PURPOSES : This study aimed to compare the object detection performance based on various analysis methods using point-cloud data collected from LiDAR sensors with the goal of contributing to safer road environments. The findings of this study provide essential information that enables automated vehicles to accurately perceive their surroundings and effectively avoid potential hazards. Furthermore, they serve as a foundation for LiDAR sensor application to traffic monitoring, thereby enabling the collection and analysis of real-time traffic data in road environments. METHODS : Object detection was performed using models based on different point-cloud processing methods using the KITTI dataset, which consists of real-world driving environment data. The models included PointPillars for the voxel-based approach, PartA2-Net for the point-based approach, and PV-RCNN for the point+voxel-based approach. The performance of each model was compared using the mean average precision (mAP) metric. RESULTS : While all models exhibited a strong performance, PV-RCNN achieved the highest performance across easy, moderate, and hard difficulty levels. PV-RCNN outperformed the other models in bounding box (Bbox), bird’s eye view (BEV), and 3D object detection tasks. These results highlight PV-RCNN's ability to maintain a high performance across diverse driving environments by combining the efficiency of the voxel-based method with the precision of the point-based method. These findings provide foundational insights not only for automated vehicles but also for traffic detection, enabling the accurate detection of various objects in complex road environments. In urban settings, models such as PV-RCNN may be more suitable, whereas in situations requiring real-time processing efficiency, the voxelbased PointPillars model could be advantageous. These findings offer important insights into the model that is best suited for specific scenarios. CONCLUSIONS : The findings of this study aid enhance the safety and reliability of automated driving systems by enabling vehicles to perceive their surroundings accurately and avoid potential hazards at an early stage. Furthermore, the use of LiDAR sensors for traffic monitoring is expected to optimize traffic flow by collecting and analyzing real-time traffic data from road environments.

오대산국립공원의 고등균류 다양성 및 분포 특성을 시기별, 고도별, 임상별로 조사하여 비교하였다. 오대산국립공원 내 계방산, 소금강, 월정사지 구 일대에 임상별 6개씩 총 18개의 고정조사구에서 고등균류를 채집한 결과, 542점의 표본을 채집하였으며, 동정한 결과 81속, 256종으로 확인되었 고 최신분류체계로 분류한 결과 2문, 6강, 19목, 56과로 확인되었다. 부생성 균류가 62.9 %로 가장 높은 비율을 보였으며, 다음으로는 공생성 균류 36.2 % 기생성 균류 0.9 % 순으로 조사되었고, 우점종은 맑은애주름버섯(Mycena pura)과 굽은꽃애기버섯(Gymnopus dryophilus)으로 확인되었다. 해발고도에 따른 고등균류의 분포는 200∼677 m 조사구에서 109종, 700∼999 m에서 109종, 1000∼1400 m에서 118종이 조사되었 으며, 채집 시기별 고등균류의 분포는 9월에 132종으로 가장 많이 조사되었고, 6월 33종, 7월 75종, 8월 99종으로 조사되었다. 임상별로는 혼효림에서 124종, 활엽수림 121종, 침엽수림에서 가장 낮은 105종이 조사되었다. 고도별, 시기별, 임상별 모두 부생성 균류가 가장 높은 비율로 분포하였다. 종다양도는 9월에 2.00, 혼효림에서 2.04로 가장 높았고, 고도별로는 유사한 종다양도를 나타냈다(1.93∼1.99). 종 균등도는 고도별, 시기별, 임상별로 비슷한 수준을 나타냈다(0.94∼0.97). 공통 발생 종은 모든 시기에 2종, 전체 고도에서 7종, 침엽수, 활엽수, 혼효림에서 14종이 확인되었다.

Disaster and safety budget can be characterized as a large-scale public asset on which the government has a significant role. It is of a crucial importance to properly allocate the limited national budget to various areas as necessary. Higher investment efficiency of the budget related to disaster and safety management requires distribution criteria based on relevance and efficiency. Currently, the budget related to disaster and safety management is orchestrated through the prior consultation system. However, there is still no clear framework for reviewing the investment direction and setting the priority investment areas by prior consultation. This study analyzes the status and characteristics of disaster and safety management projects by damage type and proposes a structured system for prioritization. This framework can be useful in selecting the areas that need priority investments by damage type of disaster and safety management projects, thereby contributing to improving investment efficiency.

Geo-structures such as levee and cut slope contain uncertainty in soil properties. Therefore, a probabilistic analysis considering the uncertainty of soil properties is required. In this study, probabilistic safety assessment of levee and cut slope has been performed.

This study investigates current states of college-level English medium instruction (EMI) focusing on students’ perception and satisfaction. In spite of increasing popularity of EMI in Korea, little attention has been paid on current states of EMI in universities located in non-metropolitan areas. This study explores this issue with a special reference to students’ perception and satisfaction classified as their English proficiency level and future direction of EMI. A survey questionnaire was administered to 224 students who took EMI in 2011. The survey indicates that successful implementation of EMI depends on students’ linguistic readiness and that policy support is needed.

This paper explores a governing condition on the extraction from the NPs. According to Fiengo & Higginbotham (1981), "specificity condition" blocks the extraction from the NPs having `some definite reference.` However, the extraction out of the NPs does not seem to be governed only by the specificity condition. As indicated by Erteschik-Shir (1973) and Horn (1974), the presence of an indefinite determiner in and of itself does not suffice to rule in extraction and the acceptability of extraction also appears to depend to some extent on the choice of verb. The extraction from the NPs seems to depend on the actual interpretation of the NPs rather than on the choice of determiner. In this paper, we present an account of the extractability from the NPs based on the focus property of the NPs. Following Lee (2004), we assume that the focus-marked object remains in situ within VP, whereas the given or presuppositonal material moves out of VP to receive an appropriate interpretation (i.e., specificity, topic, etc.). The NP which has a non-presuppositional or existential reading can be focus- marked. Hence, it remains inside the VP without movement. The extraction from the NP is allowed. By contrast, the non-focus-marked NP raises to the Spec of v to satisfy the EPP of v. The extraction from the moved NPs is blocked.

This paper examines non-default/default case environments in English and explores the nature of default case and its realization mechanism in this language. We advance four claims about the default case licensing mechanism: (ⅰ) The default case mechanism is capitalized on to spell out nominal expressions whose Case feature fails to be valued because of the deficiency of the Case value-licensing head, (ⅱ) Nominal expressions without Case valuation have case form through default case licensing at the morphological/phonological component, (ⅲ) Both Nominative and Accusative case can be default case in English, (ⅳ) The selection of the particular Case value through the default case mechanism depends on several factors such as relative positions of nominal expressions and the invariant strong form constraint (Quinn 2002).