• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.307-320
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• 2019

This study explores how an elementary school homeroom teacher who continued to lecture, can use diversified science teaching methods for learner-centered instruction. Using an auto-ethnographic approach over the course of a year, self-memory data, facebook diaries, class diaries, and interview data of an elementary teacher's day-to-day preparations and practice of elementary science, in the context of a Korean elementary school, were collected. The data was analyzed through cultural historical activity theory, examining how the interplay of key elements (i.e., the subject as a homeroom teacher with instructional expertise, norms, community, division of labor, tools, and goals) was characterized within and across distinct two-activity systems, and how these elements shaped the teacher's teaching methods into either lecture format or diversified teaching. The study revealed that a non-cooperative community, lack of division of labor, and norms that neglect preparation for science class were the elements that perpetuated the lecture format, and that a contradiction between goals and tools occurred in the activity system. However, these elements were able to be transformed into a cooperative community, shared labor, and norms that saved preparation time for both science class and diversified teaching methods, and those changed elements facilitated the teacher in using diversified teaching methods (e.g., experiments, subject-integrated classes, field work), thereby mitigating the contradiction. This study also discusses that diversified teaching methods can be facilitated when dealing with norms, community, and division of labor elements in an elementary school context as well as improving individual teachers' instructional expertise.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.2
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• pp.99-107
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• 2020

Fibromyalgia is a disorder characterized by the core symptom of chronic widespread pain, along with fatigue, sleep disturbances, mood changes, and cognitive difficulties. The etiology of fibromyalgia involves a combination of biological factors, such as genetic vulnerability, alterations in pain processing and stress response system ; psychological factors, such as anxiety, depression, anger, and perceived stress ; environmental factors, such as infections, febrile diseases, and trauma. Central sensitization, which is amplified in the process of sensory stimulation, has been emphasized as a key etiological factor, as supported by enhanced wind-up, delayed aftersensation, decreased nociceptive flexion reflex threshold and functional imaging studies. Several guidelines recommend that a multimodal approach be used to treat fibromyalgia, including both pharmacological and non-pharmacological treatments, tailored to each individual, and that clinicians should provide an intellectual framework through sufficient education and emphasis on the importance of self-management. The prevalence of mood disorders, anxiety disorders, and other psychiatric problems is 7-9 times higher in patients with fibromyalgia than in the general population ; moreover, the association between fibromyalgia and certain psychopathologies or sleep problems has also been suggested. Since psychiatric problems, with shared vulnerabilities and risk factors, interact with fibromyalgia bidirectionally and also affect the disease course, an integrated management approach is needed to determine the risk of comorbidities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.667-675
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• 2021

The purpose of this study is as follows: First, to analyze the spatial structure of Jeju by analyzing the rate of parking demand and supply; Second, to determine the parking service imbalance between regions; and third, to elucidate the causes of this spatial structural parking service imbalance and provide effective measures. Due to the rapid population and tourism growth, Jeju is suffering from traffic congestion and serious parking problems. For this, the ways to efficiently utilize the existing parking spaces were identified through spatial structure analysis based on the parking demand and supply in the Jeju area. As short-term policy, the following changes were proposed: switching to small-scale eup or myeon blocks of parking space, use of shared parking system, and repairing side streets in residential areas. As mid-to-long-term policy, it is linked to other means of transportation as follows: parking demand management policy through modal share by reorganizing public transportation routes or expanding traffic facilities; securing park-and-ride lots; and different parking pricing for different time periods. To implement these policies, each area of the public sector, private sector, and private-public partnership should develop the bond of sympathy by areas and participants.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.217-226
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• 2021

The use of personal mobility(PM) is increasing because of preading shared mobility, but, it causes risk of accidents and fear to pedestrians because of lack of sound. The purpose of this study is to find out the effects of the alert sound in PM and driving direction on risk perception of pedestrians, awareness on PM driver, and allowance for driving on each road. The 8 videos were produced from a pedestrian perspective, depending on the alert sound type(silent, vess, bell, voice) and direction of driving(front, back). After watching each video, participants completed surveys. There was a non-effect on the driving direction. Regardless of the alert sound type, all of the sounds reduced the risk perception. Also, the awareness of PM drivers and allowance for driving on each road were positive. This study found that PM needed an alert sound for pedestrian safety. We expect the results of the study to help improve awareness of PM and make policies and regulations.

• Smart Media Journal
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• v.10 no.1
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• pp.88-98
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• 2021

As blockchain technology has emerged as a security issue for IoT, technology which integrates block chain into IoT is being studied. In this paper is a research concerning token-based IoT service access control technology for data sharing, which propose a possessor focused data sharing technic by using the permissioned blockchain. To share IoT health data, a Hyperledger Fabric Network consisting of three organizations was designed to provide a way to share data by applying different access control policies centered on device owners for different services. In the proposed system, the device owner issues access control tokens with different security levels applied to the participants in the organization, and the token issue information is shared through the distributed ledger of the HFN. In IoT, it is possible to lightweight the access control processing of IoT devices by granting tokens to service requesters who request access to data. Furthmore, by sharing token issuance information among network participants using HFN, the integrity of the token is guaranteed and all network participants can trust the token. The device owners can trust that their data is being used within their authorized rights, and control the collection and use of data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.325-333
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• 2021

With the rapidly changing era of the fourth industrial revolution, the utilization of IT technology is increasing. In addition, the demand for security authentication is increasing as shared services or IoT technologies are being developed as new business models. Security authentication is becoming increasingly important for all intelligent devices such as self-driving cars. However, most location-based security authentication technologies are being developed mainly with technologies that utilize server proximity or satellite location tracking, which limits the scope of their physical use. Location-based security authentication technology has recently been developed as a complementary replacement technology. In this study, we introduce location-based security authentication technology using cell broadcasting technology, which has a wider range of applications and is more convenient and business-friendly than existing location-based security authentication technologies. We also introduced application cases and business models related to this. In addition to the current status of technology development, we analyzed current changes in business models being employed. Based on our analysis results, this study draws the implication that technology diversification is necessary to improve the performance of innovative technologies. It is meaningful that it has found and studied advanced technologies other than existing location authentication methods and systems.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.181-203
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• 2022

This study analyzed domestic and foreign literature and examined cases of foreign Community of Practice(CoP) of experts to find out what benefits researchers can gain from participating in their CoP, how the CoP was established, and how data is shared within the CoP. In addition, this study discussed on how to establish a CoP of experts in Korea for sharing and using research data. By participating in the CoP of experts, members can be provided with the opportunity to build an experts' network and have a chance to meet with various experts, to acquire and share their expertise and information, to receive help from other experts, to learn about their expertise, and to have opportunities for professional experiences. In addition, this study discussed 4 factors such as operation method and management system, memberships and number of members, activities, and management of data and repository for establishing a CoP of experts for sharing and using research data. This study provides a knowledge base for building a CoP of experts in Korea.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.1-25
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• 2022

After the first Covid-19 confirmed case occurred in Korea in January 2020, interest in personal transportation such as public bicycles not public transportation such as buses and subways, increased. The demand for 'Ddareungi', a public bicycle operated by the Seoul Metropolitan Government, has also increased. In this study, a demand prediction model of a GRU(Gated Recurrent Unit) was presented based on the rental history of public bicycles by time zone(2019~2021) in Seoul. The usefulness of the GRU method presented in this study was verified based on the rental history of Around Exit 1 of Yeouido, Yeongdengpo-gu, Seoul. In particular, it was compared and analyzed with multiple linear regression models and recurrent neural network models under the same conditions. In addition, when developing the model, in addition to weather factors, the Seoul living population was used as a variable and verified. MAE and RMSE were used as performance indicators for the model, and through this, the usefulness of the GRU model proposed in this study was presented. As a result of this study, the proposed GRU model showed higher prediction accuracy than the traditional multi-linear regression model and the LSTM model and Conv-LSTM model, which have recently been in the spotlight. Also the GRU model was faster than the LSTM model and the Conv-LSTM model. Through this study, it will be possible to help solve the problem of relocation in the future by predicting the demand for public bicycles in Seoul more quickly and accurately.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.405-411
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• 2022

In this study, K-Digital Training program, which is a representative government project of vocational training for new digital technologies in response to the 4th industrial revolution, is analyzed and an improvement model is suggested. The K-Digital training project is rapidly expanding, with the number of training operators increasing by 7.1 times and training course programs by 8.5 times within three years of implementation, but there is a severe problem in that education and training programs are concentrated in the metropolitan. To solve this problem, a shared training model is proposed. This model is a plan to maximize the use of local human and material resources, to respond to new digital technologies through systematic composition and operation, and to enhance the stability and reliability of education and training. In each region, a sharing and cooperation model in the form of a consortium is established that jointly utilizes resources scattered by various training institutions such as instructors, training contents, and training infrastructure related to digital new technology. In addition, a training certification evaluation system is introduced to increase the credibility of the rapidly developing digital new technology training.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.19-36
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• 2023

As advances in information and communication technology have made it easier for anyone to produce and disseminate information, a new problem has emerged: fake news, which is false information intentionally shared to mislead people. Initially spread mainly through text, fake news has gradually evolved and is now distributed in multimedia formats. Since its founding in 2005, YouTube has become the world's leading video platform and is used by most people worldwide. However, it has also become a primary source of fake news, causing social problems. Various researchers have been working on detecting fake news on YouTube. There are content-based and background information-based approaches to fake news detection. Still, content-based approaches are dominant when looking at conventional fake news research and YouTube fake news detection research. This study proposes a fake news detection method based on background information rather than content-based fake news detection. In detail, we suggest detecting fake news by utilizing related video information from YouTube. Specifically, the method detects fake news through CNN, a deep learning network, from the vectorized information obtained from related videos and the original video using Doc2vec, an embedding technique. The empirical analysis shows that the proposed method has better prediction performance than the existing content-based approach to detecting fake news on YouTube. The proposed method in this study contributes to making our society safer and more reliable by preventing the spread of fake news on YouTube, which is highly contagious.