• Smart Media Journal
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• v.12 no.8
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• pp.9-17
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• 2023

The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.556-576
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• 2023

This study attempted to find a way to utilize idle spaces in rural areas as a way to respond to rural extinction. Based on the keywords "startup," "youth start-up," and "youth start-up+rural," start-up+rural," the study sought to identify the perception of idle facilities in rural areas through the keywords "Idle facilities" and "closed schools." The study presented basic data for policy direction and plan search by reviewing frequency analysis, major keyword analysis, network analysis, emotional analysis, and domestic and foreign cases. As a result of the analysis, first, it was found that idle facilities and school closures are acting importantly as factors for regional regeneration. Second, in the case of youth startups in rural areas, it was found that not only education on agriculture but also problems for residence should be solved together. Third, in the case of young people, it was confirmed that it was necessary to establish digital utilization for agriculture by actively starting a business using digital. Finally, in order to attract young people and revitalize the region through best practices at home and abroad, policy measures that can serve as various platforms such as culture and education as well as startups should be presented in connection with local residents. These results are significant in that they presented implications for youth start-ups in rural areas by reviewing start-up recognition for the influx of young people as one of the alternatives for the use of idle facilities and regional regeneration, and if additional solutions are presented through field surveys, they can be used to set policy goals that fit the reality.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.539-544
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• 2023

In this study, several important aspects were studied in producing video advertisements based on the lifestyle and SNS status of Generation Z. Generation Z highly values participation and interaction due to the nature of SNS, so SNS advertisements should be produced in a way that induces active interaction with viewers and accepts feedback. Here's a summary of the main parts. It prefers various content formats of Generation Z that consume information. Advertisements should be produced in various formats such as text, images, and videos, and should have flexibility suitable for various platforms. Because each SNS platform has its own characteristics due to platform specialization, this study suggests that advertisements analyze the characteristics of the platform and use the appropriate content strategy for the optimized platform. As an emphasis on value proposition, we propose an advertising format setting to focus on what value the product or brand provides. It is important to clearly emphasize the advantages and intrinsic value of a product or service in video advertising, and in conclusion, we propose to focus on the case of increasing interest by adopting modern and trendy design of storytelling as an attractive and unique design method of aesthetic design and visual effects. Considering these factors comprehensively, the research value of this paper will be able to establish an effective SNS marketing strategy by producing video advertisements that match the lifestyle and SNS usage characteristics of Generation Z.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.109-118
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• 2023

Cardiac arrest is a critical medical emergency where immediate response is essential for patient survival. This is especially true for Out-of-Hospital Cardiac Arrest (OHCA), for which the actions of emergency medical services in the early stages significantly impact outcomes. However, in Korea, a challenge arises due to a shortage of dispatcher who handle a large volume of emergency calls. In such situations, the implementation of a machine learning-based OHCA detection program can assist responders and improve patient survival rates. In this study, we address this challenge by developing a machine learning-based OHCA detection program. This program analyzes transcripts of conversations between responders and callers to identify instances of cardiac arrest. The proposed model includes an automatic transcription module for these conversations, a text-based cardiac arrest detection model, and the necessary server and client components for program deployment. Importantly, The experimental results demonstrate the model's effectiveness, achieving a performance score of 79.49% based on the F1 metric and reducing the time needed for cardiac arrest detection by 15 seconds compared to dispatcher. Despite working with a limited dataset, this research highlights the potential of a cardiac arrest detection program as a valuable tool for responders, ultimately enhancing cardiac arrest survival rates.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.71-79
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• 2024

ChatGPT, an interactive artificial intelligence (AI) chatbot developed by Open AI in the U.S., gaining popularity with great repercussions around the world. Some academia are concerned that ChatGPT can be used by students for plagiarism, but ChatGPT is also widely used in a positive direction, such as being used to write marketing phrases or website phrases. There is also an opinion that ChatGPT could be a new future for "search," and some analysts say that the focus should be on fostering rather than excessive regulation. This study analyzed consciousness about ChatGPT for college students through a survey of their perception of ChatGPT. And, plagiarism inspection systems were prepared to establish an education support model using ChatGPT and ChatGPT. Based on this, a university education support model using ChatGPT was constructed. The education model using ChatGPT established an education model based on text, digital, and art, and then composed of detailed strategies necessary for the era of the 4th industrial revolution below it. In addition, it was configured to guide students to use ChatGPT within the permitted range by using the ChatGPT detection function provided by the plagiarism inspection system, after the instructor of the class determined the allowable range of content generated by ChatGPT according to the learning goal. By linking and utilizing ChatGPT and the plagiarism inspection system in this way, it is expected to prevent situations in which ChatGPT's excellent ability is abused in education.

• Land and Housing Review
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• v.15 no.3
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• pp.113-127
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• 2024

This study explores shifts in real estate investment sentiment using media reports from 2012 to 2022, segmenting the market dynamics into three distinct cycles based on housing and land transaction indices. Leveraging 54 BigKinds media sources, we investigates 3,387 headlines and 8,544 body texts using LDA topic modeling. The results show that the first cycle (2012-2015 ) centered on apartment pre-sales, where policy changes influenced sentiment but did not consistently affect investment decisions. The second cycle (2016-2018) was characterized by interest rate hikes and rising property prices in Seoul, resulting in significant fluctuations in transaction volumes. The third cycle (2019-2022) encompassed the effects of COVID-19, market instability, and policy failures, leading to distorted and weakened investment sentiment. Each cycle demonstrated that policies, interest rates, and economic events significantly shaped investor sentiment, as reflected in media reports.

• 유학연구
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• v.49
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• pp.265-290
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• 2019

This paper examined the understanding of the laws and punishments of Zhu Xi School. Zhu Xi of Nan-song(南宋) is a scholar who influenced many later East Asian countries, including Joseon. When limited to Joseon, various academic and political thought used Zhu Xi's interpretation as a standard. Thus it is necessary to study Zhu Xi's thought of law to comprehend the Confucian countries. However, there are a few previous studies that deal with the legal ideas of Zhu Xi. In order to understand Zhu Xi's perception of the law, this paper will analyze the Book of History(書經) as a central text. The Book of History describes the system and the law of ancient China. It also deals with the origin and development of punishment and legislation, unlike other scriptures. However, Zhu Xi died before he finished his work, making a footnote of the Book of History. Following his work, Cai Shen(蔡沈) completed the interpretation of the Book of History. Therefore, it would be natural to think Zhu Xi and Cai Shen were in continuity. This paper figures out the recognition of Zhu Xi School on punishment and law by organizing the history of punishment and law in the Book of History. Furthermore, analyzes other papers of Zhu xi to know his perception of law and punishment.

• CHINESE LITERATURE
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• v.100
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• pp.71-84
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• 2019

The academia has always maintained a strong interest in Fu Sheng Liu Ji since it was known to the world. However, current studies mostly focused on English versions translation, classification of works genres, the Image of the heroine Chen Yun, and depicting, which based on content of the works, the life of the lower literati in the mid-Qing Dynasty, yet no systematic discussion on the characteristic construction of memorial space has been carried out. Although real life was used as writing material, a careful reading will reveal that Shen Fu, the author, had the memories significantly split and reassembled, which was achieved through the repetition of fragmentary memory spaces. The intentionally constructed characters of these memory spaces, along with their combinations, and the mentality of the lower literati in the mid-Qing Dynasty are all worthy of further study, these aspects and their relations were discussed in this paper. The second chapter summarized, classified and described the types of memory spaces in the works. Two typical memory spaces were appeared, semi-closed dotted space and open linear space. The former was mainly in Gui Fang Ji Le and Xian Qing Ji Qu while the latter was in Kan Ke Ji Chou and Lang You Ji Kuai. The following discussion was on Shen Fu's deliberately disconnecting the time chain, and the narrative ways of categorizing and linking these memory spaces. The third chapter revealed the mentality of the lower-class literati in the mid-Qing Dynasty, which hidden behind the special construction mode of Shen Fu's memory spaces, was believed as a "active marginalization", and specifically manifested in defending the private space, as well as resisting the social space. Therefore, the paper holds that Fu Sheng Liu Ji is not a record of Shen Fu's life, but a deliberate cutting and reorganizing of the memory spaces, and his active marginalization mentality contributes to the construction of such groups of memory spaces.