Current portable reference equipment used to evaluate the performance of vehicle detectors can collect traffic volume and speed only for the outermost lanes in each direction. Passing vehicles on the other lanes are manually counted by reviewing the recorded videos. Consequently, only traffic volume—without vehicle speed—is used as a reference value. This method is time-consuming for comparing the performance data from the equipment with the reference data and can compromise the performance evaluation. This study aims to enhance the efficiency of vehicle detection system (VDS) performance evaluations by developing multilane portable reference equipment that can accurately collect traffic information for lanes beyond the outermost lane or for more than two lanes. This study introduced the core technologies of multilane portable reference equipment and compared and analyzed the measurement accuracy of the developed equipment against data from fixed reference equipment operated by the Intelligent Transportation System (ITS) Certification and Performance Evaluation Center, following ITS performance evaluation criteria. The data from the fixed reference equipment were considered the true values, providing a basis for evaluating the accuracy of the measurements by the developed equipment. First, the accuracy of the vehicle length was determined by driving four test vehicles, each measuring 7,085 mm in length, 24–29 times in each lane. The accuracy was calculated by comparing the vehicle length data obtained from the fixed reference equipment with the actual vehicle length. A confidence interval was established for this accuracy. To assess the accuracy of the speed and occupancy time in relation to the accuracy of the analyzed vehicle length, we evaluated the error range of the vehicle length according to variations in speed and occupancy time. This analysis was based on the following relationship equation: “vehicle length = speed × occupied time – sensor spacing.” The analysis used data from approximately 16,000 vehicles, including the speed, occupancy time, and vehicle length, collected between 8:00 am and 12:00 pm on August 8, 2024. The principle behind measuring traffic volume and vehicle speed using multilane portable reference equipment involves detecting a vehicle by analyzing the time difference between the driver and passenger tires. The vehicle speed was calculated using the installation angle of the tire detection sensor and trigonometric functions. An analysis of the measurement accuracy revealed that the traffic volume accuracy of the outermost lane (the fourth lane) was 100% during both day and night. The speed accuracy was 98.8% during the day and 97.7% at night, representing the highest performance in these metrics. Additionally, the traffic volume accuracy for the innermost lane (the first lane), as measured by the detection sensor from the third lane, was more than 99.3% at all times, with a speed accuracy exceeding 96% during the day and night, that also demonstrated excellent results. The analysis results indicated that the multilane portable reference equipment developed in this study was suitable for evaluating the VDS performance. This equipment allowed the collection of traffic volume and speed data from all lanes, rather than only the outermost lanes. This capability enabled consistent analysis for each lane and enhanced efficiency by reducing the analysis time. Additionally, this is expected to improve the reliability of the performance evaluations.

A high-pressure in-situ permeation measuring system was developed to evaluate the hydrogen permeation properties of polymer sealing materials in hydrogen environments up to 100 MPa. This system employs the manometric method, utilizing a compact and portable manometer to measure the permeated hydrogen over time, following high-pressure hydrogen injection. By utilizing a self-developed permeation-diffusion analysis program, this system enables precise evaluation of permeation properties, including permeability, diffusivity and solubility. To apply the developed system to high-pressure hydrogen permeation tests, the hydrogen permeation properties of ethylene propylene diene monomer (EPDM) materials containing silica fillers, specifically designed for gas seal in high-pressure hydrogen environments, were evaluated. The permeation measurements were conducted under pressure conditions ranging from 5 MPa to 90 MPa. The results showed that as pressure increased, hydrogen permeability and diffusivity decreased, while solubility remained constant regardless of pressure. Finally, the reliability of this system was confirmed through uncertainty analysis of the permeation measurements, with all results falling within an uncertainty of 11.2 %.

Background: The Functional Movement Screen (FMS) is widely used for movement assessment but suffers from subjective scoring that leads to inconsistent evaluations. While previous studies have focused on reliability, the validity of AI-supported assessment remains unexplored. Objectives: To evaluate the reliability and validity of an AI-based motion analysis system using MediaPipe for three FMS movements. Design: Prospective reliability and validity study with repeated measures. Methods: Thirty healthy adults (age 23.4±2.8 years) performed three FMS tests (Deep Squat, Hurdle Step, Inline Lunge) recorded on video. Three evaluators (two experienced physical therapists and one novice) assessed recordings in three phases: Phase 1 involved traditional assessment by experts only to establish criterion reference, Phase 2 had all evaluators using AI support, and Phase 3 consisted of repeated AI-supported assessment. The AI system provided real-time visual feedback of joint angles and alignment through MediaPipe skeletal tracking. Results: Criterion validity showed strong agreement between traditional expert assessment and AI-supported assessment (r=0.94, P<.05). Inter-rater reliability improved from good (ICC=0.89) to excellent (ICC=0.91) with AI support. The novice evaluator achieved immediate expert-level performance with only 0.05 points difference from experts. Intra-rater reliability was excellent for all evaluators (ICC=0.84-0.89). Conclusion: The AI-based system demonstrated strong validity and improved reliability for fundamental movement assessment. While AI support enabled novice evaluators to achieve expert-level performance immediately, it may increase sensitivity to subtle movement variations. This technology shows promise for standardizing movement screening, though current limitations restrict its application to standing movements.

Nitrogen fertilizers are generally known to be of great help in improving crop yields, but excessive nitrogen fertilizer usage can not only destroy the environment but also negatively affect crop growth. This study aims to develop a decision-making system for optimal nitrogen fertilizer use for efficient production of Chinese cabbage (Brassica rapa), one of the major vegetables. The proposed system has the functions of detecting farmland based on satellite images, predicting cabbage yields and greenhouse gas (e.g., nitrous oxide) emissions according to nitrogen fertilizer use, and making decisions using the prediction results. To develop the proposed system, a generalized prediction model is developed using experimental data collected from South Korea, Egypt, India, Canada, Lithuania, and China, and the effectiveness of the proposed system is validated through experiments. As a result, the proposed system will enable farmers to conduct eco-friendly agricultural activities through appropriate nitrogen fertilizer use while stably maximizing productivity of Chinese cabbages.

기후위기 대응과 탄소중립 실현을 위한 전략으로 해상풍력발전이 주목받고 있 으며, 한국 정부도 이를 국가 에너지 정책의 핵심 축으로 삼아 대규모 확대를 추진 중이다. 그러나 해상풍력은 어업, 환경, 지역사회 등 다양한 해양 이용 주 체들과의 이해 충돌 속에서 추진되고 있으며 이로 인한 갈등은 사업 지연 또는 무산으로 이어지는 사례가 늘고 있다. 본 연구는 해상풍력 발전과 관련된 법 적·사회적 갈등 중에서도 어업손실 보상제도에 초점을 맞추어 현행 제도의 문제점을 분석하고 제도 개선 방향을 제시하였다. 연구 결과 현재의 어업손실 보상제도는 법적 근거가 미흡하고 보상 대상 범위 가 제한적이며, 손실 산정 기준 역시 현실과 괴리가 크다는 문제가 확인되었다. 특히 민간사업자의 경우 법적 보상 협의 의무가 명확하지 않아 사업자와 어민 간 갈등이 장기화되고 있다. 해외 주요국 사례(영국, 대만, 덴마크)를 분석한 결 과 이들 국가는 제도화된 협의 절차, 어민 참여형 평가 시스템, 정교한 피해 산정 기준을 통해 갈등을 최소화하고 있었다. 이에 본 논문은 해상풍력 어업손실 보상제도의 법제화, 현실적 산정 기준 마련, 어업 증빙을 위한 정보화 기반 구축을 핵심 과제로 제안한다. 이는 단순한 보 상을 넘어 지역사회와의 상생과 지속가능한 해상풍력 확산을 위한 제도적 기 반이 될 수 있다.

본 연구는 다시마 양식을 위한 통합 자동화 시스템을 개발하고, 이를 통해 생산성, 비용 효율성, 환경적 지속 가능성을 모두 개선하는 데 중점을 두고 있다. 기존의 노동 집약적 수확 방식과 넓은 공간을 필요로 하는 수평 건조 방식은 비효율적이며, 환경적 부작 용을 초래했다. 이에 본 연구는 자동화된 수확 시스템, 해상-육상 연계 운송 시스템, 그리고 수직 건조 시스템을 통합적으로 개발하여 양 식업의 생산성을 극대화하고 자원 사용을 최적화하였다. 자동화된 수확 시스템은 작업 속도를 약 35% 향상시켰으며, 작업의 일관성을 유지하여 품질 오차율을 2% 이하로 줄이는 성과를 보였다. 해상-육상 연계 운송 시스템은 모듈형 컨테이너를 활용하여 운송 중 손상률 을 기존 15%에서 5%로 감소시켰고, 운송 시간을 평균 6시간에서 4시간으로 단축하였다. 또한, 수직 건조시스템은 고밀도 적재와 자연 대류 방식을 도입하여 건조 시간을 기존 48시간에서 28시간으로 40% 단축하였으며, 에너지 소비를 25% 감소시켰다. 이러한 시스템은 데이터 기반으로 설계 및 검증되었으며, 통합적으로 양식업의 경제성 향상과 환경적 부담 감소를 동시에 실현하였다. 본 연구의 결과는 다른 해조류 양식에도 적용 가능하며 지속 가능한 해양 자원 관리에 기여할 것으로 기대된다.

병충해의 조기 발견과 그에 따른 조치의 중요성은 농업 및 생태계 보전에 있어서 핵심적이다. 그러나 초기에는 일반적인 카메라나 센 서로는 변화의 정도를 관측하기 어렵다. 이러한 한계를 극복하기 위해 초분광 모듈을 활용하여 파장대별 식물 데이터를 관측함으로써, 딥러닝 모델을 통해 가로수 식생의 건강 상태를 판별, 병충해 여부를 초기에 확인 가능하다. 이를 통해 조기에 병충해에 대해 조치함 으로써 더 큰 피해를 방지할 수 있다. 이러한 접근 방식은 농업 및 생태학 분야에서 식물의 건강을 모니터링하고 보전하는 데 적극적 으로 연구되고 있다.

This study was conducted in the San Pedro Department to determine the impact of different soil management practices on sesame productivity. Different tillage methods (conventional deep tillage, minimum tillage, and no-tillage), crop rotations (monoculture, double, and triple rotation), various combinations of green manure, and appropriate doses of chemical fertilizers were studied. The results revealed that the no-tillage method combined with crop rotation (corn-cotton-sesame) and fertilization had the highest productivity of 1,548 kg/ha. In contrast, the conventional deep tillage method without fertilization showed the lowest productivity with 614 kg/ha. Incorporation of summer green manures (Mucuna pruriens) in minimum tillage methods with fertilization significantly improved productivity (1,010 kg/ha) in comparison with the same tillage method and fertilization but without Mucuna (720 kg/ha), which highlights the synergistic effects of combining green manures with chemical fertilizers. The treatment of winter green manures consisting of black oat + white lupine and black oat + radish has also significantly improved the productivity of sesame with 904 and 900 kg/ha, respectively, compared to the non-use of winter green manure and the use of chia, which had productivities of 695 and 298 kg/ha, respectively. The best chemical fertilization doses of nitrogen (urea 45% N), phosphorus (46% P2O5), and potassium (60% K2O) were determined through tests with increasing doses of each nutrient, maintaining 40 kg/ha as the base for the other two. The highest productivity was obtained with N, P, and K levels of 70 kg/ha each, resulting in productivities of 1,421, 1,522, and 1,486 kg/ha. However, the maximum profit compared to the input is obtained with doses of 50 kg/ha for N and 60 kg/ha for P and K, giving a productivity of 1,390, 1,510, and 1,421 kg/ha, respectively.