• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.354-359
• /
• 2003

In this paper, we consider the problem of designing a simple learning variable structure system for repeatable tracking control of robot manipulators. We combine a variable structure control law as the robust part for stabilization and a feedforward learning law as the intelligent part for nonlinearity compensation. We show that the tracking error asymptotically converges to zero. Finally, we give computer simulation results in order to show the effectiveness of our method.

• 한국경영과학회지
• /
• 제31권3호
• /
• pp.127-143
• /
• 2006

While e-learners' satisfaction would be determined by qualify of e-learning environment including learning management systems, learning contents and interactions, the influence of quality on satisfaction can be changed by e-learners' self-regulated efficacy The objective of this study is to show difference of the relationship between qualify and satisfaction In e-learning by self-regulated efficacy. For this purpose, we propose a research model which consists of five quality factors in e-learning as explaining variables, satisfaction as a result variable and self-regulated efficacy as a control variable. For empirical test of this model, the sample is collected from e-learning classes in a college and divided into two groups by self-regulated efficacy in order to analyze the effects of control variable. By multi-group analysis, we show two groups are different from each other in the relationship between quality and satisfaction of e-learning environment.

• 전자공학회논문지B
• /
• 제29B권1호
• /
• pp.94-101
• /
• 1992

The multilayer perceptron, trained by the error back-propagation learning rule, has been known as a mapping network which can represent arbitrary functions. However depending on the complexity of a function and the initial weights of the multilayer perceptron, the error back-propagation learning may fall into a local minimum or a flat area which may require a long learning time or lead to unsuccessful learning. To solve such difficulties in training the multilayer perceptron by standard error back-propagation learning rule, the paper proposes a learning method which progressively enlarges the learning domain from a small area to the entire region. The proposed method is devised from the investigation on the roles of hidden nodes and connection weights in the multilayer perceptron which approximates a function of one variable. The validity of the proposed method was illustrated through simulations for a function of one variable and a function of two variable with many extremal points.

• 대한수학교육학회지:학교수학
• /
• 제1권1호
• /
• pp.19-37
• /
• 1999

In this study, we examined some matters related to the learning of variable concept in school mathematics on the basis of the theoretical foundation from the previous studies(e.g. Davis, 1975; Rosnick, 1981; IK chemann, 1981; Wagner, 1983.) and practices on variable concept teaching by evaluating the current state of that. Matters be discussed are as follows; the use of symbol for place holders in elementary mathematics, the dealing with sets those elements are literals and operations of such sets, the teaching of dummy variable, the construction of literal expressions that contains variables, the labeling indeterminates as a constant, the change in the exact meaning of variable according to the function concept, the teaching of a generalization by means of variables. After considering on these matters that are connected with the teaching-learning of variable concept, we suggested the alternative proposal to the current state of variable concept teaching.

• 영재교육연구
• /
• 제6권1호
• /
• pp.93-109
• /
• 1996

The purpose of this study was to investigate the relationship between learning strategies and cognitive learning abilities with achievement scores of elementary school children. To achieve this purpose, 109 sixth grade children were sampled in Seoul-City, and the 'Questionnaire on the Learning Strategies and Learning Abilities Test' were administered to them. The collected data were analyzed by Pearson's Product Moment Correlation and Multiple Regression Analysis. The major findings of this study were as follows: Firstly, there appeared to be statistically significant correlations between learning strategies and achievement scores. The process of thinking variable of learning strategies were most significantly correlated with achievement scores(r=.251- .458, p<.01). The calculated R2 indicated that the combined effects of process of thinhng and affective domain on the achievement scores were about 21.5%. Secondly, there appeared to be statistically significant correlations between cognitive learning abilities and achievement scores. The verbal reasoning and verbal comprehension variable of cognitive learning abilities were most significantly correlated with achievement scores(r=.215-,493, p<.01). The calculated R2 indicated that the verbal reasoning and verbal comprehension variable of cognitive learning abilities explained about 27.6% of the variance of achievement scores. Thirdly, there appeared to be no statistically significant correlations between learning strategies and cognitive learning abilities. The results of this study shows that the development of learning strategies and cognitive learning abilities could improve the achievement scores in school learning.

• 한국학교수학회논문집
• /
• 제14권2호
• /
• pp.199-213
• /
• 2011

학습에 영향을 끼치는 요인은 크게 학습자특성변인, 교수자특성변인, 학습과제특성변인, 환경특성변인으로 구분하여 논의해 볼 수 있는데, 이 요소들 중에서도 학습자의 특성을 파악하는 것이 교육 계획을 작성하기 위해 가장 우선적으로 이루어져야 할 것이다. 이에 본 연구는 학습자의 특성 중 정의적 특성인 자아개념 학습습관 학습태도가 수학학업성취에 어떠한 영향을 미치는지에 대해 알아보고 초등학생의 학업 성취 및 태도에 관한 교육 방법으로 모색하도록 하는 데에 그 목적이 있다. 이를 위해 본 연구에서는 충청남도 A 시에 위치한 초등학교 5학년 2개반 78명을 대상으로 질문지 검사를 실시하였다. 그 결과 수학에 대한 자아개념, 학업에 대한 자아개념, 수학에 대한 학습습관, 수학에 대한 태도, 학업 에 대한 학습습관, 학업에 대한 태도 순으로 수학학업성취와 상관정도가 높음을 알 수 있었다.

• 한국정보통신설비학회:학술대회논문집
• /
• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
• /
• pp.382-386
• /
• 2009

Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.

• 산업경영시스템학회지
• /
• 제20권42호
• /
• pp.161-169
• /
• 1997

A variety of learning methods are used for neural networks. Among them, the backpropagation algorithm is most widely used in such image processing, speech recognition, and pattern recognition. Despite its popularity for these application, its main problem is associated with the running time, namely, too much time is spent for the learning. This paper suggests a method which maximize the convergence speed of the learning. Such reduction in e learning time of the backpropagation algorithm is possible through an adaptive adjusting of the slope of the activation function depending on total errors, which is named as the variable slope algorithm. Moreover experimental results using this variable slope algorithm is compared against conventional backpropagation algorithm and other variations; which shows an improvement in the performance over pervious algorithms.

• 토지주택연구
• /
• 제8권3호
• /
• pp.123-130
• /
• 2017

This study aims to empirically verify the impacts of career learning on employability and the mediating effect of job expertise in a public corporation. For the empirical analysis, I surveyed 958 employees(valid respondents) working in a public corporation. And the structural equation modeling(SEM) was used to statistically analize and test the research hypotheses. The independent variable is 'career learning', the dependent variable is 'employability' and the mediating variable is 'job expertise'. The results are as follows. The empirical analysis shows that the positive effects of 'career learning ${\rightarrow}$ job expertise', 'job expertise ${\rightarrow}$ employability' and 'career learning ${\rightarrow}$ employability' are all verified. And the mediating effect of job expertise between career learning and employability is also partially verified. So, all the proposed hypotheses are accepted. From this result, I can clearly suggest that the employees can be growing to professionals with high employability when they retire if they are voluntarily and self-motivated to set up their career plan and to enhance their job expertise. In this context, it is expected that the company should support the employees to continue to strengthen their own expertise in their job place through their mid-long term career learning plan.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.450-453
• /
• 1997

An active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. The result of simulations shows that the crane is just controlled for a very large swing angle of 1 radian within nearly one cycle.