Due to recent increase in the number of elderly patients, there is a problem of nutritional imbalance and immune function in the elderly due to decreased ability to consume food. To solve these problems, this study was conducted to verify an immunityenhancing effect of Sagunja-tang porridge (SP) on cyclophosphamide (CPA)-induced immunosuppression using an animal model. Experimental groups were set as normal control, CPA-treated group, positive control group, and SP-treated groups (0.25%, 0.5%, 1.0%). Except for the normal control group, experimental groups were injected with 100 μL of CPA dissolved in 0.9% NaCl at a concentration of 150 mg/kg twice at the beginning of the experiment and 3 days later to induce immunosuppression. When spleen cell proliferation was analyzed, both B and T cells were decreased in the immunosuppressed group, but increased in test substance-treated groups in a concentration-dependent manner. To see the effect of improving immunity, levels of IgA known to protect the mucosal surface were measured. Higher levels of IgA were found in SP-low concentration (SL) and SP-middle concentration (SM) groups. These results suggest that using SP might be an effective way to improve nutritional imbalance and immune function in the elderly.

Purpose: This study aims to examine the effect of 'debate education using generative artificial intelligence (AI)' on 'debate efficacy' targeting elementary school students in the 5th and 6th grades. Through this, we aim to provide valuable information on debate classes using generative AI to field teachers and researchers in debate-related studies. This study aimed to provide students with a positive communication experience by allowing them to articulate their arguments, engage with peers, and persuade others. Additionally, it sought to serve as a foundation for fostering students' collaborative communication skills and digital language literacy. Furthermore, in alignment with the introduction of the “Media” domain in the 2022 Revised Korean Language Education Curriculum, this study aimed to offer pedagogical implications for teachers regarding debate education using generative AI. Lastly, it sought to expand the scope of Korean language education by preparing students to actively adapt to the rapidly evolving communication environment of the future society. Methods: To achieve this, a triangulation study combining quantitative and qualitative research methods was conducted. The quantitative research compared and analyzed the pre-post debate self-efficacy of the participants, while the qualitative research explored the effects of debate classes using generative AI by analyzing portfolios generated by the participants. Descriptive statistics and the Wilcoxon signed-rank test were used to analyze quantitative data. As some of the response data from the participants did not satisfy the assumption of normality, the pre-and post-test changes in debate efficacy among the participants were analyzed using a nonparametric Wilcoxon signed- rank test (p<.05). The reliability of this study was verified through Cronbach’s ⍺ value. Portfolio analysis was employed for the qualitative data analysis. Results: The “Debate Self-Efficacy” of the participants was measured pre- and post-intervention using the Wilcoxon Signed-Rank Test. The results showed a significant improvement in all subcomponents of debate self-efficacy, including Emotional Self-Efficacy, Cognitive Self-Efficacy, and Social Self-Efficacy. In particular, significant improvements were observed in the components of Emotional Self-Efficacy, namely ‘expectation,’ ‘persistence,’ and ‘emotion regulation.’ Furthermore, the analysis of portfolios composed of activity sheets developed for this study revealed that engaging in debate activities using Generative AI positively enhanced the debate self-efficacy of the participants. Conclusion: This study demonstrates through action research and empirical analysis that Korean language debate classes utilizing generative AI are effective in enhancing students' debate efficacy. This study hopes to serve as a stepping stone for fostering Inclusivity and enhancing Communication Competence among learners, thereby contributing to the strengthening of their Debate Self-Efficacy. Furthermore, it is expected that this research will contribute to the activation of Debate Education Using Generative AI in school.

도로 위 차량의 차로변경은 주변 차량의 움직임에 민감하게 반응해야 하며, 적절한 속도와 타이밍으로 수행하지 못할 경우 교통 흐름을 방해하고 부정적인 영향을 초래할 수 있다. 자율주행차량(Autonomous Vehicle, AV)은 이러한 문제를 해결하기 위해 주변 상황을 정확히 판단하고 인지하여 차로변경을 수행한다. 이때, 안전 관리 전략의 일환으로 최적화된 차로변경 주행 궤적을 제공함으로써 안전하고 효율적인 차로변경을 실현하는 것이 중요하다. 본 연구는 이러한 배경에서 주변 차량과 EGO 차량의 예측 주행 궤적에 기반한 확률론적 개념인 risk field를 계산하고, 이를 활용하여 차량의 종방 향 및 횡방향 안전 궤적을 제시하였다. 이를 위해 고속도로 드론 데이터를 활용하여 차량 간 상호작용 상황을 분석하고, 차로변경 시나리오 데이터를 분류하였다. 연구에서는 주행 속도와 차량의 경위도 등 1.1초 동안의 연속된 주행 데이터를 입력으로 사용하였으며, 다층 인코더-디코더 장단기 메모리 네트워크(EDLN) 모델을 통해 미래 6초 후 차량의 위치를 예 측하였다. 이후 장 이론(field theory)을 기반으로 한 risk field 모형을 통해 도로 위 각 지점의 위험도를 정량화하였다. 또한, 차량의 거동 제약, 주행 편의성, 그리고 안전성 제약 조건을 반영하여 안전 궤적을 생성하였다. 마지막으로, 생성된 궤적이 교통류 안전성에 미치는 영향을 평가하기 위해 예측된 주행 궤적(predicted trajectory)과 실제 주행 궤적(ground truth)을 비교 분석하였다. 평가지표는 대리 안전 지표(surrogate safety measure, SSM) 중 TTC(Time to Collision)와 PET(Post Encroachment Time)를 활용하였다. 본 연구는 제안된 안전성 정량화 및 궤적 생성 방법이 기존 방법론과 비 교하여 우수한 성능을 보임을 입증하였으며, 향후 자율주행차량 혼재 교통류 및 완전 자율주행 교통류에서 높은 효율성 과 안전성을 확보하는 데 기여할 것으로 기대된다.

이 연구는 관측 지점의 해황 정보 데이터를 기반으로 관측 지점 이외 공간의 해황 정보 데이터를 격자 형식으로 공간 보간하는 방법에 관해 연구한다. 해황 정보를 얻을 수 있는 관측소나 관측 지점의 공간적 분포가 제한되어 있어 단편적인 지점의 해황 정보만을 수 집할 수 있기 때문에 이러한 점을 해결하기 위해 OPEN API를 활용하여 해황 정보 데이터를 수집하고, 데이터 전처리 과정을 통해 관측 데이터가 존재하지 않는 지점의 데이터를 격자 형식으로 공간 보간한다. 본 연구에서 사용된 보간 방법으로는 Cubic spline interpolation, Linear extrapolation, Kriging 3가지 방법을 사용하였고 각 보간 결과의 비교 분석을 통해 보간 결과의 정확도와 공간 보간에 활용 가능성을 평가하였다. 결과적으로 Kriging이 관측된 지점 간의 공간적 분포와 상관관계, 해황 정보의 데이터 구조를 가장 잘 반영하여 관측 지점 이 외 보간에 대한 결과가 다른 두 보간 방법에 비해 높은 정확도를 보여 해황 정보 공간 보간에 적합한 보간 방법으로 판단되었다. 공간 보 간된 데이터는 평균 풍속 및 풍향, 평균 조류 속도 및 방향 등 선박의 조종성에 영향을 미치는 요인을 정밀하게 계산하는 데 활용 가능하 며 선박 항해 경로를 따라 영향을 받는 외력을 파악, 이를 통해 안전성과 경제성을 모두 고려한 경로 탐색에 활용할 수 있을 것으로 기대 된다.

Motorcycles are becoming a major means of transportation in the delivery industry because of their mobility and economic feasibility, and their use is increasing with the spread of non-face-to-face culture. However, owing to the absence of a systematic maintenance and inspection system, illegal modifications, and a lack of safety education, the possibility of accidents is increasing, and social problems are intensifying. To address this issue, we aim to find ways to improve motorcycle safety. Problems were identified by registering motorcycles, driver crashes, and surveys of the current status of laws and systems. Subsequently, a questionnaire was administered to assess the actual conditions and perceptions regarding motorcycles. Finally, to analyze the driving characteristics of delivery motorcycles, traffic safety education was conducted for new delivery riders, and the driving characteristics were analyzed by collecting driving record data. In this study, a plan to enhance the license system, education, insurance, and educational programs is proposed to strengthen motorcycle safety. The licensing system needs to be elevated by age and classified by displacement, and delivery riders can improve their driving skills through mandatory traffic safety education. The insurance sector should introduce a system that discounts insurance premiums upon completion of training. Additionally, it is essential to prepare a systematic education program, including obstacle avoidance and simulation-based learning, by reflecting on the analysis results of road environments and driving data. In this study, insensitivity to safety, insufficient management systems, and lack of education and publicity were identified as causes of motorcycle driver crashes. It was confirmed that most types of dangerous driving were improved through traffic safety education. However, some limitations were observed, such as an increase in the right-hand rotation over time during sudden turns. Future research is needed to enhance laws, systems, and driver safety by analyzing driving characteristics in a broader context based on actual driving records and images.

Busan and Gyeongsangnam-do region host numerous significant wetlands, including the Nakdong River Estuary, one of the largest migratory bird habitats in East Asia, making it an essential habitat for waterbirds. However, issues such as wetland area reduction have arisen due to accelerated industrialization and urbanization since the 1980s. This study analyzed annual and monthly changes in waterbird populations and examined habitat use patterns and interrelationships among four wetlands in Busan and Gyeongsangnam-do: the Nakdong River Estuary (NRE), Lower Nakdong River (LNR), Junam Reservoir (JUR), and Upo Wetland (UPO), using waterbird data collected from 1999 to 2024. The results showed a decreasing trend in waterbirds at the NRE and UPO, while an increasing trend was observed at the LNR and JUR. Notably, populations of Anatidae decreased at the NRE and UPO but increased at the LNR and JUR, indicating that changes in Anatidae significantly influenced waterbird population trends. Monthly population fluctuations were particularly pronounced at the NRE and LNR. While the population decreased at the NRE after November, it increased at the LNR. This suggests that waterbirds moved to the LNR due to habitat and food resource reductions in the NRE. In contrast, the JUR and UPO exhibited weaker associations with the other sites. This study aims to contribute to future wetland management and waterbird conservation strategies in the Busan and Gyeongsangnam-do region.

In this study, we explored the design of improved road lighting for drivers and pedestrians using ray-tracing and reverse ray-tracing methods. Conventional road lighting often poses issues such as glare and unevenly illuminated areas, which can compromise safety and efficiency. These problems stem from traditional design approaches focused solely on achieving high luminance and electrical power. However, our research shows that higher brightness or power consumption does not necessarily equate to better road lighting. By applying ray-tracing techniques, we aimed to design a reflector that enhances visibility while being easier on the eyes of both drivers and pedestrians. Our optimized reflector design demonstrated significant improvements in both central and average illuminance levels, all while reducing energy consumption. This study suggests that careful reflector design is crucial for creating safer and more energy-efficient road lighting solutions.

In this study, we explored the design of improved road lighting for drivers and pedestrians using ray-tracing and reverse ray-tracing methods. Conventional road lighting often poses issues such as glare and unevenly illuminated areas, which can compromise safety and efficiency. These problems stem from traditional design approaches focused solely on achieving high luminance and electrical power. However, our research shows that higher brightness or power consumption does not necessarily equate to better road lighting. By applying ray-tracing techniques, we aimed to design a reflector that enhances visibility while being easier on the eyes of both drivers and pedestrians. Our optimized reflector design demonstrated significant improvements in both central and average illuminance levels, all while reducing energy consumption. This study suggests that careful reflector design is crucial for creating safer and more energy-efficient road lighting solutions.

본 연구에서는 baird paker agar (BPA)와 MC-media pad SA (MMPSA)의 황색포도상구균 검출효율과 정성 및 정 량 정확도를 비교하여 황색포도상구균 건조필름의 사용가 능성을 평가하였다. 본 실험에 사용된 재료는 마카롱(30건), 편육(30건) 및 김밥(30건), 총 90건을 실험 재료로 사용하 였다. 유통식품 90건의 황색포도상구균 검출효율 실험결과, BPA와 MMPSA의 검출효율은 48건(53.3%)으로 동일 하게 검출되었다. 또한 정량 정확도는 BPA와 MMPSA에 서 각각 2.0±0.8, 2.0±0.7 log CFU/g로 유의적인 차이가 나 타나지 않았다. 황색포도상구균의 정성 정확도 실험결과, BPA의 경우 97.7%, MMPSA의 경우 96.4%로 산출되어 유 의적인 차이가 나타나지 않았다. 황색포도상구균의 검출효 율, 정성과 정량 정확도 실험결과, BPA와 MMPSA 두 배지 에서 유의적인 차이가 나타나지 않아 황색포도상구균 정성 과 정량실험 시 MMPSA도 사용이 가능할 것으로 판단된다.

본 연구는 수도권 소재 D 대학을 중심으로 대학생활 적응양상(대인관 계, 학업활동, 진로준비, 개인심리, 사회체험)에 따른, 잠재계층을 분류하 고 그 영향요인(성별, 나이, 학년, 계열, 전형유형)을 살펴보려는 목적으 로 실시되었다. 연구 대상은 D대학에 재학중인 597명의 대학생이 포함 되었다. 분석결과는 다음과 같다. 첫째, 설명변수, 영향변수 간의 상관분 석에서 GPA(학업성취도)는 대인관계를 제외한 모든 대학생활적응 하위영 역과 통계적으로 유의한 관계가 있었으며, 상관계수는 정적으로 나타났 다. 둘째, 잠재계층분석에서는 4개의 집단으로 유형화되었다. 연구 대상 의 55%는 중도형 대학생활적응 집단(계층 1), 11%는 소극형 대학 생활 적응 집단(계층 2), 27%는 적극형 대학생활적응 집단(계층 3), 7%는 선 택형 대학생활적응 집단(계층 4)로 구분되었다. 셋째, 잠재계층 간 비교 에서는 계층3, 계층1, 계층2 형태는 성취 및 만족도 차이가 순서대로 낮 게 나타났으나, 계층 4의 경우는 성적 및 취업을 제외한 다른 영역에서 는 활동 및 참여가 적은 모습을 보였다. 본 연구는 입학유형에 따른 학 생들의 잠재적 특성을 밝혀내어, 이에 맞는 효과적인 학교생활적응 지원 방안을 모색하고자 하는 데 의의가 있다.

This review examines the importance of measuring practical enteric methane emissions from ruminants, considering their significant impact on global warming. Global warming is significantly driven by an increase in greenhouse gases, with rising methane (CH4) emissions from ruminants accelerating global warming recently. To successfully mitigate CH4 emissions and establish effective strategies, it is essential to apply reliable measurement techniques. This will allow for an accurate assessment of on-farm CH4 emissions. The priority should be to gather CH4 emission data that reflects the actual state of CH4 emissions from ruminants. The review provides an overview of the methods used to measure CH4 emissions from ruminants by compiling existing researches. It introduces the concepts, principles, and limitations of these methods to facilitate comparisons between existing approaches. This review discusses methods for measuring enteric CH4 emissions from ruminants at the farm level, including the tracer technique, laser methane detector, GreenFeed, and sniffer system. These methods are highlighted as potential tools to accumulate substantial data on on-farm CH4 emission from domestic animals with provides examples of international cases. Among these, this review introduces the Sniffer method, a CH4 emission measurement techniques that are suitable for on-farm use under domestic conditions, and emphasizes the necessity of its application. In addition, by presenting international cases where predictive models were developed based on on-farm CH4 measurement techniques, it is projected that if predictive models for CH4 emissions are developed by accumulating data at the farm level, it can contribute to sustainable livestock industry in various promising ways.