• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.3-19
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• 2024

The purpose of this study is to analyze the impact of attracting a university campus on the local economies of small and medium-sized cities, focusing on changes in local commercial neighborhoods(such as the number of startups, closures, and stores counts). For this study, a Difference-in-Difference(DID) analysis was used to compare the period before and after the attraction of university campuses in four local small and medium-sized cities. These include the Yangsan Campus of Pusan National University, the Jincheon Campus of Woosuk University, the Taean Campus of Hanseo University, and the Dangjin Campus of Hoseo University. The comparison was based on the number of startups, closures, and store counts, using local data provided by the Ministry of the Interior and Safety. The main findings of the study are as follows. First, attracting a university campus has a positive impact on the number of startups, both spatially and temporally. The spatial factors for the number of closures and stores showed a decrease, while the interaction terms representing the period before and after attracting the university campus all indicated an increase. Second, the number of startups in cultural and food-related sectors increase, reflecting the new demand created by attracting the university campus. However, there was also an increase in the number of closures, indicating rapidly changing consumption trends among university students. Third, physical environmental factors such as the number of building floors, land use zoning, and officially assessed land prices have a significant impact on the number of startups, closures, and stores. This supports the assertion that attracting university campus have a positive impact on the revitalization of local commercial neighborhoods.

• Information Systems Review
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• v.21 no.2
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• pp.1-27
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• 2019

It is possible to provide Smart Tourism Service through the development of information technology. It is necessary for the tourism industry to understand and utilize Big Data that has tourists' consumption patterns and service usage patterns in order to continuously create a new business model by converging with other industries. This study suggests to activate Jeju Smart Tourism by analyzing Big Data based on credit card usage records and location of tourists in Jeju. The results of the study show that First, the percentage of Chinese tourists visiting Jeju has decreased because of the effect of THAAD. Second, Consumption pattern of Chinese tourists is mostly occurring in the northern areas where airports and duty-free shops are located, while one in other regions is very low. The regional economy of Jeju City and Seogwipo City shows a overall stagnation, without changes in policy, existing consumption trends and growth rates will continue in line with regional characteristics. Third, we need a policy that young people flow into by building Jeju Multi-complex Mall where they can eat, drink, and go shopping at once because the number of young tourists and the price they spend are increasing. Furthermore, it is necessary to provide services for life-support related to weather, shopping, traffic, and facilities etc. through analyzing Wi-Fi usage location. Based on the results, we suggests the marketing strategies and public policies for understanding Jeju tourists' patterns and stimulating Jeju tourism industry.

• Information Systems Review
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• v.19 no.2
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• pp.115-136
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• 2017

Online communities have become substantial aspects of people's daily lives. However, only a few communities succeed and attract the majority of users, whereas the vast majority struggle for survival. When various communities coexist, important factors should be identified and examined to maintain attraction and achieve success. The concept of coexistence as been extensively explored in organizational ecology literature. However, given the similarities and differences between online communities and traditional organizations, the direct application of organizational theories to online contexts should be cautiously explored. In this study, we follow the roadmap proposed by Davis et al. (2007) in conducting agent-based modeling and simulation study to develop a novel theory based on the previous literature. In the case of two coexisting communities, we find that community size and participation costs can significantly affect the development of a community. A large community can attract a high number of active members who frequently log in. By contrast, low participation costs can encourage the reading and posting behaviors of members. We also observe the important influence of the distribution of interests on the topic trends of communities. A community composed of a population that focuses on only one topic can quickly converge on the topic regardless of whether the initial topic is broad or focused. This simulation model provides theoretical implications to literature and practical guidance to operators of online communities.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.39-55
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• 2024

This study aimed to examine research trends related to Natural Language Processing (NLP) in science education by analyzing 37 domestic and international documents that utilized NLP techniques in the field of science education from 2011 to September 2023. In particular, the study systematically analyzed the content, focusing on the main application areas of NLP techniques in science education, the role of teachers when utilizing NLP techniques, and a comparison of domestic and international perspectives. The analysis results are as follows: Firstly, it was confirmed that NLP techniques are significantly utilized in formative assessment, automatic scoring, literature review and classification, and pattern extraction in science education. Utilizing NLP in formative assessment allows for real-time analysis of students' learning processes and comprehension, reducing the burden on teachers' lessons and providing accurate, effective feedback to students. In automatic scoring, it contributes to the rapid and precise evaluation of students' responses. In literature review and classification using NLP, it helps to effectively analyze the topics and trends of research related to science education and student reports. It also helps to set future research directions. Utilizing NLP techniques in pattern extraction allows for effective analysis of commonalities or patterns in students' thoughts and responses. Secondly, the introduction of NLP techniques in science education has expanded the role of teachers from mere transmitters of knowledge to leaders who support and facilitate students' learning, requiring teachers to continuously develop their expertise. Thirdly, as domestic research on NLP is focused on literature review and classification, it is necessary to create an environment conducive to the easy collection of text data to diversify NLP research in Korea. Based on these analysis results, the study discussed ways to utilize NLP techniques in science education.

• Journal of Advanced Technology Convergence
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• v.3 no.1
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• pp.51-58
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• 2024

The reality of this study is that, in accordance with the development trend of human body art, art makeup and semi-permanent makeup are emerging as promising industries in the beauty industry among beauticians, and awareness of professional skill improvement is gradually increasing over time. Accordingly, interest in semi-permanent makeup has increased not only among beauticians who specialize in beauty industry or learn semi-permanent makeup, but also at beauty academies where they learn many beauty techniques, and this trending technology has been promoted at international beauty competitions by holding skill competitions for beauty technicians who specialize in semi-permanent techniques. As a venue for exchanging information about education, it is expected that synergistic effects such as dissemination of the education system can be expected. Korea's rapid industrial development has brought about great changes in the supply and demand of professional and detailed skilled manpower and in the formation of manpower in terms of technical level according to industrial development, and the skills and professional skills of beauty beauticians have improved due to the excellence of the professional education qualifications of beauticians and high skill evaluations. This had a significant impact on self-development and led to a re-recognition of the importance of efforts to achieve skilled skills.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.141-153
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• 2024

The 2022 revised science curriculum aims to develop the ability to solve scientific problems arising in daily life and society based on convergent thinking stimulated through participation in research activities using artificial intelligence (AI). Therefore, we developed a science-AI convergence education program that combines the science curriculum with artificial intelligence and employed it in convergence classes for high school students. The aim of the science-AI convergence class was for students to qualitatively understand the movement of a damped pendulum and build an AI model to predict the position of the pendulum using the block coding platform KNIME. Individual in-depth interviews were conducted to understand and interpret the learners' experiences. Based on Giorgi's phenomenological research methodology, we described the learners' learning processes and changes, challenges and limitations of the class. The students collected data and built the AI model. They expected to be able to predict the surrounding phenomena based on their experimental results and perceived the convergence class positively. On the other hand, they still perceived an with the unfamiliarity of platform, difficulty in understanding the principle of AI, and limitations of the teaching method that they had to follow, as well as limitations of the course content. Based on this, we discussed the strengths and limitations of the science-AI convergence class and made suggestions for science-AI convergence education. This study is expected to provide implications for developing science-AI convergence curricula and implementing them in the field.

• Journal of Platform Technology
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• v.12 no.1
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• pp.55-66
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• 2024

The K-POP market has become influential not only in culture but also in society as a whole, including diplomacy and environmental movements. As a result, various papers have been conducted based on machine learning to identify the success factors of idols by utilizing traditional data such as music and recordings. However, there is a limitation that previous studies have not reflected the influence of new media platforms such as Instagram releases, YouTube shorts, TikTok, Twitter, etc. on the popularity of idols. Therefore, it is difficult to clarify the causal relationship of recent idol success factors because the existing studies do not consider the daily changing media trends. To solve these problems, this paper proposes a data collection system and analysis methodology for idol-related data. By developing a container-based real-time data collection automation system that reflects the specificity of idol data, we secure the stability and scalability of idol data collection and compare and analyze the clusters of successful idols through a K-Means clustering-based outlier detection model. As a result, we were able to identify commonalities among successful idols such as gender, time of success after album release, and association with new media. Through this, it is expected that we can finally plan optimal comeback promotions for each idol, album type, and comeback period to improve the chances of idol success.

• Convergence Security Journal
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• v.24 no.3
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• pp.165-171
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• 2024

Due to the IT convergence trend, many industrial domains are developing their own IoT services. With batteries and lightweight devices, IoT could expand into various fields including smart farms, smart environments, and smart energy. Many battery-powered IoT devices are passive in enforcing security techniques to maintain service time. This is because security technologies such as cryptographic operations consume a lot of power, so applying them reduces service maintenance time. This vulnerable IoT device security environment is not stable. In order to provide safe IoT services, security techniques considering battery power consumption are required. In this study, we propose an IoT device authentication technology that minimizes power consumption. The proposed technology is a device authentication function based on the Diffie-Hell man algorithm, and has the advantage that malicious attackers cannot masquerade the device even if salt is leaked during the transmission section. The battery power consumption of the authentication technology proposed in this study and the ID/PW-based authentication technology was compared. As a result, it was confirmed that the authentication technique proposed in this study consumes relatively little power. If the authentication technique proposed in this study is applied to IoT devices, it is expected that a safer IoT security environment can be secured.

• Journal of Christian Education in Korea
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• v.77
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• pp.85-105
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• 2024

The purpose of this study is to formulate the direction of Church education, taking into account the negative effects of digital technologies in the era of the Great Digital Transformation. Firstly, the study discussed comprehension of the Great Digital Transformation and negative effects of digital technologies. The term "Great Digital Transformation" signifies a fundamental shift into a world where everything that surrounds us becomes digital-based. In this era of the Great Digital Transformation, the negative effects of digital technologies are intensifying. Secondly, the study discussed the issue of education and church education during the great digital transformation period. The use of digital technologies has been widespread in schools. However, academic circles have raised concerns about the negative effects of digital technology on both the classroom environment and basic academic skills such as reading ability. Since digital education is becoming more popular, there is a fear that church education may fall behind in a rapidly changing society. In conclusion, the study proposed recommendations for reshaping Church education in the era of the Great Digital Transformation, considering the negative effects of digital technologies. The first is Christian worldview education, which is centered around the faith community. Education in the Christian worldview, learned through the interaction with various faiths within the faith community, encourages critical thinking and reflection on the risks posed by the digital age that are associated with capitalism and meritocracy. The second is Christian care, which is centered around the faith community. Christian care in the era of the Great Digital Transformation will help us to form genuine connections with discriminated, isolated, and lonely souls who suffer from negative effects of digital technologies, guiding them towards the path of salvation.