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.

The objective of this study is to analyze the indoor air quality of multi-use facilities using an IoT-based monitoring and control system. Thise study aims to identify effective management strategies and propose policy improvements. This research focused on 50 multi-use facilities, including daycare centers, medical centers, and libraries. Data on PM10, PM2.5, CO2, temperature, and humidity were collected 24 hours a day from June 2019 to April 2020. The analysis included variations in indoor air quality by season, hour, and day of the week (including both weekdays and weekends). Additionally, ways to utilize IoT monitoring systems using big data were propsed. The reliability analysis of the IoT monitoring network showed an accuracy of 81.0% for PM10 and 76.1% for PM2.5. Indoor air quality varied significantly by season, with higher particulate matter levels in winter and spring, and slightly higher levels on weekends compared to weekdays. There was a positive correlation found between outdoor and indoor pollutant levels. Indoor air quality management in multi-use facilities requires season-specific strategies, particularly during the winter and spring. Furhtermore, enhanced management is necessary during weekends due to higher pollutant levels.

복숭아혹진딧물(Myzus persicae)은 다식성으로 담배, 감자, 고추, 배추, 복숭아 등에 심각한 피해를 입히는 대표적인 농업해충이다. 본 연구에 서는 국내 복숭아혹진딧물 야외개체군의 λ-cyhalothrin, imidacloprid 및 flupyradifurone에 대한 약제 저항성 발달 수준과 점 돌연변이(R81T, L1014F, M918L)의 발생 여부를 확인하였다. 또한, qRT-PCR을 통해 사이토크롬 P450 유전자인 CYP6CY3 발현량을 확인하였다. 그 결과, λ -cyhalothrin은 저항성비(Resistance Ratio, RR)가 12개 모든 지역이 > 200으로 높은 저항성을 보였다. Imidacloprid와 flupyradifurone은 YS, UR, HY, 그리고 WJ 개체군에서 > 200의 저항성비로 높은 저항성을 나타냈다. R81T는 12개 집단 중 약 50%, L1014F는 약 33.3%, M918L은 100%에서 발현하였다. 또한 qRT-PCR을 통해 imidacloprid 저항성 개체에서 subunit CYP6CY3의 발현량이 높게 나타난 것을 확인하였다. 이러 한 결과는 M918L 점 돌연변이는 λ-cyhalothrin 저항성 진단마커로, R81T와 CYP6CY3의 높은 발현은 imidacloprid 저항성 진단마커로 활용이 가능하다는 것을 시사한다.

PURPOSES : The evaluation of the low-temperature performance of an asphalt mixture is crucial for mitigating transverse thermal cracking and preventing traffic accidents on expressways. Engineers in pavement agencies must identify and verify the pavement sections that require urgent management. In early 2000, the research division of the Korea Expressway Corporation developed a three-dimensional (3D) pavement condition monitoring profiler vehicle (3DPM) and an advanced infographic (AIG) highway pavement management system computer program. Owing to these efforts, the management of the entire expressway network has become more precise, effective, and efficient. However, current 3DPM and AIG technologies focus only on the pavement surface and not on the entire pavement layer. Over the years, along with monitoring, further strengthening and verification of the feasibility of current 3DPM and AIG technologies by performing extensive mechanical tests and data analyses have been recommended. METHODS : First, the pavement section that required urgent care was selected using the 3DPM and AIG approaches. Second, asphalt mixture cores were acquired from the specified section, and a low-temperature fracture test, semi- circular bending (SCB) test, was performed. The mechanical parameters, energy-release rate, and fracture toughness were computed and compared. RESULTS : As expected, the asphalt mixture cores acquired from the specified pavement section ( poor condition – bad section) exhibited negative fracture performances compared to the control section (good section). CONCLUSIONS : The current 3DPM and AIG approaches in KEC can successfully evaluate and analyze selected pavement conditions. However, more extensive experimental studies and mathematical analyses are required to further strengthen and upgrade current pavement analysis approaches.

Benthic attached diatoms (BADs), a major primary producer in lotic stream and river ecosystems are micro-sized organisms and require a highly magnified microscopic technique in the observation work. Thus, it is often not easy to ensure accuracy and precision in both qualitative and quantitative analyses. This study proposed a new technique applicable to improve quality control of aquatic ecosystem monitoring and assessment using BADs. In order to meet the purpose of quality control, we developed a permanent mounting slide technique which can be used for both qualitative and quantitative analyses simultaneously. We designed specimens with the combination of grid on both cover and slide glasses and compared their efficiency. As a result of observation and counting of BADs, the slide glass designed with the color-lined grid showed the highest efficiency compared to other test conditions. We expect that the method developed in this study could be effectively used to analyze BADs and contributed to improve the quality control in aquatic ecosystem health monitoring and assessment.

After the Fukushima nuclear accident in Japan in March 2011, many Koreans were concerned that products exposed to radioactive materials released from the nuclear power plant would be imported into Korea. Systematic radiation monitoring was required for food and daily necessities imported from the nuclear accident area. The need for a legal system to support systematic radiation monitoring was also demanded. The Act on Protective Action Guidelines against Radiation in the Natural Environment was enacted to resolve concerns regarding environmental radiation in Korea in July 2011. According to this law, radiation monitoring equipment has been installed and operated at major airports and ports nationwide. This paper aims to review the radiation monitoring system of the Korean government comprehensively. The legal system and the legal basis for radiation monitoring of imported cargo conducted by each department were investigated by analyzing the laws and regulations of radiation monitoring for the relevant cargo items. In addition, the current status of radiation monitoring by the government departments was examined to determine how radiation monitoring for imported cargo is performed within the legal system. The investigation of the current radiation monitoring system for imported cargo in Korea confirmed that radiation monitoring is conducted by classifying cargo items under the jurisdiction of each government department for all imported cargo. However, the reduction in efficiency of radiation monitoring of imported cargoes, unclear legal grounds for radiation monitoring of imported cargo by some departments, the occurrence of overlapping inspections by departments, and the difficult process of issuing the radiation test certificate required for customs clearance by the Korea Customs Service were also identified. As a result of the analysis, it was found that the current radiation monitoring system for imported cargo in Korea ought to be improved, taking into account efficiency, overlapping inspection, legal background, and the difficult process of issuing the certificates.

사물인터넷(IoT) 기술을 활용한 전력 사용량 모니터링은 스마트팜 운영비 절감 기술 개발을 위한 기초자료로 필요성이 부각되고 있다. 본 연구에서는 멜론 생산 스마트팜 운영 중 실시간 전력사용량 모니터링 시스템을 설치한 예를 소개하고 이 를 이용하여 수집된 데이터를 실시간으로 활용하는 방법을 제 안한다. 전력사용량 모니터링 시스템의 실증을 위하여 멜론 스마트팜에서 3개월의 멜론 재배기간 동안 보일러, 양분분배 시스템, 자동제어기, 순환팬, 보일러제어기, 기타 IoT 관련 유 틸리티 등 스마트팜 시설에서 사용하는 개별 전원 기구들의 전력사용량 데이터를 수집하였다. 모니터링 결과를 이용하여 전기에너지 소비패턴의 예시를 분석하고, 측정 데이터를 최 적으로 활용하기 위해 필요한 고려사항을 제시하였다. 본 논 문은 전력사용량 모니터링 시스템을 새로이 구축하고자 하는 유저들에게 기술적 진입장벽을 낮추고 생성된 데이터 활용 시 시행착오를 줄이는 데 유용한 자료가 될 것으로 사료된다.

For countering nuclear proliferation, satellite imagery is being used to monitor suspicious nuclear activities in inaccessible countries or regions. Monitoring such activities involves detecting changes over time in nuclear facilities and their surroundings, and interpreting them based on prior knowledge in terms of nuclear proliferation or weaponisation. Therefore, analysts need to acquire and analyze satellite images periodically and have an understanding of nuclear fuel cycle as well as expertise in remote sensing. Meanwhile, as accessibility of satellite information has been increasing and accordingly a large amount of high-resolution satellite images is available, a lack of experts with expertise in both fields to perform satellite imagery analysis is being concerned. In this regard, the Institute of Korea Nonproliferation and Control (KINAC) has developed a prototype of semi-automatic satellite imagery analysis system that can support monitoring of potential nuclear activities to overcome the limitations of professionals and increase analysis efficiency. The system provides a satellite imagery database that can manage acquired images, and the users can load images from the database and analyze them in stages. The system includes a preprocessing module capable of resizing, correcting and matching images, a change detection module equipped with a pixel-object-based change detection algorithm for multi-temporal images, and a module that automatically generates reports with relevant information. In particular, this system continuously updates open-source information database related to potential nuclear activities and provides users with an integrated analytics platform that can support their interpretation by linking related images and textual information together. As such, the system could save time and cost in processing and interpreting satellite images by providing semi-automated analytic workflows for monitoring potential nuclear activities.

The frequent detection and occurrence of micropollutants (MPs) in aquatic ecosystems has raised public health concerns worldwide. In this study, the behavior of 50 MPs was investigated in three different domestic wastewater treatment plants (WWTPs). Furthermore, the Kruskal-Wallis test was used to assess the geographical and seasonal variation of MPs in the WWTPs. The results showed that the concentrations of 43 MPs ranged from less than 0.1 to 237.6 μg L-1, while other seven MPs including 17-ethynylestradiol, 17-estradiol, sulfathiazole, sulfamethazine, clofibric acid, simvastatin, and lovastatin were not detected in all WWTPs. Among the detected MPs, the pharmaceuticals such as metformin, acetaminophen, naproxen, and caffeine were prominent with maximum concentrations of 133.4, 237.6, 71.5, and 107.7 μg L-1, respectively. Most perfluorinated compounds and nitrosamines were found at trace levels of 1.2 to 55.3 ng L-1, while the concentration of corrosion inhibitors, preservatives (parabens), and endocrine disruptors ranged from less than 0.1 to 4310.8 ng L-1. Regardless of the type of biological treatment process such as MLE, A2O, and MBR, the majority of pharmaceuticals (except lincomycin, diclofenac, iopromide, and carbamazepine), parabens (except Methyl paraben), and endocrine disruptors were removed by more than 80%. However, the removal efficiencies of certain MPs such as atrazine, DEET, perfluorinated compounds (except PFHxA), nitrosamines, and corrosion inhibitors were relatively low or their concentration even increased after treatment. The results of statistical analysis reveal that there is no significant geographical difference in the removal efficacy of MPs, but there are temporal seasonal variations in all WWTPs.