• 한국치위생학회지
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• 제23권5호
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• pp.387-393
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• 2023

Objectives: This study was attempted in order to understand about the satisfaction with major and the dental hygiene professionalism in dental hygiene students and to grasp the factors affecting the career preparation behavior. Methods: The research subjects included 264 juniors and seniors who are attending dental hygiene department across Korea (three locations in Gyeonggi province, one locations in Daejeon, four locations in Jeolla province, and one locations in Daegu). Data were collected using the online questionnaire between March 6 to April 7, 2023. The chosen data analysis method included descriptive statistical analysis, t-test, one-way ANOVA, Pearson's correlation coefficient, and stepwise multiple linear regression. Results: The following average scores were obtained from those surveyed: 3.25 points concerning career preparation behavior, 3.83 points concerning the respondent's satisfaction with their major, and 3.45 points concerning dental hygiene professionalism. As for a difference in career preparation behavior according to general characteristics, a meaningful difference was shown in terms of gender, motivation for entering the field, and first desired employment. Aspects of career preparation behavior, satisfaction with one's major, and dental hygiene professionalism showed a significant correlation and were confirmed to explain the prediction of 29.1% of the variation in the regression model. Conclusions: For the sake of having an integrated understanding about career preparation behavior among dental hygiene students, there is a need to conduct repeated research on diverse variables and to inquire into a causal relationships between such variables.

• 한국간호교육학회지
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• 제30권2호
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• pp.149-159
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• 2024

Purpose: The aim of this study was to identify core keywords and topic groups in the "adolescent pregnancy" field of research for a better understanding of research trends in the past 10 years. Methods: Topics related to adolescent pregnancy were extracted from 3,819 articles that were published in journals between January 2013 and July 2023. Abstracts were retrieved from five databases (MEDLINE, CINAHL, Embase, RISS, and KISS). Keywords were extracted from the abstracts and cleaned using semantic morphemes. Text network analysis and topic modeling were performed using NetMiner 4.3.3. Results: The most important keywords were "health," "woman," "risk," "group," "girl," "school," "service," "family," "program," and "contraception." Five topic groups were identified through topic modeling. Through the topic modeling analysis, five themes were derived: "health service," "community program for school girls," "risks for adult women," "relationship risks," and "sexual contraceptive knowledge." Conclusion: This study utilized text network analysis and topic modeling to analyze keywords from abstracts of research conducted over the past decade on adolescent pregnancy. Given that adolescent pregnancy leads to physical, mental, social, and economic issues, it is imperative to provide integrated intervention programs, including prenatal/postnatal care, psychological services, proper contraception methods, and sex education, through school and community partnerships, as well as related research studies. Nurses can play a vital role by actively engaging in prevention efforts and directly supporting and educating socially disadvantaged adolescent mothers, which could significantly contribute to improving their quality of life.

• The Plant Pathology Journal
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• 제40권3호
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• pp.310-321
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• 2024

Tomato yellow leaf curl virus (TYLCV) and tomato spotted wilt virus (TSWV) are well-known examples of the begomovirus and orthotospovirus genera, respectively. These viruses cause significant economic damage to tomato crops worldwide. Weeds play an important role in the ongoing presence and spread of several plant viruses, such as TYLCV and TSWV, and are recognized as reservoirs for these infections. This work applies a comprehensive approach, encompassing field surveys and molecular techniques, to acquire an in-depth understanding of the interactions between viruses and their weed hosts. A total of 60 tomato samples exhibiting typical symptoms of TYLCV and TSWV were collected from a tomato greenhouse farm in Nonsan, South Korea. In addition, 130 samples of 16 different weed species in the immediate surroundings of the greenhouse were collected for viral detection. PCR and reverse transcription-PCR methodologies and specific primers for TYLCV and TSWV were used, which showed that 15 tomato samples were coinfected by both viruses. Interestingly, both viruses were also detected in perennial weeds, such as Rumex crispus, which highlights their function as viral reservoirs. Our study provides significant insights into the co-occurrence of TYLCV and TSWV in weed reservoirs, and their subsequent transmission under tomato greenhouse conditions. This project builds long-term strategies for integrated pest management to prevent and manage simultaneous virus outbreaks, known as twindemics, in agricultural systems.

• Journal of Positioning, Navigation, and Timing
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• 제13권1호
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• pp.111-115
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• 2024

This study builds a machine learning model optimized for clocks among various techniques in the field of artificial intelligence and applies it to clock stabilization or synchronization technology based on atomic clock noise characteristics. In addition, the possibility of providing stable source clock data is confirmed through the characteristics of machine learning predicted values during holdover of atomic clocks. The proposed machine learning model is evaluated by comparing its performance with the AutoRegressive Integrated Moving Average (ARIMA) model, an existing statistical clock prediction model. From the results of the analysis, the prediction model proposed in this study (MSE: 9.47476) has a lower MSE value than the ARIMA model (MSE: 221.2622), which means that it provides more accurate predictions. The prediction accuracy is based on understanding the complex nature of data that changes over time and how well the model reflects this. The application of a machine learning prediction model can be seen as a way to overcome the limitations of the statistical-based ARIMA model in time series prediction and achieve improved prediction performance.

• 농촌계획
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• 제30권2호
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• pp.51-68
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• 2024

Since 1949, the UK has implemented a national land planning strategy to sustain rural areas, emphasizing the concept of 'Natural Beauty.' This involves designating "Areas of Outstanding Natural Beauty (AONB)" as a political approach to conserving rural landscapes and fostering a societal consensus on environmental conservation. AONB adopts an integrated and systematic approach to achieve harmony between the environment and human activities. This study investigates the implications of the AONB rural landscape management approach through case studies of the Cotswolds Conservation Board and Cannock Chase Joint Committee. It examines the legislative designation and supporting processes of AONB, analyzing the governance system to clarify the roles of authorities in policy decision-making. AONB's system revolves around joint committees or conservation boards of local authorities responsible for establishing, implementing, and monitoring management plans. The planning process involves a harmonious management plan system reflecting regional demands, including regular forums. AONB serves as a powerful tool for local residents to engage in the development of their region through stewardship. The study suggests that understanding the AONB model could provide a foundation for developing rural landscape conservation and spatial management plans tailored to Korea's context in the future.

• 식물병연구
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• 제30권1호
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• pp.34-49
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• 2024

The development of sustainable smut management techniques requires an understanding of the impacts of smut on sugarcane growth and the relationships between smut intensity and meteorological variables, varieties, and crop types. Thus, assessments were made with the objectives to 1) determine the effect of smut on the above-ground growth of sugarcane, and 2) quantify the association of smut with weather variables, varieties and crop types. The effect of smut on above-ground growth was assessed in six fields planted with NCo 334 (wider coverage) having 6 months of age in Fincha and Metehara fields in 2021. Data on above-ground growth were taken from 20 randomly selected smut-affected and healthy stools from each field. Besides, 6 years' data (2015 to 2021) on the numbers of smut-affected stools and smut whips of 79 fields were collected. Furthermore, 10 years' (2011 to 2021) weather data were acquired from the sugar plantations. The results demonstrated reduction in the above-ground growth of sugarcane in the range of 18.39% and 73.42% due to smut. In addition, weather variables explained about 68.48% and 66.58% of the variability in the number of smut-affected stools and whips respectively. Smut intensity increased with crop types for susceptible varieties. The tight association between the smut epidemic and crop types, varieties, and weather, implied that these parameters must be carefully considered in management decisions. Continuous monitoring of smut disease, meteorological variables, varieties, and crop types in all the sugarcane plantations could be done as a part of integrated smut management in the future.

• Journal of Information Technology Applications and Management
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• 제30권1호
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• pp.115-126
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• 2023

In various fields such as art, design, music, film, sports, games, and fashion, NFTs (Non-Fungible Tokens) are creating new economic value through trading platforms dedicated to NFT art and content. In this article, I analyze the current state of blockchain technology and NFT art content in the context of an expanding market for blockchain-based NFT art content in the metaverse. I also propose several tasks based on the economic and industrial logic of technological innovation. The first task proposed is to integrate cultural arts on blockchain, metaverse, and NFT platforms through digital innovation, instead of separating or distinguishing between creative production and consumption. Before the COVID-19 pandemic, there was a clear separation between creators and consumers. However, with the rise of Web 3.0 platforms, any user can now create and own their own content. Therefore, it is important to promote a collaborative and integrated approach to cultural arts production and consumption in the blockchain and metaverse ecosystem. The second task proposed is to align the legal framework with blockchain-based technological innovation. The enactment and revision of relevant laws should focus on promoting the development of the NFT trading platform ecosystem, rather than merely regulating it for user protection. As blockchain-based technology continues to evolve, it is important that legal systems adapt to support and promote innovation in the space. This shift in focus can help create a more conducive environment for the growth of blockchain-based NFT platforms. The third task proposed is to integrate education on digital arts, including metaverse and NFT art contents, into the current curriculum. This education should focus on convergence and consilience, rather than merely mixing together humanities, technology, and arts. By integrating digital arts education into the curriculum, students can gain a more comprehensive understanding of the potential of blockchain-based technologies and NFT art. This article examines the digital technological innovation such as blockchain, metaverse, and NFT from an economic and industrial point of view. As a limitation of this research, the critical mind such as philosophical thinking or social criticism on technological innovation is left as a future task.

• 한국환경과학회지
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• 제33권8호
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• pp.575-581
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• 2024

Insect pests are a significant threat to stored crops and can lead to considerable economic losses and reduced crop quality. Traditional pest control methods often involve chemical treatments, which have adverse environmental and health effects. This study evaluated the effectiveness of controlling the environment using LED lighting and plant-derived odor barriers as a dual strategy for insect pest control. The storage environment was altered using LED lights that emitted specific wavelengths (580-585 nm) and by reducing other wavelengths (300-500 nm). This light environment was combined with an insect odor barrier derived from Cinnamomum verum, Illicium verum, and Artemisia annua, and their duel impact on the behavior and frequency of insect pests under real storage conditions was determined. The findings revealed significant changes in the frequencies of various insect orders, indicating differential responses to light wavelengths and odor barriers. Notably, the introduction of an anti-insect light and odor barrier environment reduced Diptera and Hemiptera frequencies, which could potentially reduce pest intrusion. The results underscore the potential use of integrated light and odor barriers as a noninvasive and environmentally friendly approach to pest management. This study identifies the specific wavelengths and odor combinations that effectively deter insect pests and contribute to the development of more efficient and sustainable pest control methods. It also highlights the importance of understanding insect behavior and frequency changes in response to novel deterrent strategies.

• 실천공학교육논문지
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• 제16권4호
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• pp.513-520
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• 2024

본 연구는 AI의 학교교육 영향이 확대됨에 따른 교사의 직무 변화에 대한 연구이다. 전통적으로 교사는 교실 수업, 교육과정 개발, 평가 및 피드백과 같은 핵심 업무를 담당해왔다. AI는 이러한 과정을 자동화할 수 있으며, 특히 개인화된 학습을 통해 효율성을 높일 수 있으며 학생 추적, 행동 감지 및 그룹 활동 분석과 같은 복잡한 교실 관리 작업을 지원할 수 있다. 그러나 AI는 상담 및 대인 커뮤니케이션과 같은 학생 생활 지도에 중요한 측면을 자동화가 어려운 것으로 나타났다. 이와 같은 직무에서 AI가 직접적으로 상담활동을 대체 하는 것은 어렵지만, 데이터 기반의 인사이트와 사전 대화 자료를 제공함으로써 교사를 지원할 수 있다. AI시대의 교사 역량 강화 요소로는 심화 학습 운영 전문성, 데이터셋 분석 능력, 개별학습 운영 능력, 학생 및 학부모 상담역량, 그리고 AI디지털 역량이 필요하다. 교사는 AI와 협업하여 창의성과 확장적 추상능력을 강조하는 수업을 운영하고, AI시스템에서 생성된 데이터셋을 분석하고 개별화된 학습 경로를 조정하는 역량을 가져야 한다. 또한 개별화된 학습과 학생 상담에 집중하여 AI로 대체되기 어려운 부분을 수행해야 한다. 교사의 기본적인 역량으로는 AI디지털 소양 능력이 필요하며, AI시스템에 대한 이해와 학생 데이터 관리 역량이 요구된다.

• 문화기술의 융합
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• 제10권5호
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• pp.645-650
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• 2024

본 논문은 챗GPT를 중심으로 생성형 AI를 활용한 대학 교양교육을 위해 지방 소재의 두 대학에서 교양교과목 교육과정을 공동으로 설계하고 개발하였다. 개발된 교육과정은 기존 연구에서 제시된 대학 챗GPT 통합 활용 수업 설계를 위한 개념적 구성요소를 고려하여 챗GPT의 기반을 이루는 언어모델과 인공지능을 이해하고 챗GPT을 포함하는 생성형 AI를 다양한 도메인에 활용하는 내용으로 개발하였다. 개발된 교육과정은 다양한 전공의 수강생을 대상으로 챗GPT의 기반인 자연어처리 언어모델과 인공지능의 개념 및 변화양상을 소개하고, 생성 AI 및 대형언어모델(LLM)인 챗GPT와 다양한 오픈소스 생성 모델을 이용하여 나만의 AI 서비스를 구현하며, 대학 교양교육에서 혁신적인 교육방법으로서, 대학간 공유협력 공동교육과정운영을 위한 사례를 제시하고자 한다.