• Journal of Science Education
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• v.39 no.1
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• pp.15-27
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• 2015

This study investigated whether there was a difference of the change in perspective of the nature of science depending on subjects of the history of science, after designing for two kinds of topics of role play programs based on the history of science to be transformed into a modern perspective. Before the history of science-role plays, the degree of the modern perspective was statistically no difference between group I(the atomic model transition-role play) and group II(the Mendeleev's periodic table-role play). However after treatment of the history of science-role plays for the each group, the degree of group I was higher than the degree of group II in the modern perspective. The results of this study indicate that the degree of changes into modern perspective of the nature of science by performing a history of science-role play may be depend on the subject of the history of science combined with the role play, and suggest the possibility that may be more effective to change the nature of science into the modern perspective, in case of performing of role play based on the history of science that includes the scientific knowledge established by a number of scientists with time series.

• Journal of The Korean Association of Information Education
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• v.8 no.3
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• pp.293-303
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• 2004

To follow in change and the development which circumference environment of education are quick even from scene of education students form the structure of knowledge themselves, the place where own lead studying of personal small group studying is emphasized, here upon specialist learning activity there is a wild possibility in the model which is suitable. But, studying of the learning paper was most center mainly the specialist learning activity of existing, it solves a learning problem at unit hour to, the hour was too insufficient to solve and it became plentifully at block time. But, this is to the curriculum operation and or the schedule operation it is when trying to consider the intensive degree of learning the elementary student, a problem point there is. It grasps the strong point and a weak point of specialist learning activity model of existing from the research which consequently, it sees and it applies more efficiently from web base study to establish the instructional strategy for, it composed the modules which strengthen the interaction of learning subject for. Also, unit macro learning and block time learning in order to do to become accomplished at web with studying problem, it will be able to solve inside unit hour in order, specialist teaching-learning system based on the web. It developed, after applied in the electrification S elementary school 5 grades which will reach the result, it analyzed.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.356-362
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• 2022

Research related to hydrogen technology is being actively conducted around the world. Korea is also making great efforts to develop technology to leap forward as a hydrogen economy powerhouse. In particular, the world's No. 1 hydrogen vehicle penetration rate is proof of this. However, the construction of hydrogen refueling stations is being delayed. The biggest delay factor is the public opposition. As such, policies without public support cannot be successfully implemented and are not sustainable. Therefore, this study intends to analyze the factors affecting the acceptability of hydrogen refueling stations in favor of and against them. As a research method, the basic factors affecting acceptability were identified by reviewing previous studies, and a questionnaire was designed and investigated based on the established factors. The validity and reliability of the questionnaire were verified, and the hypothesis was verified through correlation analysis. And, using structural equation modeling, a factor model was developed on the acceptability of hydrogen refueling stations. As a result of the study, acceptability defined private acceptability and public acceptability. In the case of private acceptability, it was confirmed that the higher the attitude toward the environment, the higher the level of knowledge about the hydrogen charging station, and the lower the degree of feeling the risk of the hydrogen charging station, the higher the acceptability. In the case of public acceptability, it was confirmed that the higher the benefit, the better the attitude toward the environment, and the lower the risk-taking characteristics of the individual, the higher the acceptability. Therefore, in this study, based on the potential factors verified in previous studies, the main factors affecting the acceptance on hydrogen refueling stations were identified. And the acceptance model was developed using structural equation modeling. This study is expected to provide basic data to seek ways to improve the acceptance of public when implementing national policies such as hydrogen refueling stations, and to be used analysis data for scientific communication.

• Knowledge Management Research
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• v.21 no.3
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• pp.249-269
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• 2020

Recently, as the online market has matured, it is facing many problems to prevent the growth. The most common problem is the homogenization of online products, which fails to increase the number of customers any more. Moreover, although the portion of the online market has increased significantly, it now becomes essential to expand offline for further development. In response, many online firms have recently sought to expand their businesses and marketing channels by securing offline spaces that can complement the limitations of online platforms, on top of their existing advantages of online channels. Based on their competitive advantage in terms of analyzing large volumes of customer data utilizing information technologies (e.g., big data and artificial intelligence), they are reinforcing their offline influence as well through this online for offline (O4O) business model. On the other hand, most of the existing research has primarily focused on online to offline (O2O) business model, and there is still a lack of research on O4O business models, which have been actively attempted in various industrial fields in recent years. Since a few of O4O-related studies have been conducted only in an experience marketing setting following a case study method, it is critical to conduct an empirical study on O4O selection attributes and their impact on customer satisfaction and loyalty. Therefore, focusing on China's representative O4O business model, 'Fresh Hema,' this study attempts to identify some key selection attributes specialized for O4O services from the customers' viewpoint and examine the impact of these attributes on customer satisfaction and loyalty. The results of the structural equation modeling (SEM) with 300 O4O (Fresh Hema) experienced customers, reveal that, out of seven O4O selection attributes, four (mobile app quality, mobile payment, product quality, and store facilities) have an impact on customer satisfaction, which also leads to customer loyalty (reuse intention, recommendation intention, and brand attachment). This study would help managers in an O4O area well adapt to rapidly changing customer needs and provide them with some guidelines for enhancing both customer satisfaction and loyalty by allocating more resources to more significant selection attributes, rather than less significant ones.

• Journal of the Korean Society of Radiology
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• v.12 no.2
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• pp.225-231
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• 2018

Recently, new teaching methods for communicating with teachers and students have been emerged according to the trends of decreasing the school-age population and the development of the mass media. We have applied teaching-learning model based on the flip learning to the college students in this work. As a result of the test for the customized flipped learning teaching-learning model in pre-class, the attendance rate of the major subject was 92.3% whereas that in liberal arts courses other than majors revealed 87.6%. This result for attendance rate shows that first year students in the radiology department have been actively participated in pre-class of the major subject than that of the liberal arts curriculum. From comparing the differences between the study group that was applied flipped learning in class and the non-applied group, the research group showed higher scores in knowledge, skills, and attitudes than the comparative group. In addition, more than 90% of the learners improved their responsibility, problem solving ability, creative thinking, cooperative ability, and communication ability through this learning program. From the test for the difference in the role of radiologists in the post class, the mean score was 4.40 for the group applied the teaching-learning model while that for non-applied group was 2.10. Hence, from such results, we see that this teaching-learning model is appropriate and needs to be extended to cultivate basic skills in radiology and relevant vocational education.

• Journal of the Korea Society for Simulation
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• v.21 no.1
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• pp.55-68
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• 2012

Recently it is important to understand service supply chain because the economy moves from manufacturing to services. However, most of existing supply chain research focuses exclusively on the manufacturing sector. To overcome this situation, it needs to investigate and analyze service supply chain. Simulation is one of the most frequently used techniques for analysis and design of complex system. Service supply chain is complex and large systems that require an accurate designing phase. Especially, it is important to examine closely the dynamically interactive behavior of the different service supply chain components in order to predict the performance of the servcie supply chain. In this paper, we develop a conceptual model of service supply chain. Then, we present a new procedure to develop simulation model for the developed conceptual model of service supply chain, based on the UML analysis and design tools and on the ARENA simulation language. The two main characteristics of the proposed procedure are the definition of a systematic procedure to design service supply chain and of a set of rules for the conceptual model translation in an ARENA simulation language. The goal is to improve the knowledge on service supply chain management and support the simulation model development efficiency on service supply chain.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.242-250
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• 2019

In this paper, we propose a method to predict the failure of industrial robot using Seq2Seq (Sequence to Sequence) model, which is a model for transforming time series data among Artificial Neural Network models. The proposed method uses the data of the joint current and angular value, which can be measured by the robot itself, without additional sensor for fault diagnosis. After preprocessing the measured data for the model to learn, the Seq2Seq model was trained to convert the current to angle. Abnormal degree for fault diagnosis uses RMSE (Root Mean Squared Error) during unit time between predicted angle and actual angle. The performance evaluation of the proposed method was performed using the test data measured under different conditions of normal and defective condition of the robot. When the Abnormal degree exceed the threshold, it was classified as a fault, and the accuracy of the fault diagnosis was 96.67% from the experiment. The proposed method has the merit that it can perform fault prediction without additional sensor, and it has been confirmed from the experiment that high diagnostic performance and efficiency are available without requiring deep expert knowledge of the robot.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.213-227
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• 2019

In this paper, we propose an end-to-end deep learning model combining Bayesian neural network with Korean speech recognition. In the past, Korean speech recognition was a complicated task due to the excessive parameters of many intermediate steps and needs for Korean expertise knowledge. Fortunately, Korean speech recognition becomes manageable with the aid of recent breakthroughs in "End-to-end" model. The end-to-end model decodes mel-frequency cepstral coefficients directly as text without any intermediate processes. Especially, Connectionist Temporal Classification loss and Attention based model are a kind of the end-to-end. In addition, we combine Bayesian neural network to implement the end-to-end model and obtain Monte Carlo estimates. Finally, we carry out our experiments on the "WorimalSam" online dictionary dataset. We obtain 4.58% Word Error Rate showing improved results compared to Google and Naver API.

• The Korean Journal of Franchise Management
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• v.13 no.3
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• pp.1-15
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• 2022

Purpose: In the restaurant sector, it has been known that consumers' positive perception of brands influences their positive WOM intention, and information sources play an important role in increasing credibility by enhancing consumer awareness and developing differentiated brands. This study examines the effects of information sources (e.g., advertisement, WOM, SNS) on trust (cognitive and affective) and, WOM and eWOM intention in the restaurant context. In the model, cognitive and affective trust play mediating roles in the relationships between information sources (e.g., advertisement, WOM, SNS) WOM and eWOM intention. Research design, data, and methodology: Research models and hypotheses were developed according to the research direction. The survey questionnaire items were developed and used appropriately according to the contents of this paper based on prior studies. All constructs were measured with multiple items developed and validated in prior studies. A total of 502 responses were collected from an online survey. The research model was evaluated using SmartPLS 4.0. Frequency analysis was performed to understand the demographic characteristics of the survey respondents. The reliability, convergent validity, and discriminant validity were assessed using measurement model analysis. The proposed model was verified using the structural equation model. Results: Advertisement, WOM, and SNS information sources all had a positive effect on affective trust, whereas only WOM had a significant effect on cognitive trust. In addition, affective trust had a positive effect on cognitive trust and eWOM intention but did not affect WOM intention. Finally, cognitive trust was found to have a positive effect on both WOM intention and eWOM intention. Conclusions: This study redefines the concept of where restaurant service companies should focus when providing consumers with information about their products and services. As a result, the conceptual framework of positive word of mouth intention to increase new customer visits to the restaurant brand has been expanded. In addition, this study not only presents an information source management strategy for restaurant brands, but also presents practical implications for resource allocation guidelines for customer management in the restaurant sector.

• Design Convergence Study
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• v.15 no.6
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• pp.195-214
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• 2016

Predictive analysis is based on a probabilistic learning algorithm called pattern recognition or machine learning. Therefore, if users want to extract more information from the data, they are required high statistical knowledge. In addition, it is difficult to find out data pattern and characteristics of the data. This study conducted statistical data analyses and visual data analyses to supplement prediction analysis's weakness. Through this study, we could find some implications that haven't been found in the previous studies. First, we could find data pattern when adjust data selection according as splitting criteria for the decision tree method. Second, we could find what type of data included in the final prediction model. We found some implications that haven't been found in the previous studies from the results of statistical and visual analyses. In statistical analysis we found relation among the multivariable and deducted prediction model to predict high box office performance. In visualization analysis we proposed visual analysis method with various interactive functions. Finally through this study we verified final prediction model and suggested analysis method extract variety of information from the data.