• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.25-30
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• 2018

This paper is about wine quality classification with multilayer perceptron using the deep neural network. Wine complexity is an issue when predicting the quality. And the deep neural network is considered when using complex dataset. Wine Producers always aim high to get the highest possible quality. They are working on how to achieve the best results with minimum cost and efforts. Deep learning is the possible solution for them. It can help them to understand the pattern and predictions. Although there have been past researchers, which shows how artificial neural network or data mining can be used with different techniques, in this paper, rather not focusing on various techniques, we evaluate how a deep learning model predicts for the quality using two different activation functions. It will help wine producers to decide, how to lead their business with deep learning. Prediction performance could change tremendously with different models and techniques used. There are many factors, which, impact the quality of the wine. Therefore, it is a good idea to use best features for prediction. However, it could also be a good idea to test this dataset without separating these features. It means we use all features so that the system can consider all the feature. In the experiment, due to the limited data set and limited features provided, it was not possible for a system to choose the effective features.

• Annual Conference of KIPS
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• 2016.04a
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• pp.633-635
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• 2016

Convolutional Networks (ConvNets) are powerful models that learn hierarchies of visual features, which could also be used to obtain image representations for transfer learning. The basic pipeline for transfer learning is to first train a ConvNet on a large dataset (source task) and then use feed-forward units activation of the trained ConvNet as image representation for smaller datasets (target task). Our key contribution is to demonstrate superior performance of multiple ConvNet layer features over single ConvNet layer features. Combining multiple ConvNet layer features will result in more complex feature space with some features being repetitive. This requires some form of feature selection. We use AdaBoost with single stumps to implicitly select only distinct features that are useful towards classification from concatenated ConvNet features. Experimental results show that using multiple ConvNet layer activation features instead of single ConvNet layer features consistently will produce superior performance. Improvements becomes significant as we increase the distance between source task and the target task.

• Knowledge Management Research
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• v.20 no.3
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• pp.119-137
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• 2019

With the recent spread of digital content, more people have been watching the digital content of TV programs on their PCs or mobile devices, rather than on TVs. With the change in such media use pattern, genres(types) of broadcast programs change in the flow of the times and viewers' trends. The programs that were broadcast on TVs have been released in digital content, and thereby people watching such content change their perception. For this reason, it is necessary to newly and differently classify genres(types) of broadcast programs on the basis of digital content, from the conventional classification of program genres(types) in broadcasting companies or relevant industries. Therefore, this study suggests a plan for newly classifying broadcast programs through using machine learning with the log data of people watching the programs in online media and for applying the new classification. This study is academically meaningful in the point that it analyzes and classifies program types on the basis of digital content. In addition, it is meaningful in the point that it makes use of the program classification algorithm developed in relevant industries, and especially suggests the strategy and plan for applying it.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.97-104
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• 2021

The authors provide characteristics of the open educational platforms, classification and quantitative analysis regarding the availability of IT courses, teaching language, thematic directions on the following platforms: Coursera, EdX, Udemy, MIT Open Course Ware, OpenLearn, Intuit, Prometheus, UoPeople, Open Learning Initiative, Open University of Maidan (OUM). The quantitative analysis results are structured and visualized by tables and diagrams. The authors propose to use open educational resources (teaching, learning or research materials that are in the public domain or released with an intellectual property license that allows free use, adaptation, and distribution) for organization of independent work; for organization of distance or correspondence training; for professional development of teachers; for possibility and expediency of author's methods dissemination in the development of their own courses and promoting them on open platforms. Post-project activities are considered in comparing the courses content of one thematic direction, as well as studying the experience of their attending on different platforms.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.13-18
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• 2022

In the post-information era, most of technologies have a visual part, or at least some functions related to visualization. It is also one of the popular means of presenting materials in education area. However, despite its popularity, the impact of visualization on the effectiveness of learning still remains controversial. Even more controversial is its usefulness in developing creativity, which is one of the most important skills for today's employee. The authors considered the use of visualization as a tool for the development of children's creativity on the example of learning video games, in particular, ClassCraft to distinguish features that, from the point of view of psychology, may lead to developing creativity even being not useful for educational purposes. It is concluded that video games useful for learning may have features, that are inappropriate in formal educational context, but important to develop creative thinking.

• Educational Technology International
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• v.13 no.1
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• pp.27-48
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• 2012

In this paper we are comparing how the OER (open educational resources) are developed in Higher Education in Finland and South Korea. We also present a comparison model for further studies. Essential findings based on our comparison are that in both countries there are many best practices of use of the OER and open learning. Open educational resources have great potential and their use can ensure quality teaching and learning. The activity has not inspired the great mass of higher education teachers in Finland and Korea. Traditionally, a teacher's job is working alone, and so a new operational culture is required. Our comparison indicates that numerous questions, fears and problems and cultural differences are also related to the thematic. There is an evident need for a new kind of strategic leadership, a new kind of teaching and learning culture and a doing together and production ideology for the method to spread. Based on our study the following interlinked elements of OER seem to be pivotal: changes to pedagogies, technology and operational culture; educational policy intention; and attitude to culture. Lastly, comparison frame by OER practice model is developed.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.343-351
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• 2008

By supervised learning with p predictors, we frequently obtain a prediction function of the form $y\;=\;f(x_1,...,x_p)$. When $p\;{\geq}\;3$, it is not easy to understand the inner structure of f, except for the case the function is formulated as additive. In this study, we propose to use p simple graphs for visual understanding of complex prediction functions produced by several supervised learning engines such as LOESS, neural networks, support vector machines and random forests.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.153-159
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• 2018

The purpose of this study is to grasp the internet use time that young people use for purposes other than learning purpose, to grasp the perceived status of the youth according to internet use time and to grasp the interrelationships of them. Using the 2016 youth health behavior online survey, the odds ratios and 95% confidence intervals of perceived status according to internet use time were calculated by binary logistic regression analysis. The main results are as follows. In perceived health and perceived oral health the odds ratios of perceived who feel that they are perceived and unhealthy as the time spent using the Internet increased significantly compared to those who did not use the Internet for learning purposes. In the perceived body type, the odds ratio of being overweight increased significantly with longer internet use time. The odds ratios of perceived happiness were 1.19 times (CI = 1.10-1.30) higher than the perceived expectation of unhappiness when using the Internet for over 300 minutes. The use of the internet for a long time other than the purpose of learning may have a negative effect on the health and happiness of the youth, so we think that the recommended time for using the internet is necessary.

• 전자공학회논문지 IE
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• v.45 no.1
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• pp.50-57
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• 2008

It is applying the various teaming contents to improve learner's studying desire and effect in E-Learning system. In this learning contents, there are text animation, sound and picture etc. But, multimedia teaming contents which has big file size need much transmission service times. In this paper, I proposed a scheduling technique of LMS to be faster and service efficiently the multimedia learning contents which was managed and processed it in LMS. for this purpose, I used message and scheduler at LMS. While loaming was processed, it saved the result information of learning contents request to LMS. In this case, if the learner request loaming contents request, it could be possible to support the learning contents efficiently to use learning contents information in LMS without connecting to LCMS. As application result of this techniques, at the first learning course, existent techniques displayed faster learning contents service than proposal techniques. But the more learning process, proposal technique is faster service than existent.

• Journal of Korean Institute of Industrial Engineers
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• v.2 no.1
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• pp.45-60
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• 1976

In this study, Multiple Factor Analysis was undertaken for the purpose of substituting General Vocational Aptitude tester for paper tests according to the standardized and partially modified norm, and compared and analyzed these aptitude tests YK Type Working Character test for a test battery. In this analysis, four basis aptitude cluster of AQE was utilized as aptitude cluster, the study for skill was carried out by the method of sampling electronic aptitude cluster in four basis ones, and the parts needed in the process of its analysis were investigated by means of Video-Tape Recording. This paper was performed with sample test by application of the inverse variation curve from learning theory and induced learning rate as a measure of the degree of proficient of technicians, and from the obtained results illustrated optimum newly-production plan of ability program and load program by the use of computer program.