• Title/Summary/Keyword: Trajectory estimation

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Update Policy and Estimation of Uncertain Position Using Trajectory Information (위상 정보를 이용한 갱신 정책과 불확실한 위치 정보에 대한 추정 기법)

  • Sim, Tai-Jung;Kim, Jae-Hong;Jung, Won-Il;Jang, Yong-Il;Bae, Hae-Young
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05c
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    • pp.1651-1654
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    • 2003
  • 이동 단말의 보급이 보편화됨에 따라 이동 객체의 위치 정보를 기반으로 사용자에게 사람이나 사물, 차량 등과 같은 이동 객체의 위치를 파악하여 그에 대한 정보를 제공해 주는 시스템이 필요로 하게 되었나 이러만 이동 객체관리 시스템에서는 계속적으로 위치 정보가 변화하는 이동 객체의 특성상 데이터의 빈번한 갱신이 일어나게 되고 DBMS에 명시적으로 저장되지 않은 위치 정보에 대해서도 보다 정확한 위치를 사용자에게 제공해 주어야 한다. 그러나 차량의 위치 추적과 같이 적용 개체가 차량에 한정된 경우 이동 경로가 도로상으로 제한되어 있으므로 이동 경로를 예측하기 힘든 사람과 같은 객체와는 특성이 나르나 따라서 차량 객체에 대해 보다 효과적인 서비스를 제공해 주기 위해서는 사람에 대한 위치 추적과는 다른 갱신 정책과 불확실한 위치의 추정 기법이 필요하다. 본 논문에서는 공간 데이터에 저장된 도로의 위상 정보와 차량의 속도 속성을 이용한 갱신 정책을 정하여 갱신 빈도수로 줄이고 도로 레이어의 위상 정보를 통해 불확실한 과거 및 미래의 위치로 추정하는 기법을 제안한다. 제안한 갱신 정책은 차량의 속도를 고려하여 현재의 위치에서 도로상의 교차점에 도착하는 시점의 위치를 예측하여 데이터의 갱신 시점으로 결정한다. 또한 불확실한 위치에 대한 추정은 이동하는 도회와 대응되는 위상 정보를 기반으로 차량의 이동 방향을 예측하 여 불확실한 미래의 위치를 결정할 수 있으며 명시적으로 저장되지 않은 과거 위치 정보의 검색에 대한 요청이 발생했을 경우 위상 정보를 이용하여 위치를 보정하고 사용자에게 보나 높은 정확성을 지닌 정보를 제공해 줄 수 있다.다. SQL Server 2000 그리고 LSF를 이용하였다. 그리고 구현 환경과 구성요소에 대한 수행 화면을 보였다.ool)을 사용하더라도 단순 다중 쓰레드 모델보다 더 많은 수의 클라이언트를 수용할 수 있는 장점이 있다. 이러한 결과를 바탕으로 본 연구팀에서 수행중인 MoIM-Messge서버의 네트워크 모듈로 다중 쓰레드 소켓폴링 모델을 적용하였다.n rate compared with conventional face recognition algorithms. 아니라 실내에서도 발생하고 있었다. 정량한 8개 화합물 각각과 총 휘발성 유기화합물의 스피어만 상관계수는 벤젠을 제외하고는 모두 유의하였다. 이중 톨루엔과 크실렌은 총 휘발성 유기화합물과 좋은 상관성 (톨루엔 0.76, 크실렌, 0.87)을 나타내었다. 이 연구는 톨루엔과 크실렌이 총 휘발성 유기화합물의 좋은 지표를 사용될 있고, 톨루엔, 에틸벤젠, 크실렌 등 많은 휘발성 유기화합물의 발생원은 실외뿐 아니라 실내에도 있음을 나타내고 있다.>10)의 $[^{18}F]F_2$를 얻었다. 결론: $^{18}O(p,n)^{18}F$ 핵반응을 이용하여 친전자성 방사성동위원소 $[^{18}F]F_2$를 생산하였다. 표적 챔버는 알루미늄으로 제작하였으며 본 연구에서 연구된 $[^{18}F]F_2$가스는 친핵성 치환반응으로 방사성동위원소를 도입하기 어려운 다양한 방사성의 약품개발에 유용하게 이용될 수 있을 것이다.었으나 움직임 보정 후 영상을 이용하여 비교한 경우, 결합능 변화가 선조체 영역에서 국한되어 나타나며

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Calibration of Car-Following Models Using a Dual Genetic Algorithm with Central Composite Design (중심합성계획법 기반 이중유전자알고리즘을 활용한 차량추종모형 정산방법론 개발)

  • Bae, Bumjoon;Lim, Hyeonsup;So, Jaehyun (Jason)
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.2
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    • pp.29-43
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    • 2019
  • The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

Analysis of Spatial Trip Regularity using Trajectory Data in Urban Areas (도시부 경로자료를 이용한 통행의 공간적 규칙성 분석)

  • Lee, Su jin;Jang, Ki tae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.6
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    • pp.96-110
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    • 2018
  • As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

Estimation of Pollutant Sources in Dangjin Coal-Fired Power Plant Using Carbon Isotopes (탄소 안정동위원소를 이용한 석탄화력발전소 인근 오염원 기원 추정 : 당진시를 중심으로)

  • Yoon, Soohyang;Cho, Bong-Yeon
    • The Journal of the Korea Contents Association
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    • v.21 no.3
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    • pp.567-575
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    • 2021
  • Residents in Dangjin, South Chungcheong Province, in which large-scale emissions facilities such as coal-fired power plants and steel mills are concentrated, are very much concerned about their health despite the local government's aggressive efforts to improve air quality and reduce greenhouse gases. To understand the impact of coal-fired power plants and external factors on local air pollution, the origins of local pollutants were investigated using stable carbon isotopes that are generally used as tracers of the provenance of fine or ultrafine dust. The origins of the pollutants were analyzed with the data library, built using the seasonally measured data for the two separate locations selected considering the distance from the coal-fired power plant and the analysis of previous studies, and with the back trajectory analysis. As a result of analyzing stable isotope ratios, the tendency of high concentration was found in the order of winter > spring > fall > summer. According to the data matching with the library, the mobile pollutants and open-air incineration had a relatively higher impact on the local air pollution. It is believed that this study, as a pilot study, should focus on securing the reliability of the study results through continuous monitoring and data accumulation.

Computer Vision-based Continuous Large-scale Site Monitoring System through Edge Computing and Small-Object Detection

  • Kim, Yeonjoo;Kim, Siyeon;Hwang, Sungjoo;Hong, Seok Hwan
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1243-1244
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    • 2022
  • In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

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Autonomous Ship's Remote Operation Situation Occurrence Probability Estimation Model based on Navigation Areas (운항 해역별 자율운항선박 원격운항 상황 발생 확률 추산 시뮬레이션 모델)

  • Taewoong Hwang;Taemin Hwang;Dain Lee;Hyeinn Park;Ik-Hyun Youn
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.910-914
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    • 2023
  • With the technological innovation owing to the 4th industrial revolution, the maritime transportation is rapidly being developed with autonomous ships and systems. Particularly, autonomous ships will partially replace the manned ships and navigation among them remotely upon the degree of autonomy suggested by IMO. Accordingly, the remote operator and related research have increased as well. However, the data on the minimum required manpower for remote operators are lacking such as considering engage required situations and their co-occurrence probability. Therefore, this study proposes a simulation model that calculates the number of remote engage required situations by defining restricted water area and remote engage required situation as close-quarter situations based on accumulated trajectory data of actual ships. The findings are expected to be used as background materials to establish the appropriate manpower distribution of remote operators in remote operation centers.

An Estimation of Concentration of Asian Dust (PM10) Using WRF-SMOKE-CMAQ (MADRID) During Springtime in the Korean Peninsula (WRF-SMOKE-CMAQ(MADRID)을 이용한 한반도 봄철 황사(PM10)의 농도 추정)

  • Moon, Yun-Seob;Lim, Yun-Kyu;Lee, Kang-Yeol
    • Journal of the Korean earth science society
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    • v.32 no.3
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    • pp.276-293
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    • 2011
  • In this study a modeling system consisting of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), the Community Multiscale Air Quality (CMAQ) model, and the CMAQ-Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) model has been applied to estimate enhancements of $PM_{10}$ during Asian dust events in Korea. In particular, 5 experimental formulas were applied to the WRF-SMOKE-CMAQ (MADRID) model to estimate Asian dust emissions from source locations for major Asian dust events in China and Mongolia: the US Environmental Protection Agency (EPA) model, the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model, and the Dust Entrainment and Deposition (DEAD) model, as well as formulas by Park and In (2003), and Wang et al. (2000). According to the weather map, backward trajectory and satellite image analyses, Asian dust is generated by a strong downwind associated with the upper trough from a stagnation wave due to development of the upper jet stream, and transport of Asian dust to Korea shows up behind a surface front related to the cut-off low (known as comma type cloud) in satellite images. In the WRF-SMOKE-CMAQ modeling to estimate the PM10 concentration, Wang et al.'s experimental formula was depicted well in the temporal and spatial distribution of Asian dusts, and the GOCART model was low in mean bias errors and root mean square errors. Also, in the vertical profile analysis of Asian dusts using Wang et al's experimental formula, strong Asian dust with a concentration of more than $800\;{\mu}g/m^3$ for the period of March 31 to April 1, 2007 was transported under the boundary layer (about 1 km high), and weak Asian dust with a concentration of less than $400\;{\mu}g/m^3$ for the period of 16-17 March 2009 was transported above the boundary layer (about 1-3 km high). Furthermore, the difference between the CMAQ model and the CMAQ-MADRID model for the period of March 31 to April 1, 2007, in terms of PM10 concentration, was seen to be large in the East Asia area: the CMAQ-MADRID model showed the concentration to be about $25\;{\mu}g/m^3$ higher than the CMAQ model. In addition, the $PM_{10}$ concentration removed by the cloud liquid phase mechanism within the CMAQ-MADRID model was shown in the maximum $15\;{\mu}g/m^3$ in the Eastern Asia area.

Atmospheric Aerosol Monitoring Over Northeast Asia During 2001 from MODIS and TOMS data (MODIS와 TOMS자료를 이용한 2001년 동북아시아 지역의 대기 에어로졸 모니터링)

  • 이권호;홍천상;김영준
    • Korean Journal of Remote Sensing
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    • v.20 no.2
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    • pp.77-89
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    • 2004
  • The spatial and temporal variations of aerosol optical depth (AOD) over Northeast Asia regions have special importance in the aerosol research for estimation of aerosol radiative forcing parameters and climate change. Aerosol optical and physical properties (AOD and ${\AA}$ngstrom parameter) have been investigated by using Moderate Resolution Imaging Spectroradiometer (MODIS) and Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) to estimate aerosol characteristics over the study region during 2001. Additionally, aerosol characteristics over the Korean peninsular during Aerosol Characteristic Experiment in Asia (ACE-Asia) Intensive Observation Period (IOP) have been investigated by using satellite observations. The results showed that the daily-observed aerosol data indicate seasonal variations with relatively higher aerosol loading in the spring and very low during the winter. The typical Asian dust case showed higher AOD (>0.7) with lower Angstrom exponent (<0.5) and higher AI (>0.5) that is mainly due to the composition of coarse particles in the springtime. Mean AOD for 2001 at 4 different places showed 0.65$\pm$0.37 at Beijing, 0.31$\pm$0.19 at Gosan, 0.54$\pm$0.26 at Seoul, and 0.38$\pm$0.19 at Kwangju, respectively. An interesting result was found in the present study that polluted aerosol events with small size dominated-aerosol loading around the Korean peninsular are sometimes observed. The origin of these polluted aerosols was thought to East China. Aerosol distribution from satellite images and trajectory results shows the proof of aerosol transport. Therefore, aerosol monitoring using satellite data is very useful.

Estimation of Mean Surface Current and Current Variability in the East Sea using Surface Drifter Data from 1991 to 2017 (1991년부터 2017년까지 표층 뜰개 자료를 이용하여 계산한 동해의 평균 표층 해류와 해류 변동성)

  • PARK, JU-EUN;KIM, SOO-YUN;CHOI, BYOUNG-JU;BYUN, DO-SEONG
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.24 no.2
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    • pp.208-225
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    • 2019
  • To understand the mean surface circulation and surface currents in the East Sea, trajectories of surface drifters passed through the East Sea from 1991 to 2017 were analyzed. By analyzing the surface drifter trajectory data, the main paths of surface ocean currents were grouped and the variation in each main current path was investigated. The East Korea Warm Current (EKWC) heading northward separates from the coast at $36{\sim}38^{\circ}N$ and flows to the northeast until $131^{\circ}E$. In the middle (from $131^{\circ}E$ to $137^{\circ}E$) of the East Sea, the average latitude of the currents flowing eastward ranges from 36 to $40^{\circ}N$ and the currents meander with large amplitude. When the average latitude of the surface drifter paths was in the north (south) of $37.5^{\circ}N$, the meandering amplitude was about 50 (100) km. The most frequent route of surface drifters in the middle of the East Sea was the path along $37.5-38.5^{\circ}N$. The surface drifters, which were deployed off the coast of Vladivostok in the north of the East Sea, moved to the southwest along the coast and were separated from the coast to flow southeastward along the cyclonic circulation around the Japan Basin. And, then, the drifters moved to the east along $39-40^{\circ}N$. The mean surface current vector and mean speed were calculated in each lattice with $0.25^{\circ}$ grid spacing using the velocity data of surface drifters which passed through each lattice. The current variance ellipses were calculated with $0.5^{\circ}$ grid spacing. Because the path of the EKWC changes every year in the western part of the Ulleung Basin and the current paths in the Yamato Basin keep changing with many eddies, the current variance ellipses are relatively large in these region. We present a schematic map of the East Sea surface current based on the surface drifter data. The significance of this study is that the surface ocean circulation of the East Sea, which has been mainly studied by numerical model simulations and the sea surface height data obtained from satellite altimeters, was analyzed based on in-situ Lagrangian observational current data.

Estimation of the Surface Currents using Mean Dynamic Topography and Satellite Altimeter Data in the East Sea (평균역학고도장과 인공위성고도계 자료를 이용한 동해 표층해류 추산)

  • Lee, Sang-Hyun;Byun, Do-Seong;Choi, Byoung-Ju;Lee, Eun-Il
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.14 no.4
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    • pp.195-204
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    • 2009
  • In order to estimate sea surface current fields in the East Sea, we examined characteristics of mean dynamic topography (MDT) fields (or mean surface current field, MSC) generated from three different methods. This preliminary investigation evaluates the accuracy of surface currents estimated from satellite-derived sea level anomaly (SLA) data and three MDT fields in the East Sea. AVISO (Archiving, Validation and Interpretation of Satellite Oceanographic data) provides a MDT field derived from satellite observation and numerical models with $0.25^{\circ}$ horizontal resolution. Steric height field relative to 500 dbar from temperature and salinity profiles in the East Sea supplies another MDT field. Trajectory data of surface drifters (ARGOS) in the East Sea for 14 years provide another MSC field. Absolute dynamic topography (ADT) field is calculated by adding SLA to each MDT. Application of geostrophic equation to three different ADT fields yields three surface geostrophic current fields. Comparisons were made between the estimated surface currents from the three different methods and in-situ current measurements from a ship-mounted ADCP (Acoustic Doppler Current Profiler) in the southwestern East Sea in 2005. For offshore areas more than 50 km away from the land, the correlation coefficients (R) between the estimated versus the measured currents range from 0.58 to 0.73, with 17.1 to $21.7\;cm\;s^{-1}$ root mean square deviation (RMSD). For coastal ocean within 50 km from the land, however, R ranges from 0.06 to 0.46 and RMSD ranges from 15.5 to $28.0\;cm\;s^{-1}$. Results from this study reveal that a new approach in producing MDT and SLA is required to improve the accuracy of surface current estimations for the shallow costal zones of the East Sea.