• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3023-3032
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• 1997

This study examined individual differences in navigating in hyperspace learning environment where a minimum structure is provided. Using a hypercard stack called "Pearl Harbor", Field Dependent people used guidance more often than those in Field Indepedent; FI achieved scored higher at the end of the study; and FI people had some type of pattern showing from them audit trail when FD people did not show any trail of patterns. Also people with higher visual thinking scores achieved higher scores in hyperspace environment.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.29-35
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• 2019

In this paper, the effects of educational contents on job behavior, the effects of job behavior on job effectiveness and the effects of educational contents on job effectiveness were studied when working in the Software field. For this purpose, a questionnaire survey was conducted on the learning workers who conducted the training in the IT field, and 302 valid questionnaires were used for the analysis. The research model was set up to test exploratory factor and confirmatory factor analysis and hypothesis, and the research hypothesis was tested by applying structural equation. The effects of job behavior on job effectiveness were positively related to job satisfaction, customer orientation, and organizational commitment.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.92-97
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• 2022

Plastics are classified into 7 types such as PET (PETE), HDPE, PVC, LDPE, PP, PS, and Other for separation and recycling. Recently, large corporations advocating ESG management are replacing them with bioplastics. Incineration and landfill of disposal of plastic waste are responsible for air pollution and destruction of the ecosystem. Because it is not easy to accurately classify plastic materials with the naked eye, automated system-based screening studies using various sensor technologies and AI-based software technologies have been conducted. In this paper, NIR scanning devices considering the NIR wavelength characteristics that appear differently for each plastic material and a system that can identify the type of plastic by learning the NIR spectrum data collected through it. The accuracy of plastic material identification was evaluated through a decision tree-based SVM model for multiclass classification on NIR spectral datasets for 8 types of plastic samples including biodegradable plastic.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.37-47
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• 2021

In this paper, we propose a new deep learning model for tongue segmentation with improved accuracy compared to the existing model by diversifying the receptive field in the U-net. Methods such as parallel convolution, dilated convolution, and constant channel increase were used to diversify the receptive field. For the proposed deep learning model, a tongue region segmentation experiment was performed on two test datasets. The training image and the test image are similar in TestSet1 and they are not in TestSet2. Experimental results show that segmentation performance improved as the receptive field was diversified. The mIoU value of the proposed method was 98.14% for TestSet1 and 91.90% for TestSet2 which was higher than the result of existing models such as U-net, DeepTongue, and TongueNet.

• Journal of Multimedia Information System
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• v.4 no.3
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• pp.115-122
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• 2017

Over the years, there has been much research in blended learning. However, research regarding its use and evaluation is inconsistent, not following any specific evaluation method, and may not be applicable to local students. In this research, a case study was conducted to evaluate the environment based on three levels of Kirkpatrick's model. Methodological triangulation was the principle of data collection used in which multiple sources of evidence were triangulated to provide insights into this study. Instruments used include surveys, interviews, questionnaires and pre- and post-tests that are guided by Kirkpatrick's model. The results revealed that students were positive with the learning environment. Students enjoyed learning with multimedia and motivated to learn as well as engaged in the environment. The tests showed significant difference in their learning. Students also perceived that they have transferred their learning from face-to-face lecture into problem-based learning and learning outcome. This research contributes to the field by providing deeper insights into assessments in multimedia-based blended learning environment and empirical evidence on views, attitudes, learning and knowledge transfer of students in higher education.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1195-1202
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• 2018

Artificial neural network is widely used for its excellent performance and implementability. However, traditional neural network needs to learn the system from scratch, with the addition of new input data, the variation of the observation environment, or the change in the form of input/output data. To resolve such a problem, the technique of transfer learning has been proposed. Transfer learning constructs a newly developed target system partially updating existing system and hence provides much more efficient learning process. Until now, transfer learning is mainly studied in the field of image processing and is not yet widely employed in acoustic data processing. In this paper, focusing on the scalability of transfer learning, we apply the concept of transfer learning to the problem of guitar chord classification and evaluate its performance. For this purpose, we build a target system of convolutional neutral network (CNN) based 48 guitar chords classification system by applying the concept of transfer learning to a source system of CNN based 24 guitar chords classification system. We show that the system with transfer learning has performance similar to that of conventional system, but it requires only half the learning time.

• International Journal of Contents
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• v.4 no.1
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• pp.20-25
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• 2008

The development of communication technology and the spread of computers and internet have affected to the field of education. In this paper, we design a learning process with LAMS to make the new education environment which is required in an information age. We made the learning environment with LAMS which develops the learner's algorithmic thinking faculty on some sorting algorithm, especially such as selection sort, bubble sort and insertion sort algorithm. In addition, we analyse the effectiveness of the learning environment. The designed contents were applied to elementary school students' learning and a questionnaire survey was conducted after a learning course. The research of the questionnaire shows that the learning system using LAMS motivates a learner for learning and provides a convenient learning environment.

• Journal of Engineering Education Research
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• v.19 no.2
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• pp.76-82
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• 2016

The purpose of this study is to identify core elements required of instruction consulting and to develop a systematic consulting procedure for successful Flipped Learning. The main contents of this study to achieve its purpose are as follows. First, core elements required of consulting are deduced by analyzing cases of instruction implemented with Flipped Learning. Second, consulting procedure is constructed based on core consulting elements of Flipped Learning. Based on the study results, the 3P process is suggested as the elements and procedure of instruction consulting for Flipped Learning. The 3P process has the following characteristics. The first stage Preparation involves guiding students to have an objective viewpoint about the lesson beginning with building a relationship with the instructor. Also, a lesson plan and source materials for lesson are selected and developed. The second stage Performance involves implementing lesson coaching oriented towards cooperative problem-solving to find better direction. The last stage Post-review involves introspection necessary for continuous quality improvement of lessons. The validity of the instruction consulting elements for Flipped Learning applied to deduce the aforementioned results has been verified after specialist review and field application.

• Journal of Agricultural Extension & Community Development
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• v.23 no.3
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• pp.233-242
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• 2016

This study aimed to analyze educational satisfaction and the relationship between learning transfer and learning persistence shown after actual education targeting students who participated in the agricultural education and training. Conclusions based on the study results can be suggested as follows. First, of the factors related to learning persistence, satisfaction of educational contents turned out to be a statistically significant factor with a positive effect in the agricultural education and training. Students participating in the agricultural education and training have a conspicuous object to learn for improving ability which is necessary for and applicable to agriculture. Second, of the three factors related to learning transfer in the agricultural education and training, satisfaction of educational contents, educational facilities and satisfaction of environment turned out to have a positive effect. Third, results show that satisfaction of instructors does not affect both learning persistence and learning transfer. Lastly, in case of education and training for field practice, this study is suggesting the necessity of research by accessing in a concrete and detailed manner such as learning contents, instructors, educational facilities and satisfaction of environment from the comprehensive concept of educational satisfaction in the directivity of study related to satisfaction.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.770-802
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• 2022

With the development of deep learning techniques, text mining is producing breakthrough performance improvements, promising future applications, and practical use cases across many fields. Likewise, even though several attempts have been made in the field of financial information, few cases apply the current technological trends. Recently, companies and government agencies have attempted to conduct research and apply text mining in the field of financial information. First, in this study, we investigate various works using text mining to show what studies have been conducted in the financial sector. Second, to broaden the view of financial application, we provide a description of several text mining techniques that can be used in the field of financial information and summarize various paradigms in which these technologies can be applied. Third, we also provide practical cases for applying the latest text mining techniques in the field of financial information to provide more tangible guidance for those who will use text mining techniques in finance. Lastly, we propose potential future research topics in the field of financial information and present the research methods and utilization plans. This study can motivate researchers studying financial issues to use text mining techniques to gain new insights and improve their work from the rich information hidden in text data.