• Title/Summary/Keyword: Source location estimation

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QZSS TEC Estimation and Validation Over South Korea

  • Byung-Kyu Choi;Dong-Hyo Sohn;Junseok Hong;Woo Kyoung Lee
    • Journal of Positioning, Navigation, and Timing
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    • v.12 no.4
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    • pp.343-348
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    • 2023
  • The ionosphere acts as the largest error source in the Global Navigation Satellite System (GNSS) signal transmission. Ionospheric total electron content (TEC) is also easily affected by changes in the space environment, such as solar activity and geomagnetic storms. In this study, we analyze changes in the regional ionosphere using the Qusai-Zenith Satellite System (QZSS), a regional satellite navigation system. Observations from 9 GNSS stations in South Korea are used for estimating the QZSS TEC. In addition, the performance of QZSS TEC is analyzed with observations from day of year (DOY) 199 to 206, 2023. To verify the performance of our results, we compare the estimated QZSS TEC and CODE Global Ionosphere Map (GIM) at the same location. Our results are in good agreement with the GIM product provided by the CODE over this period, with an averaged difference of approximately 0.1 TECU and a root mean square (RMS) value of 2.89 TECU.

Preliminary Source Apportionment of Ambient VOCs Measured in Seoul Metropolitan Area by Positive Matrix Factorization (PMF를 이용한 수도권지역 VOCs의 배출원 추정)

  • Han J. S.;Moon K. J.;Kim R. H.;Shin S. A.;Hong Y. D.;Jung I. R.
    • Journal of Korean Society for Atmospheric Environment
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    • v.22 no.1
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    • pp.85-97
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    • 2006
  • The PAMS data collected at four sites in Seoul metropolitan area in 2004 were analyzed using the positive matrix factorization (PMF) technique, in order to identify the possible sources and estimate their contributions to ambient VOCs. Ten sources were then resolved at Jeongdong, Bulgwang, Yangpyeong, and Seokmo, including vehicle exhaust, LPG vehicle, petroleum evaporation, coating, solvent, asphalt, LNG, Industry & heating, open burning, and biogenic source. The PMF analysis results showed that vehicle exhaust commonly contributed the largest portion of the predicted total VOCs mass concentration, more than $30\%$ at four sites. The contribution of other resolved sources were significantly different according to the characteristics of site location. In the case of Jeongdong and bulgwang located in urban area, various anthropogenic sources such as coating, solvent, asphalt, residual LPG, and petroleum evaporation contributed about $40\%$ of total VOCs mass. On the other hand, at yangpyeong and Seokmo located in rural and remote area, the portion of these anthropogenic sources was reduced to less than $30\%$ and the contribution of natural sources including open burning and biogenic source clearly observed. These results were considerably corresponding to the emission inventory investigated in this region.

On the speaker's position estimation using TDOA algorithm in vehicle environments (자동차 환경에서 TDOA를 이용한 화자위치추정 방법)

  • Lee, Sang-Hun;Choi, Hong-Sub
    • Journal of Digital Contents Society
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    • v.17 no.2
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    • pp.71-79
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    • 2016
  • This study is intended to compare the performances of sound source localization methods used for stable automobile control by improving voice recognition rate in automobile environment and suggest how to improve their performances. Generally, sound source location estimation methods employ the TDOA algorithm, and there are two ways for it; one is to use a cross correlation function in the time domain, and the other is GCC-PHAT calculated in the frequency domain. Among these ways, GCC-PHAT is known to have stronger characteristics against echo and noise than the cross correlation function. This study compared the performances of the two methods above in automobile environment full of echo and vibration noise and suggested the use of a median filter additionally. We found that median filter helps both estimation methods have good performances and variance values to be decreased. According to the experimental results, there is almost no difference in the two methods' performances in the experiment using voice; however, using the signal of a song, GCC-PHAT is 10% more excellent than the cross correlation function in terms of the recognition rate. Also, when the median filter was added, the cross correlation function's recognition rate could be improved up to 11%. And in regarding to variance values, both methods showed stable performances.

The Software Complexity Estimation Method in Algorithm Level by Analysis of Source code (소스코드의 분석을 통한 알고리즘 레벨에서의 소프트웨어 복잡도 측정 방법)

  • Lim, Woong;Nam, Jung-Hak;Sim, Dong-Gyu;Cho, Dae-Sung;Choi, Woong-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.5
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    • pp.153-164
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    • 2010
  • A program consumes energy by executing its instructions. The amount of cosumed power is mainly proportional to algorithm complexity and it can be calculated by using complexity information. Generally, the complexity of a S/W is estimated by the microprocessor simulator. But, the simulation takes long time why the simulator is a software modeled the hardware and it only provides the information about computational complexity quantitatively. In this paper, we propose a complexity estimation method of analysis of S/W on source code level and produce the complexity metric mathematically. The function-wise complexity metrics give the detailed information about the calculation-concentrated location in function. The performance of the proposed method is compared with the result of the gate-level microprocessor simulator 'SimpleScalar'. The used softwares for performance test are $4{\times}4$ integer transform, intra-prediction and motion estimation in the latest video codec, H.264/AVC. The number of executed instructions are used to estimate quantitatively and it appears about 11.6%, 9.6% and 3.5% of error respectively in contradistinction to the result of SimpleScalar.

$PM3.5/NO_2$ Concentration Ratio in Roadside and Exposure Assessment of Shoes Repairmen in Seoul (서울시 도로변의 $PM3.5/NO_2$ 농도비 및 구두수선대 근로자의 노출평가)

  • 배현주;양원호;김나리;정문호
    • Journal of environmental and Sanitary engineering
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    • v.16 no.4
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    • pp.21-30
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    • 2001
  • Vehicles, especially diesel-using, are a major source of airborne particulate matter(PM), nitrogen dioxide($NO_2$) and so on in metropolitan cities such as Seoul. Therefore workers, who are mainly merchants, near roadside may be highly exposed to air pollutants from exhausted emissions of vehicles. This means that occupational type and location can affect the workers'health by exposure to outdoor pollutions of ambient as well as indoor pollutions of working condition, respectively. In this study, we simultaneously measured the PM3.5 and $NO_2$concentrations in indoor and outdoor of shoes repair shops in Seoul, which were generally located at roadside in Korea. Shoes repairmen were highly exposed to PM3.5 and $NO_2$ both indoor and outdoor of repair shops comparing with other sub-population groups. High exposure to air pollutants for shoes repairmen was considered to be outdoor source from exhausted emission of vehicles and indoor source from working condition. The $PM3.5/NO_2$ concentration ratio was $1.17{\pm}$0.59 in roadside, of which ratio was higher 7han ratios of other studies. This result suggested that major air pollutant in Seoul was fine particle. Also, this PM3.5 to $NO_2$ ratio will be used in environmental exposure and risk assessment by estimation of PM3.5 concentration as measuring the only $NO_2$ concentration with small and accurate $NO_2$ passive sampler.

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Dimethylsulfide (DMS) in the Coastal Areas of the Cheju Island, Korea (제주도 연안해역을 중심으로 한 DMS 농도의 관측)

  • 김기현;이강웅;허철구;강창희
    • Journal of Korean Society for Atmospheric Environment
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    • v.13 no.2
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    • pp.161-170
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    • 1997
  • The concentrations of dimethylsulfide (DMS) were determined using samples collected from a station located at Kosan, Cheju Island during two field campaigns held in December 1996 and January 1997. The atmospheric DMS concentrations measured at 6-hr intervals during the entire campaign periods, after excluding a few extreme values, spanned in the range of 14 to 410 pptv with mean and 1 SD value of 127 $\pm$ 94 pptv (N=42). Between two month periods during which the field campaigns were conducted, a notable reduction in DMS levels was observed which was comparable to the dramatic shift in air temperature. A considerable difference was also noted in DMS levels, when data were grouped by day/night basis. The cause of unexpected, high day-to-night DMS ratios is best explained in terms of high efficiency of daytime source processes relative to low efficiency of nighttime sink processes due to the characteristics of the study location. The surface water DMS of the study site, although scarcely measured, also behaved similarly to its atmospheric counterpart with its range from 0.3 to 19 nM (N=11). When correlation analysis was conducted between the atmospheric DMS concentration and other concurrently determined parameters, significant correlations were observed from most basic meteorological parameters such as windspeed, relative humidy, and air temperature. However, the existence of "not-so-strong" correlations between air temperature and DMS concentrations relative to other ones indicated that the effect of temperature on DMS behavior must be reflected in more complicated manners at the study site. The sea-to-air flux of DMS was approximated through an application of the mass-balance flux calculation method of Wylie and de Mora (1996) under the assumption that sink mechanism within the marine boundary layer is in steady-state condition with its counterpart, source mechanism. Based on this estimation method, we reached a conclusion that oceanic DMS emitted from the southwest sea of the Korean Peninsula can amount to approximately 9 $\sim$ 36 Gg S $yr^{-1}$.$yr^{-1}$.

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Intelligent Collision Prevention Technique for Construction Equipment using Ultrasound Scanning (초음파 스캐닝을 활용한 지능형 건설기계 충돌방지 기술)

  • Lee, Jaehoon;Hwang, Yeongseo;Yang, Kanghyeok
    • Korean Journal of Construction Engineering and Management
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    • v.22 no.5
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    • pp.48-54
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    • 2021
  • According to the Ministry of Employment and Labor's statistics on occupational fatalities in South Korea, more than half of the fatalities in the past five years have occurred in the construction industry. The stuck-by and caught-in-between accidents associated with construction equipment is the major source of fatalities from construction sites. In order to prevent such accidents in construction sites, the government has spent lots of efforts including proposing the "special law on construction safety" and encouraging the implementation of new technology for accident prevention. However, numerous accidents are still occurred at construction sites and further efforts are still required. In this manner, this study developed a collision prevention technique that can prevent collision between equipment and worker by recognizing location and type of the nearby objects through ultrasound scanning. The study conducted a pilot experiment and the analysis results demonstrate the feasibility of achieving high performance in both object recognition and location estimation. The developed technique will contribute to prevent collision accidents at construction sites and provide the supplemental knowledge on developing automated collision prevention system for construction equipment.

Machine Learning-based Estimation of the Concentration of Fine Particulate Matter Using Domain Adaptation Method (Domain Adaptation 방법을 이용한 기계학습 기반의 미세먼지 농도 예측)

  • Kang, Tae-Cheon;Kang, Hang-Bong
    • Journal of Korea Multimedia Society
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    • v.20 no.8
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    • pp.1208-1215
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    • 2017
  • Recently, people's attention and worries about fine particulate matter have been increasing. Due to the construction and maintenance costs, there are insufficient air quality monitoring stations. As a result, people have limited information about the concentration of fine particulate matter, depending on the location. Studies have been undertaken to estimate the fine particle concentrations in areas without a measurement station. Yet there are limitations in that the estimate cannot take account of other factors that affect the concentration of fine particle. In order to solve these problems, we propose a framework for estimating the concentration of fine particulate matter of a specific area using meteorological data and traffic data. Since there are more grids without a monitor station than grids with a monitor station, we used a domain adversarial neural network based on the domain adaptation method. The features extracted from meteorological data and traffic data are learned in the network, and the air quality index of the corresponding area is then predicted by the generated model. Experimental results demonstrate that the proposed method performs better as the number of source data increases than the method using conditional random fields.

Spatial Spectrum Estimation of Broadband Incoherent Signals using Rotation of Signal Subspace Via Signal Enhancement (신호부각에 의한 신호 부공간 회전을 이용한 광대역 인코히어런트 신호의 공간 스펙트럼 추정)

  • 김영수;이계산;김정근
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.15 no.7
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    • pp.669-676
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    • 2004
  • In this paper, a new algorithm is proposed for resolving multiple broadband incoherent sources incident on a uniform linear array. The proposed method dose not require any initial estimates for finding the transformation matrix, while the Coherent Signal-Subspace Method(CSM) proposed by Wang and Kaveh requires preliminary estimates of multigroup source location. An effective procedure is derived for finding the enhanced spectral density matrix at the center frequency using signal enhancement approach and then constructing a common signal subspace by selecting a unitary transformation matrix which is obtained via rotation of signal subspace method. The proposed approach is found to provide superior performance relative to that obtained with the CSM method in terms of sample bias of direction-of-arrival estimates.

EXTRACTING OUTLINE AND ESTIMATING HEIGHT OF LAND FEATURES USING LIDAR DATA

  • Lee, Woo-Kyun;Song, Chul-Chul
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.181-183
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    • 2006
  • Digital topographic map in Korea contains layers of spatial and attribute data for 8 land features such as railroads, watercourses, roads, buildings and etc. Some of the layers such as building and forest don't include any information about height, which can be just prepared by interpretation of remote sensed data or field survey. LiDAR(Light Detection And Ranging) data using active pulse and digital camera provides data about height and form of land features. LiDAR data can be used not only to extract the outline of land features but also to estimate the height. This study presents technical availability for extraction and estimation of land feature's outline and height using LiDAR data which composes of natural and artificial land features, and digital aerial photograph which was taken simultaneously with the LiDAR. The estimated location, outline and height of land features were compared with the field survey data, and we could find that LiDAR data and digital aerial photograph can be a useful source for estimating the height of land features as well as extracting the outline.

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