초당옥수수는 고당도 옥수수 품종으로, 식단 트렌드 변화와 천연 당류에 대한 관심 증가로 인해 수요가 증가하면서 재배가 확대되고 있다. 초당옥수수는 높은 당도로 매우 달고 맛이 좋지만, 전분 함량이 낮아 일반 옥수수에 비해 발아율이 낮은 특징이 있다. 본 연구는 초당옥수수 계통의 전분 함량과 발아율의 상관관계를 조사하여, 우수한 생장과 발아율을 갖춘 고품질 계통을 선발하는 것을 목표로 하였다. 본 연구에서는 10개의 초당옥수수 계통을 대상으로 발아율과 식물체 생장 특성을 평가하였다. 모든 계통이 80% 이상의 발아율을 보였으며, KH51 계통이 53일로 가장 출사일이 빨랐고, KH29W 계통이 148cm로 간장이 가장 크게 나타났다. 고당도 계통을 선발하기 위해 수정 후 20일째에 이삭을 수확하여 유리당 함량을 측정하였다. KH28W 계통이 가장 높은 당 함량(23.3%)을 보였으며, KH45 계통이 가장 낮은 당 함량(8.1%)을 나타냈다. 또한, 전분 함량이 유리당과 비례하여 축적되는지를 확인하기 위해 수분 후 40일째에 이삭을 수확하여 분석한 결과, KH47 계통이 가장 높은 전분 함량(30.1%)을, KH28W 계통이 가장 낮은 전분 함량(23.6%)을 보였다. 전분 함량이 발아에 미치는 영향을 평가하기 위해 발아와 관련된 효소 및 유전자들을 분석하여, 발아 과정에서의 효소 활성 및 유전자 발현 수준을 측정하였다. 낮은 전분 함량은 발아 초기에 효소 활성과 유전자 발현을 저하시켜 발아 지연 및 불균일성을 초래하였으나, 발아 후 생장에는 큰 영향을 미치지 않았다. 이는 초당옥수수 종자의 초기 발아 과정이 유리당과 전분 함량에 의해 영향을 받을 수 있음을 시사한다.

전국 태양광 발전시설의 효율적인 보급을 위해 9개 도 지역별 기상 데이터를 활용한 DEA(Data Envelopment Analysis) 효율성 분석 결과를 도출하고자 한다. 국내 태양광 중심으로 설비보급과 발전 비중이 빠른 속도로 증가 중이며 재생에너지 전력 생산의 효율적 개편을 위해 기후변화에 따른 기상 예측 정보를 활용하고 있다. 본 연구는 신재생 에너지 정책의 시사점이 높았던 2020∼2022년의 기상청 데이터와 과거 30년 평균(1981년 ∼2012년) 데이터를 기준으로 일사량 변화에 의한 발전량 예측 모델을 시뮬레이션했다. 특히 기상 데이터와 실제 발전량 사이 관계를 분석하여 투입 산출 변수와 관련 있는 연구모형의 효율성을 파악하였다. 태양광 발전시설의 안정적인 운영과 관리를 통해 최상의 발전시설 상태를 유지하고, 전력량을 끌어올리기 위해 전문적이고 차별화된 운영관리 (O&M) 서비스 제공이 필요하다.

본 연구에서는 한국의 겨울철 강수량이 음()과 양(+)의 극값으로 각각 관측된 2021/2022년과 2023/2024년 사 례를 중심으로, 북극 성층권부터 열대 태평양까지 이어지는 전구 규모 대기 변동이 동아시아 대륙-북서 태평양을 거쳐 중국 동부-황해-한국 지역 대류권 하층 강수 발생 메커니즘에 어떻게 작용하는지를 규명하였다. 1991-2024년 동안 한국 겨울철 강수량은 연평균 0.55±0.80 mm yr1 , 강수일수는 0.04±0.08 day yr1로 증가하였으나, 2021/2022년에는 74.9 mm, 2023/2024년에는 +150.1 mm의 극단적 아노말리가 발생했다. 2021/2022년 겨울에는 북극 성층권 냉각으로 강한 극소용 돌이가 발달해 중위도 대류권 상층이 온난해졌으나, 티벳 고원의 눈 덮임으로 형성된 한랭 고기압이 중국 동부-황해-한 국에 북서풍을 강화하고 수증기 발산을 유도함으로써 강수량이 크게 줄었다. 반면 2023/2024년 겨울에는 성층권 돌연 승온과 엘니뇨가 겹쳐, 서태평양-남동아시아 해역 해수면 온도가 양(+) 편차를 보이는 가운데 온난 고기압이 대류권 하 층 남서풍을 강화해 수증기 수렴과 구름 생성을 촉진하여 극단적인 강수량 증가로 이어졌다. 결국 북극-열대 태평양 간 그리고 동아시아 대륙-북서 태평양 간 외부 요인이 내부 요인들과 복합적으로 작용해 한국 겨울철 강수량 극값 변동을 유발함이 확인되었으며, 이는 겨울 몬순 기후 예측 및 이해에 중요한 단서를 제공한다.

역사적으로 빈곤층을 대상으로 한 반빈곤 정책은 전통적인 빈민 구호 방식에서 인적 자본 형성과 경제 참여를 촉진하는 사회투자 전략으로 전 환되어 왔다. 미국의 개인발달계좌 (Individual Development Accounts, IDAs) 의 경우, 저소득층이 발달적 목표를 위한 자산을 축적하도록 장려 하고, 이를 통해 지속 가능한 경제적 안정을 달성하도록 설계된 대표적 인 자산형성 프로그램이다. 한국에서도 2010년부터 저소득층을 위한 자 산형성지원사업을 도입하였으나 프로그램의 주된 목표는 탈수급을 유도 하는 것이어서, 사회투자 전략에 기반한 장기적인 발달 목표를 지원하는 데는 한계가 있었다. 이에 본 연구는 빈곤층을 위한 자산형성 개념을 재 조명하고, 한국의 자산형성프로그램에 대한 시사점을 찾아보고자, 저소득 층을 위한 개인발달계좌의 원형적 시범 사업인 아메리칸 드림 시범사업 (American Dream Demonstration, ADD) 프로젝트를 주요 사례로 분 석하였다. 이를 위해 David Gil의 정책분석 틀을 적용하였고, ADD의 주 요 쟁점, 가치 전제, 제도적 메커니즘, 주요 성과와 시사점, 상호작용을 제시하였다. 끝으로 한국의 자산형성지원사업이 ADD에 내재된 사회투자 개념을 잘 활용할 수 있도록 정책 대안을 제시하였다.

This study explores trends in skincare products for pregnant women using text mining to analyze consumer preferences for safety and functionality. Data were collected from Naver blogs, cafes, and Facebook between September 2023 and August 2024 and processed using the Textom platform. Through text mining and semantic network analysis, 50 significant keywords were selected, and centrality measurements such as degree and eigenvector centrality were applied to assess keyword importance. CONCOR analysis categorized these keywords into structural equivalence groups, revealing key consumer priorities, including ingredient safety, moisturizing properties, and product recommendations. The findings highlight the growing demand for dual-purpose skincare products suitable for both pregnant women and infants, as well as the increasing influence of consumer reviews in product selection. Academically, this research underscores the effectiveness of text mining in understanding niche consumer markets. However, the study's reliance on specific online platforms presents a limitation, as it may not fully represent broader consumer preferences. Future research should incorporate diverse data sources and quantitative analyses to further validate product efficacy and consumer satisfaction.

Various road traffic signs are placed on the shoulder to inform drivers of the work situation ahead, speed limits, and lane changes in highway work zones. In this study, we analyze the effectiveness of a portable lane-change assistance system (PLCS) that can replace existing traffic signs from the perspectives of driver visibility and lane-change behavior. The existing highway work zone traffic management guidelines were regarded as a scenario without PLCS, and the case of replacing the existing traffic signs proposed by the manual with PLCS was set as a scenario with PLCS. For each analysis scenario, we analyzed the change in subjective awareness of traffic signs, perception accuracy of PLCS, advance lane-change rate, and lane-change location. The subjective perception analysis showed that the subjective perception change rate increased by 13.85% for two-lane highways and 5.29% for three-lane highways when PLCS was applied compared to that without PLCS. Regarding PLCS perception accuracy, all drivers correctly recognized the lane closure information for the two-lane case. Two PLCS are used in the three-lane case to provide lane-closure information. Regarding the first PLCS, all drivers correctly recognized lane closure information for the first lane sign, and 31 drivers correctly recognized lane closure information for the second and third lane signs. Regarding the second PLCS, all drivers correctly recognized lane closure information for the first and third lane signs, and 30 drivers correctly recognized lane closure information for the second lane sign in the second PLCS. Analysis of lane-change behavior showed that the proportion of advance lane changes increased by 31.25% in the two-lane case and 59.38% in the three-lane case with PLCS compared to that without PLCS. Additionally, lane-change locations where drivers performed lane changes from the starting point of the work zone area were analyzed. Drivers changed lanes at 653.68 m without PLCS and at 919.66 m with PLCS resulting in a 265.98 m increase in lane change location for the two-lane case. The drivers changed lanes twice in the three-lane scenario. Drivers changed lanes at 1014.41 m and 743.64 m without PLCS and at 1137.05 m and 868.24 m with PLCS, resulting in a 122.64 m and 124.60 m increase in the lane change location for the three-lane case. The proposed PLCS demonstrated a greater recognition capability than existing traffic signs and was effectively encouraged. This can be useful for replacing existing traffic signs in highway work zones.

Until all vehicles are equipped with autonomous driving technology, there will inevitably be mixed traffic conditions that consist of autonomous vehicles (AVs) and manual vehicles (MVs). Interactions between AVs and MVs have a negative impact on traffic flow. Cloverleaf interchanges (ICs) have a high potential to cause traffic accidents owing to merging and diverging. Analyzing the driving safety of cloverleaf ICs in mixed traffic flows is an essential element of proactive traffic management to prevent accidents. This study proposes a comprehensive simulation approach that integrates driving simulation (DS) and traffic simulation (TS) to effectively analyze vehicle interactions between AVs and MVs. The purpose of this study is to identify hazardous road spots for a freeway cloverleaf IC by integrating DS and TS in mixed traffic flow. The driving behavior data of MVs collected through a DS were used to implement vehicle maneuvering based on an intelligent driver model in the TS. The driving behavior of the AVs was implemented using the VISSIM parameters of the AVs presented in the CoEXist project. Additionally, the market penetration rate of AVs, ranging from 10% to 90% in 10% increments, was considered in the analysis. Deceleration rate to avoid crashes was adopted as the evaluation indicator, and pinpointing hazardous spot technique was used to derive hazardous road spots for the cloverleaf IC. The most hazardous road spot was identified in the deceleration lane where greater speed changes were observed. Hazardous road spots moved downstream within the deceleration lane as traffic volumes increased based on level of service. The number of AVs decelerating stably increased as traffic increased, thereby improving the safety of the deceleration lane. These results can be used to determine the critical point of warning information provision for preventing accidents when introducing AVs.

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.

In this study, we aim to classify personal mobility (PM)-related traffic crash data into four categories: PM-to-vehicle, PM-to-pedestrian, PM-single, and vehicle-to-PM crashes, and analyze the factors influencing the severity of each crash type. To overcome the limitations of existing studies in explaining the impact of independent variables on ordinal dependent variables, a random forest model was combined with the Shapley additive explanation technique. This approach visualizes the influence of independent variables on a dependent variable, providing clearer insights and enhancing interpretability. The analysis of PM traffic accidents, categorized into at-fault, single-vehicle, and victim accidents, revealed distinct key factors for each type. The main contributors to the severity of crashes caused by PM are traffic violations by teenagers and collisions with elderly pedestrians. Single-vehicle accidents were predominantly caused by overturn incidents, with inadequate driving skills among PM users aged 40 years and older, and significantly increasing severity. Victim accidents primarily occur at intersections, where the behavior of the at-fault driver and age of the PM user are critical factors influencing the severity. We identified various factors influencing the severity of PM crashes by type, highlighting the need for tailored policy measures. Proposed policies include physically separating bicycle–pedestrian shared spaces and strictly regulating illegal PM sidewalk riding, introducing PM licenses for teenagers to ensure compliance with traffic rules, and implementing regular safety education programs for all age groups. Although this study applied a new analytical technique, it relied on limited crash data, thus limiting the results to estimates.

In this study, we analyze the design preferences of parking spaces for shared e-scooters. The detailed purposes are to develop the attributes and attribute levels for the design of shared e-scooter parking spaces, derive profiles by combining the attributes and attribute levels of parking space design, collect preference data on parking-space design from shared e-scooter users, and analyze the preferences for parking space design. The attributes and attribute levels for the design of shared e-scooter parking spaces were developed based on a literature review and an investigation of shared e-scooter parking spaces. Using the full profile method and orthogonal design, the profiles were derived by combining the attribute levels. Preference data for parking space profiles were collected from shared e-scooter users using survey cards to visualize the profiles. Preferences for parking-space design were analyzed using conjoint analysis. Through a literature review and case studies, three attributes: parking angle and direction, parking unit, and parking method, along with their attribute levels were developed. By combining the attributes and their levels, 16 profiles for parking spaces were created. Preference data for these parking-space profiles were collected from 278 shared e-scooter users using a 10-point Likert scale. Using conjoint analysis, the utility and importance of the attributes and attribute levels for parking space design were analyzed. A parking-space design plan that considers the preferences of shared e-scooter users was proposed. The utilities of the attribute levels for shared e-scooter parking space design were derived. Among the attribute levels, the 'compact parking unit' showed the highest utility for the parking unit, whereas 'head-in parking' had the highest utility for the parking method. For parking angle and direction, 'perpendicular parking' had the highest utility, followed by '45°, direction toward the facility’s passageway.' The importance of the attributes for shared e-scooter parking space design was also derived, with 'parking angle and direction' being the most important attribute. Finally, a parking space design plan for shared e-scooters was proposed using visualized survey cards.