AlN thin film is highly valued for use as a high-temperature material because of its excellent heat resistance, thermal conductivity and high mechanical strength. In addition, it is known as a replacement material for ZnO, because it can be applied to surface acoustic wave elements and high-frequency filters using piezoelectric properties or sound velocity. In this study, an alternating sputtering method was used to fabricate an AlN thin film with excellent film quality. The c-axis orientation and residual stress of the fabricated AlN thin film were measured using an X-ray diffraction method. Nitrogen gas pressure and target electrode conversion time are important deposition conditions when producing a thin film using the alternating sputtering method. The AlN thin film fabricated on the glass substrate using the alternating planar magnetron sputtering method exhibited a crystal structure in which the c-axis was preferentially oriented in the normal direction of the substrate surface. The c-axis orientation was better when the target electrode switching time was short under the condition of low nitrogen gas pressure. Residual stress is tensile stress in the very low nitrogen gas pressure range (PN ≤ 0.3 Pa), compressive stress in the low nitrogen gas pressure range (0.3 < PN < 0.9 Pa), and in the high nitrogen gas pressure range (PN ≥ 0.9 Pa), it becomes tensile stress. Residual stress shows tensile stress when the switching time is short, tensile stress decreases as the switching time increases, and becomes compressive stress when the switching time is sufficiently long (300 to 600 s). Compared to the simultaneous sputtering of two targets, the use of the alternating sputtering method can produce a high-quality thin film with excellent c-axis orientation and low residual stress.

중앙버스전용차로는 일반 도로 대비 높은 교통량과 반복적인 축하중이 작용하는 구간으로, 정차 및 출발 과정에서 발생 하는 국부적인 응력 집중으로 인해 포장 파손이 빈번하게 발생한다. 그러나 기존 도로 설계에서는 정적인 교통량을 기준 으로 축하중을 산정하여, 실제 교통 환경에서의 버스 유형별 차이, 재차 인원, 시간대별 하중 변화 등 동적인 요소를 충 분히 반영하지 못하는 한계가 존재한다. 이에 본 연구에서는 대중교통 빅데이터를 활용하여 중앙버스전용차로의 버스 유 형 및 시간대별 재차 인원을 반영한 새로운 축하중 산정 모델을 개발하였다. 이를 위해 서울시 열린 데이터 광장의 교통 정보를 활용하여 버스 유형 및 시간대별 재차 인원 데이터를 수집하고, 카카오맵 및 네이버 로드뷰 데이터를 이용해 결 측치를 보완하여 데이터셋을 구축하였다. 구축된 데이터셋을 활용하여 기존 ESAL(Equivalent Single Axle Load) 방식과 비교 분석한 결과, 새로운 축하중 모델에서는 기존 방식 대비 평균 111.8% 높은 축하중이 산정되었으며, 일부 구간에서 는 최대 128.9%까지 차이가 발생하는 것으로 나타났다. 이는 기존 포장 설계가 중앙버스전용차로의 실질적인 교통 하중 을 충분히 반영하지 못하고 있음을 시사하며, 추가적으로 버스 중하중의 가·감속의 영향을 고려한다면, 시간대별·노선별 실시간 축하중 변화를 보다 정밀하게 분석할 수 있으며, 이를 통해 과소 산정된 설계 하중을 보완하고 포장 공용성을 향 상시킬 수 있는 최적의 설계 및 유지보수 전략 수립이 가능할 것으로 기대된다.

인공지능의 발전은 검색엔진, SNS, ChatGPT 등 다양한 분야에서 혁신을 이끌며 사회와 산업 전반에 변화를 가져오고 있다. 특히, 교 통 분야에서는 AI 기반 기술이 교통정보 수집 및 분석 방식에 변화를 주며, 새로운 활용 가능성을 제시하고 있다. 과거 육안 계수 방 식에 의존했던 교통량 조사는 현재 CCTV 영상과 딥러닝 객체 인식 기술을 활용해 신뢰성과 정확성이 크게 향상되었다. AI 기반 교통 솔루션의 도입으로 교통량 조사 데이터는 정책 수립, 운영 개선, 사회간접자본 건설 등 다양한 분야에서 중요한 기초 자료로 활용되고 있다. 이에 본 연구에서는 YOLO v8을 활용하여 차량 축 인식 기반 차종 분류의 정확성을 향상시키고, 기존 촬영 기법과 비교·분석을 통해 최적의 인식기법을 제시하고자 한다.

This study addresses the critical challenge of enhancing vehicle classification accuracy in traffic surveys by optimizing the conditions for vehicle axle recognition through artificial intelligence. With current governmental traffic surveys facing issues—particularly the misclassification of freight vehicles in systems employing a 12-category vehicle classification—the research proposes an optimal imaging setup to improve axle recognition accuracy. Field data were acquired at busy intersections using specialized equipment, comparing two camera installation heights under fixed conditions. Analysis revealed that a shooting height of 8.5m combined with a 50°angle significantly reduces occlusion and captures comprehensive vehicle features, including the front, side, and upper views, which are essential for reliable deep learning-based classification. The proposed methodology integrates YOLOv8 for vehicle detection and a CNN-based Deep Sort algorithm for tracking, with image extraction occurring every three frames. The axle regions are then segmented and analyzed for inter-axle distances and patterns, enabling classification into 15 categories—including 12 vehicle types and additional classes such as pedestrians, motorcycles, and personal mobility devices. Experimental results, based on a dataset collected at a high-traffic point in Gwangju, South Korea, demonstrate that the optimized conditions yield an overall accuracy of 97.22% and a PR-Curve AUC of 0.88. Notably, the enhanced setup significantly improved the classification performance for complex vehicle types, such as 6-axle dump trucks and semi-trailers, which are prone to misclassification under lower installation heights. The study concludes that optimized imaging conditions combined with advanced deep learning algorithms for axle recognition can substantially improve vehicle classification accuracy. These findings have important implications for traffic management, infrastructure planning, road maintenance, and policy-making by providing a more reliable and precise basis for traffic data analysis.

V-type coupling, which is often applied to wastegate-turbochargers(WGT), is a mechanical fastener. Its radial forces generated from the bolt pretension load colse contact with each other to the axial direction for turbine housing and center housing rotating assembly(CHRA). In addition, the torsional stiffness between two bodies should be sufficiently secured to minimize the linkage angle change from the EWGA to the valve spindle. Therefore, in this study, the torsional stiffnesses according to the effects of positioning pins and friction coefficient, and the bolt pretension loads were calculated for V-coupling turbocharger. As a result, it can be seen that the torsional stiffness of the coupling according to the number of position pins is very small. And, when the friction coefficient and the axial force of the bolt are large, the torsional stiffness is greatly increased, and gradually decreasing when the bolt load of the coupling is about 6,000 N or more.

In the case of the Pohang earthquake, which had a magnitude of 5.4 in 2017, geotechnical damages such as liquefaction and ground settlement occurred. The need for countermeasures has emerged, and experimental research in the Pohang area has continued. This study collected undisturbed samples from damaged fine-grained soil areas where ground settlement occurred in Pohang. Cyclic tri-axial tests for identifying the dynamic characteristics of soils were performed on the undisturbed samples, and the results were analyzed to determine the cause of ground settlement. As a result of the study, it was determined that in the case of fine-grained soils, ground settlement occurred because the seismic load as an external force was relatively more significant than the shear resistance of the very soft fine-grained soils, rather than due to an increase in excess pore water pressure.

European and Turkish rice varieties were analysed to identify the traits associated with low-temperature germination. The aim of the study is to develop new rice varieties that can use these traits to reduce greenhouse gas emissions in rice fields. The average low temperature germination ratio (GR) in the European and Turkish rice varieties was 89.0±14.1%. The speed of the germination rate (SG) in Korean early maturing varieties, ‘Jopyeong’ and ‘Baekilmi’ was 1.3 and 3.5, respectively, whereas the European and Turkish varieties had a SG of 6.6. In terms of germination energy (GE) by the date, the European and Turkish varieties started germination within 4 days, while ‘Jopyeong’ and ‘Baekilmi’ began to germinate after 8 and 10 days, respectively. The mean germination time (MGT) for the European and Turkish varieties was 9.9±1.2 days. Between 4 to 10 days after inoculation, the germination velocity coefficient (GVC) for the European and Turkish varieties increased moderately from 2.6 to 5.3. After 10 days, the GVC rose rapidly from 7.0 to 12.0. ‘Jopyeong’ and ‘Baekilmi’ had slower germination rates compared to the European and Turkish varieties, in which the GVC increased moderately to 3.2 and 2.3, respectively, between 7 and 9 days after inoculation. The average mesocotyl elongation ability was 4.0±0.4 cm, with a range from 1.3 cm to 7.3 cm.

Injection molding is a process of shaping resin materials by heating them to a temperature above their melting point and then using a mold. The resin material is injected into and cooled within the mold cavity, solidifying into the desired shape. The core and cavity components that make up the mold cavity are crucial elements for the precision molding in injection molding. In the case of precision mold production, the application of 5-axis machining technology is required to ensure high machining quality for complex shapes, and among these factors, the tool angle is a critical machining condition that determines the surface roughness of the workpiece. In this study, we aim to measure the surface roughness of the machined surface of KP4A specimens during machining processes with variations in the tool angle and analyze the correlation between the tool angle and surface roughness.

In this research, a new piston pinhole boring machine for simultaneous 3-axis machining using linear motor and tilting unit is developed. We propose a new method that combines the linear motor and tilting unit to overcome the limitations of existing techniques. By using the linear motor, we suggest oval machining of piston pin holes. The horizontal reciprocating motion of the linear motor allows for oval machining, creating horizontal or vertical ovals on the pin holes based on the spindle tool's rotation angle. For profile machining of piston pin holes, we propose the use of a tilting unit that converts servo motor motion into linear motion. The vertical motion of the tilting unit enables profile machining, allowing the spindle tool connected to it to translate vertically during spindle rotation and shape the pin holes. To ensure simultaneous oval and profile machining, we suggest channel synchronization, separating the oval and profile machining channels. Synchronizing these channels enables both oval and profile machining to be performed simultaneously on the pin holes. In summary, this research aims to develop a piston pinhole boring machine that effectively utilizes the linear motor and tilting unit for accurate and productive pin hole machining, achieving simultaneous 3-axis machining.

본 연구에서는 DWI 적용 시 X축 거리에 따른 신호 손실과 인공물 발생 여부를 SS-EPI 기법과 비교 분석하여, MS-EPI 기법의 특성을 제시하고 임상 적용 관련 기초자료를 제시하고자 하였다. 3.0T 자기공명영상장치와 팬텀을 사용 하여 자기장 중심축과 좌우 끝 지점 ±3cm, 3번씩 움직여 표준 영상인 T2 강조영상과 SS-EPI DWI, MS-EPI DWI(RESOLVE) 축상면 영상을 획득하였다. 각 동일 부위에서의 SS-EPI DWI, MS-EPI DWI 영상을 T2 강조영상과 감산하여 신호 손실 직경을 측정하여 정량적 분석을 하였다. 정성적 평가는 나이퀴스트 허상과 기하학적 왜곡과 신호 손실, 인공물 발생 여부를 방사선사 3명이 비교평가 하였다. 두 기법 모두 오프 센터(off-center)로 이동할수록 신호 손실구간 또는 기하학적 왜곡이 나타나는데, 특히 MS-EPI 기법에서는 좌우 신호 손실 현상이 매우 증가해 –25, +25 cm 구간에서 는 약 50% 길이가 감소하였다. MS-EPI 기법은 근골격계 질환에서 기존에 매우 높은 영상 유용성을 인정받고 있다. 그러 나 k-공간을 분할 하여 채우는 MS-EPI 기법은 오프 센터의 낮은 공간 주파수 획득 시 위상변동 보정이 안 되어 신호 손실구간이 나타나며, 이에 관한 연구는 전혀 없는 실정이다. 이에 따라 본 연구는 기존의 선행 연구에서의 보여주지 못한 임상적 적용 시 MS-EPI 기법의 문제점을 파악하면서 이러한 정보를 공유하고 추가적인 연구에 토대가 될 수 있는 기초를 마련했다는 점에 의의가 있다.

Hydrogen infrastructure, for instance, such as hydrogen stations, supply chain network, is important in society of hydrogen economy. Special alloy are frequently used to prevent the hydrogen embrittlement in hydrogen vehicles, semiconductor factories and so on. Because special alloy including Monel material has high strength and high hardness, it is known as the hard-to-cut or roll material. This paper aims to investigate the characteristics and safety on bearing and shaft, which consist of key parts of rolling unit, through structural analysis. As the results, it showed that the bearing was weaker than shaft. Further the bearing was safe up to 20.4 ton, which was about 2 times of maximum of roller reaction force in case of considering as static load. However, the bearing was safe up to 10.2 ton in case of considering as repeated load.