• Journal of the Korea Society of Computer and Information
• /
• v.29 no.5
• /
• pp.111-121
• /
• 2024

With strength training comes the risk of injury and the benefits of exercise. Lack of knowledge and experience or repetitions at excessive intensity can lead to injury. Adequate feedback on an exercise's progress can increase the exercise's effectiveness and reduce injuries by providing scientific data and psychological motivation. This study aimed to validate EMG equipment and examine the effects of 8 weeks of biofeedback training with wireless electromyography. A correlation analysis between the Noraxon device and Fitsig^®(EMG Prototype), a well-known instrument in the field of research, showed a moderate correlation. Statistically significant differences in humeral circumference, humeral muscle mass, and biceps and triceps strength were found between the left and right sides of the body over time, with no differences in the type of exercise. Feedback training with real-time EMG was found to be favorable for hypertrophic growth and strength improvement. Future studies should be conducted to investigate its application in sports activities further.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.6
• /
• pp.41-55
• /
• 2023

In order to secure sustainable competitiveness of startups, business model innovation is an important task to achieve competitive advantage by transforming the various elements that make up the business model. This study conducted a multi-case analysis study on leading smart farm companies around the world using an analysis framework based on business model theory. Through this, we sought to identify business model types and their constituent elements. For this, 19 companies were selected from the list of top 10 investment startups of the year for the past three years published by Agfunder, a global investment research company specializing in AgTech. Then data collection and analysis of the company cases were conducted according to the case study protocol. As a result of the study, the business model types were analyzed into four types: large-scale centralized production model, medium-to-large local distributed production model, small-scale hyperlocal modular FaaS model, and small-scale hyperlocal turnkey solution supply model. A comparative analysis was conducted on five business model components for each type, and strategic implications were derived through this. This study is expected to contribute to improving the competitiveness of domestic smart farm startups and diversifying their strategies by identifying the business models of overseas leading companies in the smart farm field using an academic analysis framework.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.2
• /
• pp.243-252
• /
• 2024

Among the Foley sound generation models that have recently begun to be studied, a sound generation technique using the Vector Quantized-Variational AutoEncoder (VQ-VAE) structure and generation model such as Pixelsnail are one of the important research subjects. On the other hand, in the field of deep learning-based acoustic signal compression, residual vector quantization technology is reported to be more suitable than the conventional VQ-VAE structure. Therefore, in this paper, we aim to study whether residual vector quantization technology can be effectively applied to the Foley sound generation. In order to tackle the problem, this paper applies the residual vector quantization technique to the conventional VQ-VAE-based Foley sound generation model, and in particular, derives a model that is compatible with the existing models such as Pixelsnail and does not increase computational resource consumption. In order to evaluate the model, an experiment was conducted using DCASE2023 Task7 data. The results show that the proposed model enhances about 0.3 of the Fréchet audio distance. Unfortunately, the performance enhancement was limited, which is believed to be due to the decrease in the resolution of time-frequency domains in order to do not increase consumption of the computational resources.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.2
• /
• pp.565-574
• /
• 2024

ChatGPT is causing significant reverberations across all sectors of our society, and this holds true for the field of education as well. However, scholarly and societal discussions regarding ChatGPT in academic settings have primarily focused on issues such as plagiarism, with relatively limited research on the positive effects of utilizing generative AI. Additionally, amidst the educational crisis of the post-COVID era, there is a growing recognition of the need to enhance academic engagement. In light of these concerns, we investigated how academic engagement varies based on students' levels of ChatGPT literacy and examined whether students' academic confidence and perceived academic competence serve as mediators between ChatGPT literacy and academic engagement. An analysis using SPSS was conducted on the data collected from 406 college students. The results showed that ChatGPT literacy had a positive effect on academic engagement, and academic confidence mediated the relationship between ChatGPT literacy and academic engagement. Also, when the mediating effect of perceived academic competence was significant only when it was serially mediated. Based on these findings, we discussed the theoretical contributions of identifying the theoretical mechanism between ChatGPT literacy and academic engagement. In addition, practical implications regarding the importance of ChatGPT literacy education were described.

• Journal of Service Research and Studies
• /
• v.14 no.1
• /
• pp.77-90
• /
• 2024

This research aims to investigate methods of leveraging generative artificial intelligence in service sectors where consumer sentiment and experience are paramount, focusing on minimizing hallucination phenomena during usage and developing strategic services tailored to consumer sentiment and experiences. To this end, the study examined both mechanical approaches and user-generated prompts, experimenting with factors such as business item definition, provision of persona characteristics, examples and context-specific imperative verbs, and the specification of output formats and tone concepts. The research explores how generative AI can contribute to enhancing the accuracy of personalized content and user satisfaction. Moreover, these approaches play a crucial role in addressing issues related to hallucination phenomena that may arise when applying generative AI in real services, contributing to consumer service innovation through generative AI. The findings demonstrate the significant role generative AI can play in richly interpreting consumer sentiment and experiences, broadening the potential for application across various industry sectors and suggesting new directions for consumer sentiment and experience strategies beyond technological advancements. However, as this research is based on the relatively novel field of generative AI technology, there are many areas where it falls short. Future studies need to explore the generalizability of research factors and the conditional effects in more diverse industrial settings. Additionally, with the rapid advancement of AI technology, continuous research into new forms of hallucination symptoms and the development of new strategies to address them will be necessary.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.3
• /
• pp.77-85
• /
• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• The Korean Journal of Archival Studies
• /
• no.79
• /
• pp.33-82
• /
• 2024

Interest in ESG management, which spread through the UN PRI in 2006, has recently spread throughout our society. Consumers use a company's activeness in the ESG field as the standard of consumption behavior, and the international community is reorganizing and strengthening various regulatory measures. In the investment market, non-financial performance (ESG information) is used as an important investment indicator along with financial performance (credit rating). Due to these changes in the corporate evaluation paradigm and market pressure, if a company neglects ESG response activities, it is more likely to be excluded from market selection, and accordingly, the importance of ESG management is also increasing. Companies are making various efforts to secure legitimacy in response to these market pressures, but in the process, it is difficult to systematically manage and utilize records/data that are the basis for ESG management. For a basic understanding of ESG management, this paper summarizes the emerging process of ESG and the current ESG-related regulations applied to companies. Through this, it can be seen that ESG management is not carried out with the good will of the company, but is accepted as a management strategy for the survival of the company according to the change in the corporate evaluation paradigm. Through interviews with the company's ESG-related personnel, the company's ESG response process was divided into passive communication and active communication, and the problems identified during the interview were summarized for each communication type. In addition, in the process of passively and actively communicating ESG management information with internal and external stakeholders, the possibility that ESG archives can function as a tool to overcome problems for each communication type was raised, and five types of ESG archives that can play this role were presented.

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

• Korean Journal of Environmental Biology
• /
• v.42 no.1
• /
• pp.28-45
• /
• 2024

This study was conducted to investigate the flora of Sonjukdo Island(Yeosu-si), Korea. From results of four field surveys from April 2023 to October 2023, we identified 483 total taxa, representing 440 species, seven subspecies, 35 varieties, and one hybrid. They were placed in 322 genera and 109 families, including 249 taxa newly recorded in this study. Among them, four taxa were endemic to Korea, four taxa were IUCN red list plants, and 22 taxa were climate sensitive indicator plants. Floristic target plants amounted to 99 taxa, including two taxa of grade IV, 41 taxa of grade III, 10 taxa of grade II, and 46 taxa of grade I. A total of 54 taxa of alien plants were identified, with a Naturalized Index of 11.2% and an Urbanization Index of 13.8%. Three plants disturbed the ecosystem. The flora of this surveyed area belongs to the south-coast province among floral provinces of the Korean Peninsula. Our results provide basic data on vascular plants flora, plant species diversity, and distributional changes.

• Korean Journal of Environmental Biology
• /
• v.42 no.2
• /
• pp.193-206
• /
• 2024

This study aimed to quantify changes in forest cover and carbon storage of Korean Peninsular during the last two decades by integrating field measurement, satellite remote sensing, and modeling approaches. Our analysis based on 30-m Landsat data revealed that the forested area in Korean Peninsular had diminished significantly by 478,334 ha during the period of 2000-2019, with South Korea and North Korea contributing 51.3% (245,725 ha) and 48.6% (232,610 ha) of the total change, respectively. This comparable pattern of forest loss in both South Korea and North Korea was likely due to reduced forest deforestation and degradation in North Korea and active forest management activity in South Korea. Time series of above ground biomass (AGB) in the Korean Peninsula showed that South and North Korean forests increased their total AGB by 146.4Tg C (AGB at 2020=357.9Tg C) and 140.3Tg C (AGB at 2020=417.4Tg C), respectively, during the last two decades. This could be translated into net AGB increases in South and North Korean forests from 34.8 and 29.4 Mg C ha^-1 C to 58.9(+24.1) and 44.2(+14.8) Mg C ha^-1, respectively. It indicates that South Korean forests are more productive during the study period. Thus, they have sequestered more carbon. Our approaches and results can provide useful information for quantifying national scale forest cover and carbon dynamics. Our results can be utilized for supporting forest restoration planning in North Korea