• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.67-78
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• 2017

Traffic congestion cost is increasing annually. Specifically congestion caused by the CDB traffic contains more than a half of the total congestion cost. Recent advancement in the field of Big Data, AI paved the way to industry revolution 4.0. And, these new technologies creates tremendous changes in the traffic information dissemination. Eventually, accurate and timely traffic information will give a positive impact on decreasing traffic congestion cost. This study, therefore, focused on developing both recurrent and non-recurrent congestion prediction models on urban roads by adopting Recurrent Neural Network(RNN), a tribe in machine learning. Two hidden layers with scaled conjugate gradient backpropagation algorithm were selected, and tested. Result of the analysis driven the authors to 25 meaningful links out of 33 total links that have appropriate mean square errors. Authors concluded that RNN model is a feasible model to predict congestion.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.87-94
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• 2014

Social media which includes Facebook enable users to construct relationships and networks as well as sharing of information. By enlisting Facebook users as proxy, this paper attempted to analyze the different emotional states experienced by social media users, specifically to gauge what effect their usage motivation and usage pattern had on the ambivalence level of the users. The quantitative survey result revealed that usage duration or the time of day when Facebook was accessed had no relevant impact on one's ambivalence level. However, there was a direct correlation between frequency of Facebook usage and the ambivalence level. The more the user logged onto Facebook the more suppressed his or her expression became due to fear of giving negative impressions to others and also receiving their negative feedbacks, which then subsequently added to the user's ambivalence. People's main reasons for using Facebook were identified as "chatting," "communicating," "maintaining relationships," "relationship building," "networking," and "finding information about friends," but only "maintaining relationships," "communicating," and "networking" had observable effect on ambivalence. There were no noticeable differences among genders with regards to ambivalence and usage levels, but there was a marked difference based on the user's age. For example, people in their forties showed higher levels of ambivalence than those in their twenties. This may be attributed to anxiety they face as they use Facebook primarily to expand their networks and to maintain relationships. As such, it is surmised that their fatigue level from using social media will only increase. Meanwhile, Korean Facebook user's emotional manifestation tended to skew toward relation-involved ambivalence rather than the self-defensive type. This relation-involved ambivalence might be something that can actually help prevent damage to relationships by limiting excessive emotional expressions. In other words, such ambivalence by Facebook users may be a positive element in a user's social media interaction.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.51-63
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• 2021

Identifying characters who appear in a story and analyzing their relationships is essential to understanding the story. This paper aims to identify the two actants (or character roles) as Helper and Opponent in Greimas's Actantial model by identifying Subject (i.e., protagonist) and analyzing the emotional interactions between the Subject and the two actants (Helper/Opponent). Our proposed method consists of three steps. First, we identify objects (i.e., characters) appearing in the text story. Next, we extract relational information through the interaction of the characters, and then classify emotions in the text expressed as relational information. Finally, we represent the flow of emotional relations among characters as a directed graph. The node with the highest degree is considered as the Subject because it includes the most relational information. The node that sends the most positive/negative emotions to the Subject is considered as the Helper/Oppenent, respectively. Our research contributes to the computer-based narrative understanding by providing a computational method that automatically extracts the three key character roles (Subject, Helper, and Opponent) from the text story.

• Journal of The Korean Association of Information Education
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• v.23 no.1
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• pp.73-84
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• 2019

Maker movement is emerging as one of the key areas of the fourth industrial revolution in recent years. The maker movement is to create and share what users need using a variety of inexpensive production tools such as open source software and hardware, 3D printers and laser cutters. We think that the effect would be enhanced if design thinking is applied to elementary and middle school (K-12) class. The purpose of this study is to develop a design thinking-based maker education program and to apply it to classroom for clarify the effect on the creative problem solving ability of elementary school students. In order to verify the purpose of the research, students in the 5th-6th grades of elementary school were divided into a controlled group and an experimental group. The general lecture maker class was applied in the controlled group, and our developed design thinking-based maker class was simultaneously applied in the experimental group. The creative problem solving ability test was conducted before and after the test, and its effectiveness was verified using statistical t-test. In conclusion, this study suggests that design thinking-based maker education program has a positive effect on elementary school students' creative problem solving ability.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.275-284
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• 2021

The study attempted to systematically and comprehensively analyze individual studies in which proprioceptive neuromuscular facilitation (PNF) was performed with chronic stroke patients. Selection criteria included type of participants (stroke patients), intervention (PNF), comparison (intervention group or non-intervention group), outcomes (effect on dynamic balance), and study design (randomized controlled trial). We searched seven literature databases, and selected 17 papers that met our selection criteria. For meta-analysis, effect size of each individual study was extracted using the R project for Statistical computing version 4.0.3. Rob 2.0 tool, developed by the Cochrane group, was used to evaluate the quality of each individual study. The overall effect size PNF with dynamic balance was 0.59 (95% CI=0.41-1.77), which was significantly different than the median effect size (p<0.05). The sub-group for dynamic balance was analyzed, for effect sizes of BBS (0.50), TUG (0.78), and FRT (0.51). Thus, PNF intervention has a positive impact on improve of dynamic balance by chronic stroke patients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.557-569
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• 2021

In preparation for the future society, the educational curriculum is changing according to the trend of the times, and with the advent of the era of the 4th Industrial Revolution, the purpose of the new 2015 revised curriculum was suggested to foster the convergence creativity of students. The purpose of software education is to promote creativity and further develop problem-solving skills in connection with real life. In addition, flow in learning leads to outstanding educational achievement. However, in elementary school computer education, there is still a lack of development of a convergence class model for students to easily immerse themselves and promote creative problem-solving skills. Therefore, in this study, we designed convergence computer education using Novel Engineering, which is a convergence class model suitable for these educational conditions and applied it to classes. Further, to measure the effect on the improvement of learning flow and creative problem-solving ability. the Novel Engineering-based computer class was applied to the experimental group for 6th graders, and the general computer class was applied to the control group. As a result of the pre-post test between groups, it was found that computer classes using Novel Engineering had a positive effect on learning flow and creative problem-solving ability.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.111-123
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• 2022

Artificial intelligence, which is developing as the core of an intelligent information society, is bringing convenience and positive life changes to humans. However, with the development of artificial intelligence, human rights and property are threatened, and ethical problems are increasing, so alternatives are needed accordingly. In this study, the most controversial artificial intelligence ethics problem in the dysfunction of artificial intelligence was aimed at researching and developing artificial intelligence ethical measurement indicators to protect human personality rights and property first under artificial intelligence ethical principles and components. In order to research and develop artificial intelligence ethics measurement indicators, various related literature, focus group interview(FGI), and Delphi surveys were conducted to derive 43 items of ethics measurement indicators. By survey and statistical analysis, 40 items of artificial intelligence ethics measurement indicators were confirmed and proposed through descriptive statistics analysis, reliability analysis, and correlation analysis for ethical measurement indicators. The proposed artificial intelligence ethics measurement indicators can be used for artificial intelligence design, development, education, authentication, operation, and standardization, and can contribute to the development of safe and reliable artificial intelligence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.171-179
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• 2021

This study was a meta-analysis of previous studies that subjected stroke patients to the whole-body vibration exercise, in an attempt to evaluate the effectiveness of such exercise in improving their balance and walking ability. The electronic databases used for literature search were the National Assembly Library, Korean Educational Academic Information (RISS), Korean Academic Information (KISS), and Nuri Media (DBPIA). We also investigated a prior study of the whole-body vibration exercise applied to stroke patients from January 2010 to August 2020. In assessing the quality of the study, the RCT (randomized controls trials) study used the risk of bias 2 (RoB2) tool developed by the Cochrane group. Meta-analysis was performed using R software for statistical computing version 4.0.3. The results of the study confirmed that the overall effect size was 0.40, and the whole-body vibration exercise used had a moderate effect on the balance and gait of stroke patients, the effect size of balance was 0.44, and the effect size of gait was 0.36, showing a positive effect. These results indicated that the whole-body vibration exercise is an effective intervention for stroke patients, and further research is needed.

• Journal of The Korea Institute of Healthcare Architecture
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• v.28 no.4
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• pp.41-50
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• 2022

Purpose: This study aims to suggest an analysis model finding the relationship between building scale characteristics of Public-use facilities and infectious disease outbreaks around senior leisure welfare facilities and the features and their scopes where quarantine resources are to be concentrated. Methods: Reviewing previous studies found the user characteristics of senior leisure welfare facilities and scale characteristics of urban architectures. The data preprocessing was performed after collecting building data and infectious disease outbreak data in the analysis area. This study derived data for attributes of building size and frequency of infectious disease outbreaks in Public-use facilities around senior leisure welfare facilities. A computing algorithm was implemented to analyze the correlation between the building size characteristics and the infectious disease outbreak frequency as per the change of the spatial scope. Results: The results of this study are as follows: First, the suggested model was to analyze the correlation between the infection frequency and the number of senior leisure welfare facilities, the number of Public-use facilities, building area, total floor area, site area, height, building-to-land ratio, and floor area ratio varied as per the change of spatial scope. Second, correlation results varied between the infection frequency and the number of senior leisure welfare facilities, the number of Public-use facilities, building area, total floor area, site area, height, building-to-land ratio, and floor area ratio. Third, a negative correlation appeared in the analysis between the number of senior leisure welfare facilities and infection frequency. And positive correlations appeared noticeably in the study between the number of Public-use facilities, building area, total floor area, height, building-to-land ratio, and floor area ratio. Implications: This study can be used as primary data on the utilization of limited quarantine resources by analyzing the relationship between the Public-use facilities around the senior leisure welfare facilities and the spread of infectious diseases. In addition, it suggests that infectious disease prevention measures are necessary considering the spatial scope of the analysis area and the size of buildings.