system.

• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.574-599
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• 2018

The purpose of this study is to suggest implications for the importance of shared leadership of leaders by analyzing the influence of learning orientation and unlearning on the recognition of leader's shared leadership and employees'. The questionnaire survey was conducted on the employees who work as knowledge workers in the domestic SMEs. A total of 387 questionnaires were collected using SPSS 24.0 statistical package. The results of this study were that the relationships between a leader's shared leadership and innovation behavior, shared leadership and learning orientation, and learning orientation and innovation behavior were positive. In addition, learning orientation mediated in the relationship between shared leadership and innovation behavior, and unlearning reinforced the relationship between shared leadership and learning orientation. The implication of this study is that the employees themselves need continuous reinforcement activities for active unlearning and learning orientation in order to improve the innovation behavior of the employees. In addition, the shared leadership of leaders in employees and organization is more important.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.10
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• pp.1816-1823
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• 1992

In order to develop general CMAC training technique applicable to any CMAC, characteristics of CMAC learning algorithm and training problems of CMAC are studied. Neighborhood Sequential Training technique which is general and free fro CMAC learning interference is proposed. The technique is used to generate mathematical functions and found to be effective.

• Journal of Gifted/Talented Education
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• v.24 no.1
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• pp.1-16
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• 2014

This study was to examine whether high school students' academic motivation and learning strategies influence their competence. Of the 600 high school students surveyed from 3 high schools in two metropolitan cities, Korea, 489 completed and returned the questionnaires yielding a total response rate of 81.50%. The final sample consisted of 399 males (81.6%) and 82 females (16.8%). Among the final sample, 113 students were gifted, and 376 students were non-gifted. Their average age was 17.20 years. Measures of students' competence (i.e., cognitive competence, and social competence), academic motivation (i.e., intrinsic motivation to know, toward accomplishment, and to experience stimulation, and extrinsic motivation identified, introjected, and external regulation, and amotivation), and learning strategies (i.e., metacognition, self-monitoring, strategy formation) Spearman's rho(${\rho}$) indicated that students' competence was positively associated with intrinsic (i.e., to know, toward accomplishment, to experience stimulation) and extrinsic (i.e., identified, introjected) motivation, and learning strategies. However, students' competence was negatively associated with amotivation. Hierarchical multiple regression analyses showed that intrinsic motivation (i.e., to experience stimulation), extrinsic motivation(i.e., external regulation), and learning strategies (i.e., strategy formation) were the crucial contributors for enhancing students' competence. Results are discussed in relation to theoretical implications and school settings.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.204-210
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• 2002

The self-organizing feature map of Kohonen has disadvantage that needs too much input patterns in order to converge into the equilibrium state when it trains. In this paper we proposed the method of improving the convergence speed and rate of self-organizing feature map converting the interaction set into Dynamic Gaussian function. The proposed method Provides us with dynamic Properties that the deviation and width of Gaussian function used as an interaction function are narrowed in proportion to learning times and learning rates that varies according to topological position from the winner neuron. In this Paper. we proposed the method of improving the convergence rate and the degree of self-organizing feature map.

• Journal of the Health Care and Life Science
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• v.9 no.1
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• pp.77-86
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• 2021

This study is a research study to determine the effect of online lecture substitution for subjects due to COVID-19 on self-directed learning ability, academic achievement, and online learning satisfaction of nursing students. From September to October 2020, the final 113 nursing students of data recovered as enrolled in the Department of Nursing at a university located in G City were analyzed. The data collected were analyzed by performing descriptive statistics and hierarchical regression analysis using the SPSS 21.0 program. The study results are summarized as follows. The average score of self-directed learning was 3.32±0.39, academic achievement 3.32±0.75, and learning satisfaction was 3.31±0.78. Factors affecting online learning satisfaction were found to be preferred learning methods and academic achievement. Based on the results of this study, it is necessary to design instruction and operate classes to improve online learning satisfaction by evaluating the learner's learning method in advance when running nursing school subjects as online lectures for nursing students.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.51-63
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• 2001

In supervised machine learning, an induction algorithm, which is able to extract rules from data with learning capability, provides a useful tool for data mining. Practical induction algorithms are known to degrade in prediction accuracy and generate complex rules unnecessarily when trained on data containing superfluous features. Thus it needs feature subset selection for better performance of them. In feature subset selection on the induction algorithm, wrapper method is repeatedly run it on the dataset using various feature subsets. But it is impractical to search the whole space exhaustively unless the features are small. This study proposes a heuristic method that uses sensitivity analysis of neural networks to the wrapper method for generating rules with higher possible accuracy. First it gives priority to all features using sensitivity analysis of neural networks. And it uses the wrapper method that searches the ordered feature space. In experiments to three datasets, we show that the suggested method is capable of selecting a feature subset that improves the performance of the induction algorithm within certain iteration.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.346-356
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• 2012

The purpose of this study is to examine the effect of opinion leader behavior on E-learning satisfaction on the mediating role of social intelligence. For the study, opinion leader behavior were defined two groups such as information mediated behavior, influence behavior and e-learning satisfaction were defined two groups such as contents satisfaction, operation satisfaction. On the basis of theoretical linkages between the constructs, a conceptual model and hypotheses were established. Data were collected from 153 graduated students by structured questionnaires. Collected data were analyzed by PLS(Partial Least Square) statistics program and findings are as follows. Empirical results indicate that opinion leader behavior has a positive impact on opinion leader's social intelligence, social intelligence has a positive impact on E-learning satisfaction. Opinion leader's social intelligence has partially mediated effect on the relationship between opinion leader behavior and E-learning satisfaction.