• Journal of Engineering Education Research
• /
• v.3 no.2
• /
• pp.3-13
• /
• 2000

The paper has analyzed and summarized about the theoretical problem occurred in the CAQC, and has developed the learning model focused on the histogram as a case study. The range of study is to systematize the basic method of histogram generally used, and to make step by step procedures under the interactive relation with the improvement of the theory that must be added in case of the calculation by the aided of MS-Excel software. A histogram is the theory to understand the population distribution from which samples are extracted, so alternative methods are presented to estimate the population shape through an experiment and a practice. In order to enlarge the application area of the histogram in the factory, the theory of normal test, the criteria of process capability index and the probability calculation of PPM are added to the histogram. The learning model of CAQC education is proposed that is consistent with the target of histogram to control and search the cause of item defectives fast and correctly.

• Korean Journal of Child Studies
• /
• v.4
• /
• pp.1-10
• /
• 1983

This study examined the characteristics of the relationship of home environment variables and preschool children's intelligence, learning readiness and socio-emotional developments. The subjects of this study were 63 children at age five and their mothers. Instruments included the children's intelligence test, preschool inventory for learning readiness, the socio-emtional rating scale and the inventory of HOME. The data of the present study were analyzed by the statistical methods of Pearson's product-moment correlation coefficient and step-wise multiple regression analysis. The kinds of HOME variables that significantly predict children's intelligence were "need gratification and avoidance of restriction" "quality of language environment" "play materials" "aspects of physical environment" "organization of stable and predictable environment". The variables that significantly predict children's socio-emotional developments were "breath of experience" "fostering maturity and independence" "developmental stimulation". All of the HOME variables were not significantly predict children's learning readiness. The kinds of HOME factors that significantly predict children's intelligence were factor II and factor III. Factor I predicted children's socio-emotional developments significantly. All of the HOME factors were not significantly predicted children's learning readiness.

• Management Science and Financial Engineering
• /
• v.16 no.1
• /
• pp.81-117
• /
• 2010

Semi-supervised learning incorporates unlabeled examples, whose labels are unknown, as well as labeled examples into learning process. Although transductive support vector machine (TSVM), one of semi-supervised learning models, was proposed about a decade ago, its application to large-scaled data has still been limited due to its high computational complexity. Our previous research addressed this limitation by introducing a branch-and-bound algorithm for finding an optimal solution to TSVM. In this paper, we propose three new techniques to enhance the performance of the branch-and-bound algorithm. The first one tightens min-cut bound, one of two bounding strategies. Another technique exploits a graph-based approximation to a support vector machine problem to avoid the most time-consuming step. The last one tries to fix the labels of unlabeled examples whose labels can be obviously predicted based on labeled examples. Experimental results are presented which demonstrate that the proposed techniques can reduce drastically the number of subproblems and eventually computational time.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.4
• /
• pp.90-99
• /
• 2023

This paper deals with studying strategy about impact of deep learning (DL) on the factor of Korean economic growth. To study classification of impact factors of Korean economic growth, we suggest dynamic equation of microeconomy and study methods on economic growth impact of deep learning. Next step is to suggest DL model to dynamic equation with Korean economy data with growth related factors to classify what factor is import and dominant factors to build policy and education. DL gives an influence in many areas because it can be implemented with ease as just normal editing works and speak including code development by using huge data. Currently, young generations will take a big impact on their job selection because generative AI can do well as much as humans can do it everywhere. Therefore, policy and education methods should be rearranged as new paradigm. However, government and officers do not understand well how it is serious in policy and education. This paper provides method of policy and education for AI education including generative AI through analysing many papers and reports, and experience.

• International journal of advanced smart convergence
• /
• v.8 no.4
• /
• pp.68-74
• /
• 2019

Along with the deeper architecture in the deep learning approaches, the need for the data becomes very big. In the real problem, to get huge data in some disciplines is very costly. Therefore, learning on limited data in the recent years turns to be a very appealing area. Meta-learning offers a new perspective to learn a model with this limitation. A state-of-the-art model that is made using a meta-learning framework, Meta-SGD, is proposed with a key idea of learning a hyperparameter or a learning rate of the fast adaptation stage in the outer update. However, this learning rate usually is set to be very small. In consequence, the objective function of SGD will give a little improvement to our weight parameters. In other words, the prior is being a key value of getting a good adaptation. As a goal of meta-learning approaches, learning using a single gradient step in the inner update may lead to a bad performance. Especially if the prior that we use is far from the expected one, or it works in the opposite way that it is very effective to adapt the model. By this reason, we propose to add a weight term to decrease, or increase in some conditions, the effect of this prior. The experiment on few-shot learning shows that emphasizing or weakening the prior can give better performance than using its original value.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.5
• /
• pp.231-240
• /
• 2019

The purpose of this study is to understand of flipped learning of vocational high school teachers and to provide basic data of teacher training program development that can support flipped learning classes of vocational high school. We conducted surveys and focus group interviews to solve these research problems. The focus group interview is conducted on four flipped learning teachers who participated in the questionnaire. The results of this study are as follows. First, vocational high school teachers only heard the term 'flipped learning', but they did not have much experience in class. Second, it is necessary to learn contents and pre-learning for basic understanding of flipped learning, method of making learning contents of learning materials that focused on students' motivation and interest in the classroom. Also, we needed a method to induce participation in classroom activities, and a compensation method and evaluation method to maintain it. In addition, they requested specific flipped learning instruction procedures and various learning materials at each stage in accordance with the vocational high school situation. Third, I requested training contents and practice - centered training method that can induce interest and motivation as the training management method for the vocational high school teachers' flipped learning classes. In addition, it required step - by - step training according to the understanding level of flipped learning of high school teacher.

• Journal of the Korean Home Economics Association
• /
• v.51 no.2
• /
• pp.253-261
• /
• 2013

The purpose of this study was to investigate the moderating effects of parental monitoring on the relationship between children's dependency on mobile phones and control of learning behavior. The data came from the 2010 Korean Children and Youth Panel (N = 1,609) conducted by the National Youth Policy Institute. The analysis method used was Structural Equation Modeling by using SPSS 17.0 and AMOS 7.0. To test the significant moderating effects, Ping's two-step technique, which is free from the requirement of nonlinear constraints, was used. Our results demonstrated that children's dependency on mobile phones had negative effects on control of learning behavior, and the interaction effects between such dependency and parental monitoring affected the control of learning behavior. Thus, these results proved the moderating effects of parental monitoring in the control of learning behavior. This study suggests that parental monitoring buffers against having difficulties to control and adjust one's behavior associated with control of learning behavior, which is affected by the dependency on mobile phones among children. We discussed that the risks of children's dependency on mobile phones and parental monitoring should be acknowledge as a significant protective factor.

• Journal of The Korean Association of Information Education
• /
• v.7 no.2
• /
• pp.189-197
• /
• 2003

WBI(Web Based Instruction) has been confined to some course due to a burden of development of instruction materials. In this paper, we implemented a personalized instruction and learning system for Word Processor based on Internet by using WBI. Compared to the traditional instruction and learning method for Word Processor Education, the proposed method induce students to take an interest in the learning and make it possible to do student oriented instruction and learning due to the selection of specific contents according to student's ability and his/her learning step. And this system can evaluate the learning rate on the spot by using personalized homework and maximize learning effect by using feedback.

• The Journal of the Korea Contents Association
• /
• v.14 no.7
• /
• pp.550-558
• /
• 2014

The purposes of the study are to introduce and apply an activity that can help improve student-initiated learning on the TOEIC Speaking Test (TOEICST) performance and to see students' attitude toward the activity. Twenty-eight university students in Chungcheong province engaged in learning based on this activity. In the present study, the activity proposed by McCormick and Vercellotti (2013) and Stillwell, Curabba, Alexander, Kidd, Kim, Stone, & Wyle (2010) was modified and adapted[14][19]. The outline of the Task Recording Activity (TRA) consisted of three steps: preparation step, Task Recording Activity step, and evaluation step. As data collection of the study, a survey and students' journal were utilized and qualitatively analyzed. The results showed that student-initiated learning activity could be applied positively not only in communicative lessons, but in TOEICST specific lessons as well. Additionally, participants showed positive attitudes toward self-transcription and self-correction. Some implications of the study are that the TRA can be applied to generate autonomous learners studying for the TOEIC Speaking Test, that the guideline for different proficiency can be developed to help them improve their self-reflection, and that students need to have an active attitude to lead their own learning.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.3B
• /
• pp.279-289
• /
• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.