• Title/Summary/Keyword: Level Sensor

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Empirical Research on Improving Traffic Cone Considering LiDAR's Characteristics (LiDAR의 특성을 고려한 자율주행 대응 교통콘 개선 실증 연구)

  • Kim, Jiyoon;Kim, Jisoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.253-273
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    • 2022
  • Automated vehicles rely on information collected through sensors to drive. Therefore, the uncertainty of the information collected from a sensor is an important to address. To this end, research is conducted in the field of road and traffic to solve the uncertainty of these sensors through infrastructure or facilities. Therefore, this study developed a traffic cone that can maintaing the gaze guidance function in the construction site by securing sufficient LiDAR detection performance even in rainy conditions and verified its improvement effect through demonstration. Two types of cones were manufactured, a cross-type and a flat-type, to increase the reflective performance compared to an existing cone. The demonstration confirms that the flat-type traffic cone has better detection performance than an existing cone, even in 50 mm/h rainfall, which affects a driver's field of vision. In addition, it was confirmed that the detection level on a clear day was maintained at the 20 mm/h rain for both cones. In the future, improvement measures should be developed so that the traffic cones, that can improve the safety of automated driving, can be applied.

A Study on Moisture Adsorption Capacity by Charcoals (숯의 수분 흡착성능 연구)

  • Kim, Dae Wan;An, Ki Sun;Kwak, Lee Ku;Kim, Hong Gun;Ryu, Seung Kon;Lee, Young Seak
    • Korean Chemical Engineering Research
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    • v.60 no.3
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    • pp.377-385
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    • 2022
  • Surface morphology and adsorption characteristics of charcoals prepared from Korean traditional kiln were analyzed, and their moisture adsorption capacities were examined with respect to humidity and temperature change. Moisture adsorption capacities of red-clay powder, activated carbon fiber fabric (ACF fabric) and activated carbon fiber paper(ACF paper) were also examined to compare with those of charcoals. Moisture adsorption capacity of charcoal was low less than 45% humidity due to its hydrophobic property, but it slowly and linearly increased as increasing the humidity. Moisture adsorption capacity of red-clay powder was similar to charcoal at low level humidity, it increased exponentially as increasing the humidity showing Type V adsorption isotherm. Therefore, the weather forecast annal prepared by employee of weather centre in Joseon Dynasty is experimentally approved. ACF fabric and ACF paper show excellent moisture adsorption capacities, which can be used to humidity measuring sensor. Adsorption isotherm of charcoal slice was peculear showing the mixed Type I and Type IV due to low-pressure hysteresis that was occurred from embedment of nitrogen in crevice of charcoal. The specific surface area of charcoal increased by grinding charcoal slice to powder, resulted in increasing the desorption amount of adsorbent at low relative pressure.

A Study on Real-Time SOC Structure Behavior Evaluation System using Big Data (Big data를 이용한 실시간 SOC 구조물 거동분석 시스템 연구)

  • Jung-Youl Choi;Jae-Min Han;Dae-Hui Ahn;Jee-Seung Chung
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.691-695
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    • 2023
  • Currently, the utilization of measurement results of the automated measurement system is very low and is at the level of providing only fragmentary measurement results. In this study, we are going to study a structure behavior analysis 3D display system with high precision and reliability for automated measurement data obtained by constructing big data by transmitting massive data values measured in real time to the cloud and using a Python-based algorithm. As a result of the study, as a system that can evaluate the behavior of a structure to a manager in real time, it provides analysis data in real time without significant restrictions regardless of the type of measurement data and sensor, and derived it as a 3D display. In addition, it was analyzed that the manager could grasp the behavior graph of the structure in real time and more easily judge the derivation of the weak part of the structure through data analysis. In the future, by analyzing the behavior of structures in three dimensions using past and present data, it is expected that more effective measurement results can be obtained in terms of repair, reinforcement, and maintenance of realistic structures.

Attention based Feature-Fusion Network for 3D Object Detection (3차원 객체 탐지를 위한 어텐션 기반 특징 융합 네트워크)

  • Sang-Hyun Ryoo;Dae-Yeol Kang;Seung-Jun Hwang;Sung-Jun Park;Joong-Hwan Baek
    • Journal of Advanced Navigation Technology
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    • v.27 no.2
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    • pp.190-196
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    • 2023
  • Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

Photosynthesis Monitoring of Rice using SPAR System to Respond to Climate Change

  • Hyeonsoo Jang;Wan-Gyu Sang;Yun-Ho Lee;Hui-woo Lee;Pyeong Shin;Dae-Uk Kim;Jin-Hui Ryu;Jong-Tag Youn
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.169-169
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    • 2022
  • Over the past 100 years, the global average temperature has risen by 0.75 ℃. The Korean Peninsula has risen by 1.8 ℃, more than twice the global average. According to the RCP 8.5 scenario, the CO2 concentration in 2100 will be 940 ppm, about twice as high as current. The National Institute of Crop Science(NICS) is using the SPAR (Soil-Plant Atmosphere Research) facility that can precisely control the environment, such as temperature, humidity, and CO2. A Python-based colony photosynthesis algorithm has been developed, and the carbon and nitrogen absorption rate of rice is evaluated by setting climate change conditions. In this experiment, Oryza Sativa cv. Shindongjin were planted at the SPAR facility on June 10 and cultivated according to the standard cultivation method. The temperature and CO2 settings are high temperature and high CO2 (current temperature+4.7℃ temperature+4.7℃·CO2 800ppm), high temperature single condition (current temperature+4.7℃·CO2 400ppm) according to the RCP8.5 scenario, Current climate is set as (current temperature·CO2400ppm). For colony photosynthesis measurement, a LI-820 CO2 sensor was installed in each chamber for setting the CO2 concentration and for measuring photosynthesis, respectively. The colony photosynthetic rate in the booting stage was greatest in a high temperature and CO2 environment, and the higher the nitrogen fertilization level, the higher the colony photosynthetic rate tends to be. The amount of photosynthesis tended to decrease under high temperature. In the high temperature and high CO2 environment, seed yields, the number of an ear, and 1000 seed weights tended to decrease compared to the current climate. The number of an ear also decreased under the high temperature. But yield tended to increase a little bit under the high temperature and high CO2 condition than under the high temperature. In addition, In addition to this study, it seems necessary to comprehensively consider the relationship between colony photosynthetic ability, metabolite reaction, and rice yield according to climate change.

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Hydrological Drought Assessment and Monitoring Based on Remote Sensing for Ungauged Areas (미계측 유역의 수문학적 가뭄 평가 및 감시를 위한 원격탐사의 활용)

  • Rhee, Jinyoung;Im, Jungho;Kim, Jongpil
    • Korean Journal of Remote Sensing
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    • v.30 no.4
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    • pp.525-536
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    • 2014
  • In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.

Object-based Building Change Detection Using Azimuth and Elevation Angles of Sun and Platform in the Multi-sensor Images (태양과 플랫폼의 방위각 및 고도각을 이용한 이종 센서 영상에서의 객체기반 건물 변화탐지)

  • Jung, Sejung;Park, Jueon;Lee, Won Hee;Han, Youkyung
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.989-1006
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    • 2020
  • Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.

The Comparison of the Ultra-Violet Radiation of Summer Outdoor Screened by the Landscaping Shade Facilities and Tree (조경용 차양시설과 수목에 의한 하절기 옥외공간의 자외선 차단율 비교)

  • Lee, Chun-Seok;Ryu, Nam-Hyong
    • Journal of the Korean Institute of Landscape Architecture
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    • v.41 no.6
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    • pp.20-28
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    • 2013
  • The purpose of this study was to compare the ultra-violet(UV) radiation under the landscaping shade facilities and tree with natural solar UV of the outdoor space at summer middays. The UVA+B and UVB were recorded every minute from the $20^{th}$ of June to the $26^{th}$ of September 2012 at a height of 1.1m above in the four different shading conditions, with fours same measuring system consisting of two couple of analog UVA+B sensor(220~370nm, Genicom's GUVA-T21GH) and UVB sensor(220~320nm, Genicom's GUVA-T21GH) and data acquisition systems(Comfile Tech.'s Moacon). Four different shading conditions were under an wooden shelter($W4.2m{\times}L4.2m{\times}H2.5m$), a polyester membrane structure ($W4.9m{\times}L4.9m{\times}H2.6m$), a Salix koreensis($H11{\times}B30$), and a brick-paved plot without any shading material. Based on the 648 records of 17 sunny days, the time serial difference of natural solar UVA+B and UVB for midday periods were analysed and compared, and statistical analysis about the difference between the four shading conditions was done based on the 2,052 records of daytime period from 10 A.M. to 4 P.M.. The major findings were as follows; 1. The average UVA+B under the wooden shelter, the membrane and the tree were $39{\mu}W/cm^2$(3.4%), $74{\mu}W/cm^2$(6.4%), $87{\mu}W/cm^2$(7.6%) respectively, while the solar UVA+B was $1.148{\mu}W/cm^2$. Which means those facilities and tree screened at least 93% of solar UV+B. 2. The average UVB under the wooden shelter, the membrane and the tree were $12{\mu}W/cm^2$(5.8%), $26{\mu}W/cm^2$(13%), $17{\mu}W/cm^2$(8.2%) respectively, while the solar UVB was $207{\mu}W/cm^2$. The membrane showed the highest level and the wooden shelter lowest. 3. According to the results of time serial analysis, the difference between the three shaded conditions around noon was very small, but the differences of early morning and late afternoon were apparently big. Which seems caused by the matter of the formal and structural characteristics of the shading facilities and tree, not by the shading materials itself. In summary, the performance of the four landscaping shade facilities and tree were very good at screening the solar UV at outdoor of summer middays, but poor at screening the lateral UV during early morning and late afternoon. Therefore, it can be apparently said that the more delicate design of shading facilities and big tree or forest to block the additional lateral UV, the more effective in conditioning the outdoor space reducing the useless or even harmful radiation for human activities.

Application and Analysis of Ocean Remote-Sensing Reflectance Quality Assurance Algorithm for GOCI-II (천리안해양위성 2호(GOCI-II) 원격반사도 품질 검증 시스템 적용 및 결과)

  • Sujung Bae;Eunkyung Lee;Jianwei Wei;Kyeong-sang Lee;Minsang Kim;Jong-kuk Choi;Jae Hyun Ahn
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1565-1576
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    • 2023
  • An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (Rrs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This Rrs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of Rrs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ Rrs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for Rrs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying Rrs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

A Polarization-based Frequency Scanning Interferometer and the Measurement Processing Acceleration based on Parallel Programing (편광 기반 주파수 스캐닝 간섭 시스템 및 병렬 프로그래밍 기반 측정 고속화)

  • Lee, Seung Hyun;Kim, Min Young
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.8
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    • pp.253-263
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    • 2013
  • Frequency Scanning Interferometry(FSI) system, one of the most promising optical surface measurement techniques, generally results in superior optical performance comparing with other 3-dimensional measuring methods as its hardware structure is fixed in operation and only the light frequency is scanned in a specific spectral band without vertical scanning of the target surface or the objective lens. FSI system collects a set of images of interference fringe by changing the frequency of light source. After that, it transforms intensity data of acquired image into frequency information, and calculates the height profile of target objects with the help of frequency analysis based on Fast Fourier Transform(FFT). However, it still suffers from optical noise on target surfaces and relatively long processing time due to the number of images acquired in frequency scanning phase. 1) a Polarization-based Frequency Scanning Interferometry(PFSI) is proposed for optical noise robustness. It consists of tunable laser for light source, ${\lambda}/4$ plate in front of reference mirror, ${\lambda}/4$ plate in front of target object, polarizing beam splitter, polarizer in front of image sensor, polarizer in front of the fiber coupled light source, ${\lambda}/2$ plate between PBS and polarizer of the light source. Using the proposed system, we can solve the problem of fringe image with low contrast by using polarization technique. Also, we can control light distribution of object beam and reference beam. 2) the signal processing acceleration method is proposed for PFSI, based on parallel processing architecture, which consists of parallel processing hardware and software such as Graphic Processing Unit(GPU) and Compute Unified Device Architecture(CUDA). As a result, the processing time reaches into tact time level of real-time processing. Finally, the proposed system is evaluated in terms of accuracy and processing speed through a series of experiment and the obtained results show the effectiveness of the proposed system and method.