• Journal of Korean Elementary Science Education
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• v.27 no.2
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• pp.117-133
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• 2008

The purpose of this study was to investigate the elementary students' views about lab-based science learning. For the purpose of this study, semi-structured interviews were conducted with thirty sixth grade students in 12 classes from two elementary schools located in Daegu City. The interview contents consisted of three major categories. The first category was related to attitude toward science lab, the second was related to lab-based science learning which had four sub-categories; recognizing lesson object, planning experiment, performing experiment, drawing conclusion in lab-based science learning in which the students had ordinary have views and expectations, and the last category was related to students' difficulties and something need to be improved in lab-based science learning. In-depth interviews were performed individually and the interviews were recorded. From the interviews, we found that students, in first category, do like lab-activities more than lectures or instruction-based activities in textbook. Students, in second category, wanted generally more discussion for their own activities rather than teacher's instruction and they wanted teacher' mediation conflicts within small groups and comments for students' experiment results. In the last, most of students had fears for some dangerous reagents and accidents. Based on the results, the study suggested that teacher need to give their students to autonomous discussion opportunities to design and interpret data through teacher' guided questions in inquiry steps, to produce some intimate atmosphere for active interaction in small groups, and to teach the safety education on some dangerous reagents.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.139-155
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• 2012

A fundamental concepts of business environment changes and the importance of stakeholder's value creation is changing in the business. This study ISO9004: 2009 quality management system of Category 5: Strategy and Policy, Category 10: improvement, innovation and learning (Note) SBK target was to develop a model that is the company's sustained success. Three concepts of the new revision of ISO9004" in response to environmental changes," "learning", "innovation" (Note) SBK applied to the project settings and talent establish long-term vision was to establish the process as the organization's learning content was TDR for the creation of exceptional and innovative programs were introduced. As a result, (Note) SBK three years of continuous business performance indicator has grown dramatically to more than 50% continued success is going to create business models. But 100 years to accomplish the vision, ISO9004 model needs to extends the entire category as a management system to achieve the optimization needed.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.286-294
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• 2023

We studied learners' perceptions and learning styles of project research activities in the chemical field conducted by 54 science high school students. In a survey of students' perceptions of task research, positive responses were found in "internal motivation," "cooperation," "task solving," and "tenacity and immersion," and statistically significant differences were found in "self-directedness," "cooperation," and "tenacity and immersion" by year. The 'lower' group responded most positively in the 'cooperation' category, and the 'higher' group responded most positively in the 'task solving' category. As a result of investigating the learning styles of the students who conducted the task research, it was found in the order of assimilator, converger, accommodator, and diverger. The assimilators showed the characteristic of systematically and scientifically approaching the problem. Convergers were found to have excellent problem-solving and decision-making ability, are practical, and have experimental-based thinking characteristics. In this study, the characteristics of science high school students showed well in the results of the learning style performed.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.23-31
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• 2019

Deep learning is a hot topic in both academic and industrial fields. Deep learning applications can be categorized into two areas. The first category involves applications such as Google Alpha Go using interfaces with human operators to run complicated inference engines in high-performance servers. The second category includes embedded applications for mobile Internet-of-Things devices, automotive vehicles, etc. Owing to the characteristics of the deployment environment, applications in the second category should be bounded by certain H/W and S/W restrictions depending on their running environment. For example, image recognition in an autonomous vehicle requires low latency, while that on a mobile device requires low power consumption. In this paper, we describe issues faced by embedded applications and review popular inference engines. We also introduce a project that is being development to satisfy the H/W and S/W requirements.

• Journal of The Korean Association of Information Education
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• v.13 no.1
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• pp.77-84
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• 2009

Along with developments of information and communication technologies, internet has spread not only all over the society, but also our everyday life deeply. Also requirements for e-learning using internet in the educational aspect have a great influence on the changes of school educations. The benefits of e-learning are many, including cost-effectiveness, enhanced responsiveness to change, consistency, and timely contents. Therefore, the e-learning has been introduced to the universities. However, the e-learning is operated inefficiently because of introduction to the university with no definite idea about effects of education and economy in the university. Therefore, in this paper we analysed the category of e-learning based the curriculum operation forms in the university, surveyed tests about students preference and the studied what is desirable e-learning operation forms.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Archives of design research
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• v.15 no.3
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• pp.115-126
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• 2002

The occupational execution technique and the ability of people has been changed along with the change of thinking and the development of complicated social structure. The needs of learner's self-controlled learning system is arise to increase the occupational execution technique and adaptation in such a changing social environment. To meet these needs, we must develop systematic approach on the module-type educational material system. The purpose of this study lies on developing the module-type educational material system and its application in aspects of occupational execution ability. Based on the job analysis of advertising design, 1 analyze the learning ability for the occupational execution and abstract knowledge, function, attitude from each learning category of each learning ability. All these processes are the basis of developing the module-type educational material system. and the system will be appreciated in many other fields not only on advertising design.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.40-44
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• 2023

The defect detection based on deep learning requires minimal loss and high accuracy to pinpoint product defects. In this paper, we confirm the loss rate of deep learning training based on disc-shaped artificial scaffold images. It is intended to compare the performance of Cross-Entropy functions used in object detection algorithms. The model was constructed using normal, defective artificial scaffold images and category cross entropy and sparse category cross entropy. The data was repeatedly learned five times using each loss function. The average loss rate, average accuracy, final loss rate, and final accuracy according to the loss function were confirmed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.409-410
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• 2022

This paper proposes a fusion model based on Long-Short Term Memory networks (LSTM) and CNN deep learning methods, and applied to multi-category news datasets, and achieved good results. Experiments show that the fusion model based on deep learning has greatly improved the precision and accuracy of text sentiment classification. This method will become an important way to optimize the model and improve the performance of the model.