• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• Journal of Ginseng Research
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• v.44 no.3
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• pp.442-452
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• 2020

Backgroud: Sleep deprivation (SD) impairs learning and memory by inhibiting hippocampal functioning at molecular and cellular levels. Abnormal autophagy and apoptosis are closely associated with neurodegeneration in the central nervous system. This study is aimed to explore the alleviative effect and the underlying molecular mechanism of stem-leaf saponins of Panax notoginseng (SLSP) on the abnormal neuronal autophagy and apoptosis in hippocampus of mice with impaired learning and memory induced by SD. Methods: Mouse spatial learning and memory were assessed by Morris water maze test. Neuronal morphological changes were observed by Nissl staining. Autophagosome formation was examined by transmission electron microscopy, immunofluorescent staining, acridine orange staining, and transient transfection of the tf-LC3 plasmid. Apoptotic event was analyzed by flow cytometry after PI/annexin V staining. The expression or activation of autophagy and apoptosis-related proteins were detected by Western blotting assay. Results: SLSP was shown to improve the spatial learning and memory of mice after SD for 48 h, accomanied with restrained excessive autophage and apoptosis, whereas enhanced activation of phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin signaling pathway in hippocampal neurons. Meanwhile, it improved the aberrant autophagy and apoptosis induced by rapamycin and re-activated phosphoinositide 3-kinase/Akt/mammalian target of rapamycin signaling transduction in HT-22 cells, a hippocampal neuronal cell line. Conclusion: SLSP could alleviate cognitive impairment induced by SD, which was achieved probably through suppressing the abnormal autophagy and apoptosis of hippocampal neurons. The findings may contribute to the clinical application of SLSP in the prevention or therapy of neurological disorders associated with SD.

• 대한공업교육학회지
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• v.38 no.1
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• pp.163-194
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• 2013

This study aims at giving examples that can be applied in the real education field, and it develops theme-based integrative education program for Industrial Specialized high school students. It analyzed the models of many scholars about the development of education course, and devised developmental models and procedures of the theme-based integrative education program of engineering specialized high school from those. As a result, it used and reorganized ADDIE model which is the systematic education course development model and the theme-based integrative education development model of Frazee and Rudnitski(1995) as the basic structure, and came to devise theme-based integrative education program of engineering specialized high school while referring to creative engineering design education program development model by Lee Chang-hoon. This study that is theme-based integrative education program for engineering-specialized high school students and is the result of this study has the following characters. First, This theme-based integrative education program that is developed for engineering-specialized high school students can be applied and the initial example that approach the Theme-Based. Second, This Education Program included the Activity project that is "Making Maglev" for the third grade at the engineering-specialized high school and One of the Program's aim is to bring up their attitude that engaged to in the class having the Interest. Third, Theme-based integrative education program for engineering-specialized high school is composed the workbook for the students and the teaching guidance plan for the teachers. Workbook for the students is composed four Units;"Brief about the Maglev","Basic principles about the Maglev","Intensive principles about the Maglev", Activity project about the Maglev". And each unit is made by Learning Purpose, Introducing, Learning Contents(Deepen Learning, Reading Magazines), Assesment etc. Teaching guidance plan for the teachers include that Summary, Purpose, Time Planing & Streaming Map for the class, contents associated Maglev, prerequisite learning, constructure of the education program, flow chart, learning activity, assesment(self-appraiser and peer review).

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.48-63
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• 2024

This study aims to develop a class procedure for the application of classrooms that value context and to conduct science classes using this procedure to examine the effects. Among various contexts related to scientific knowledge, the study develops a teaching procedure for designing classes that focus on the contexts of discovery and real life. After verifying the content validity of the context-based design and the program to which it was applied, a class was conducted, and the responses of the children were checked. The final draft of the lesson design completed after revision and supplementation is as follows: context-based design was presented in four stages, namely, presenting, exploring the context, adapting the context, and organizing (share and synthesizing; PEAS). The goal is to enable people to experience the overall flow of scientific knowledge instead of focusing on the acquisition of fragmentary knowledge by covering a wide range of topics from the social and historical contexts in which scientific knowledge was created to its use in real life. To aid in understanding the newly proposed class procedure and verifying its effectiveness, we developed a program by selecting the "My Fun Exploration," 2. Biology and Environment unit of the second semester of the fifth grade. The result indicated that the elementary science program that applied the context-centered design effectively improved the self-directed learning ability of students. In addition, the effect was especially notable in terms of intrinsic motivation. As the students experienced the contexts of discovery and real life related to scientific knowledge, they developed the desire to actively participate in science learning. As this becomes an essential condition for deriving active learning effects, a virtuous cycle in which meaningful learning can occur has been created. Based on the implications, developing programs that apply context-based design to various areas and contents will be possible.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.453-462
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• 2005

Recently, due to technical improvements of storage devices and networks, the amount of data increase rapidly. In addition, it is required to find the knowledge embedded in a data stream as fast as possible. Huge data in a data stream are created continuously and changed fast. Various algorithms for finding frequent itemsets in a data stream are actively proposed. Current researches do not offer appropriate method to find frequent itemsets in which flow of time is reflected but provide only frequent items using total aggregation values. In this paper we proposes a novel algorithm for finding the relative frequent itemsets according to the time in a data stream. We also propose the method to save frequent items and sub-frequent items in order to take limited memory into account and the method to update time variant frequent items. The performance of the proposed method is analyzed through a series of experiments. The proposed method can search both frequent itemsets and relative frequent itemsets only using the action patterns of the students at each time slot. Thus, our method can enhance the effectiveness of learning and make the best plan for individual learning.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.240-250
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• 2020

This study explores the process of transitional career choice for North Korean defectors who are successfully living their lives after transition to a different system labor market. To achieve this study purpose, what is the process of transitional career choice for North Korean defectors due to the system transition? At present, he (Ed- who is he?) has a subjective sense of success in his professional life and conducted in depth interviews with three men and eight women as objects that can explain the process of experience in rich and detailed ways. To this end, the author interviewed three men and eight women who are satisfied with their current job and analyzed them with the grounded theory method proposed by Strauss & Corbin (1998). As a result, the paradigm model was derived from the central phenomenon of 'conversion of perspective', and the core category was 'conversion of perspective and challenge new career'. The transitional career choice process was derived into four stages according to the flow of time and interaction as 'reality recognition stage', 'active change recognition stage', 'support and coping strategy stage', and 'growth stage' and positive reflections from transitional learning and potential factors of planned chance skills were found.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.419-431
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• 2018

In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.

• Journal of The Korean Association For Science Education
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• v.31 no.2
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• pp.210-224
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• 2011

The purpose of this study is to analyze students' recognition of the free inquiry activity and to investigate what effect the free inquiry activity of the 2007 Revised Educational curriculum revision has on the science inquiry ability of middle school students. To conduct the research we worked with 262 female students, 8 classes of first graders in a middle school. Among them, 4 classes were taught in free inquiry activity and the remaining 4 classes were taught in the traditional way. The results of Likert-questionnaire indicate that students were learning about cooperative spirit through group investigation activities and discussions and did not take the free inquiry activity as a hard activity. Also they showed positive reaction agreeing that this activity is both a helpful method in learning science and interesting. However, it seemed that the investigation tends to flow between the leading 1~2 members of the group and showed difficulty in carrying out the investigation as a group after school hours. It showed there are few problems and obstacles in operating the free inquiry activity. The free inquiry activity did not give any meaningful influence on the improvement of science inquiry ability of students. Integrative inquiry process skills did not give a relevant influence, however, it showed a meaningful influence on the improvement of basic inquiry process skills. Especially, among the low-ranking element of basic inquiry process skills, it enhanced the capacity for prediction.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.431-440
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• 2018

In this study, authors predicted probability of resignation of newly employed nurses using TensorFlow, an open source software library for numerical computation and machine learning developed by Google, and suggested strategic human resources management plan. Data of 1,018 nurses who resigned between 2010 and 2017 in single university hospital were collected. After the order of data were randomly shuffled, 80% of total data were used for machine leaning and the remaining data were used for testing purpose. We utilized multiple neural network with one input layer, one output layer and 3 hidden layers. The machine-learning algorithm correctly predicted for 88.7% of resignation of nursing staff with in one year of employment and 79.8% of that within 3 years of employment. Most of resigned nurses were in their late 20s and 30s. Leading causes of resignation were marriage, childbirth, childcare and personal affairs. However, the most common cause of resignation of nursing staff with in one year of employment were maladaptation to the work and problems in interpersonal relationship.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.414-423
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• 2020

In this paper, we propose a Dilated Convolution Gate Linear Unit (DCGLU) to mitigate the lack of sparsity and small receptive field problems caused by the segmentation map extraction process in sound event detection with weak labels. In the advent of deep learning framework, segmentation map extraction approaches have shown improved performance in noisy environments. However, these methods are forced to maintain the size of the feature map to extract the segmentation map as the model would be constructed without a pooling operation. As a result, the performance of these methods is deteriorated with a lack of sparsity and a small receptive field. To mitigate these problems, we utilize GLU to control the flow of information and Dilated Convolutional Neural Networks (DCNNs) to increase the receptive field without additional learning parameters. For the performance evaluation, we employ a URBAN-SED and self-organized bird sound dataset. The relevant experiments show that our proposed DCGLU model outperforms over other baselines. In particular, our method is shown to exhibit robustness against nature sound noises with three Signal to Noise Ratio (SNR) levels (20 dB, 10 dB and 0 dB).