• Title/Summary/Keyword: 데이터밀도

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Recent Developments and Field Application of Foreign Waterworks Automatic Meter Reading (국외 상수도 원격검침시스템의 개발 동향 및 현장 적용 사례 고찰)

  • Joo, Jin Chul;Ahn, Hosang;Ahn, Chang Hyuk;Ko, Kyung-Rok;Oh, Hyun-Je
    • Journal of Korean Society of Environmental Engineers
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    • v.34 no.12
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    • pp.863-870
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    • 2012
  • The market trends of automatic meter reading associated with smart water meters were investigated. Also, recent developments and field applications of key technology for automatic meter reading associated with smart water meters were analyzed. Smart water meters have been manufactured mostly in United States and Europe and have been expanded their business to Asia. Integrated water management system combining with the additional functions such as real-time consumption metering, cost notification, water conservation, leak detection, water quality monitoring, and flow control have been operated in automatic meter reading. Both water quality and quantity data measured from smart water meters and sensors were transferred to data concentration units through neighborhood area network, and then were transferred to integrated server through wide area network. The data transfer methods were determined by comprehensively considering urban scale, density of smart water meters, power supply and network topologies. Common data collection methods such as fixed network to data concentation units, vehicles drive by, people walk by, and drone fly by have been applied. The automatic meter reading associated with smart water meters are spread throughout the world, and both water and energy savings result in saving the money and reducing the greenhouse gases emission.

Analysis of Geographic Network Structure by Business Relationship between Companies of the Korean Automobile Industry (한국 자동차산업의 기업간 거래관계에 의한 지리적 네트워크 구조 분석)

  • KIM, Hye-Lim;MOON, Tae-Heon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.3
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    • pp.58-72
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    • 2021
  • In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.

Multi-fidelity Data-fusion for Improving Strain accuracy using Optical Fiber Sensors (이종 광섬유 센서 데이터 융합을 통한 변형률 정확도 향상 기법)

  • Park, Young-Soo;Jin, Seung-Seop;Yoo, Chul-Hwan;Kim, Sungtae;Park, Young-Hwan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.547-553
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    • 2020
  • As aging infrastructures increase along with time, the efficient maintenance becomes more significant and accurate responses from the sensors are pre-requisite. Among various responses, strain is commonly used to detect damage such as crack and fatigue. Optical fiber sensor is one of the promising sensing techniques to measure strains with high-durability, immunity for electrical noise, long transmission distance. Fiber Bragg Grating (FBG) is a point sensor to measure the strain based on reflected signals from the grating, while Brillouin Optic Correlation Domain Analysis (BOCDA) is a distributed sensor to measure the strain along with the optical fiber based on scattering signals. Although the FBG provides the signal with high accuracy and reproducibility, the number of sensing points is limited. On the other hand, the BOCDA can measure a quasi-continuous strain along with the optical fiber. However, the measured signals from BOCDA have low accuracy and reproducibility. This paper proposed a multi-fidelity data-fusion method based on Gaussian Process Regression to improve the fidelity of the strain distribution by fusing the advantages of both systems. The proposed method was evaluated by laboratory test. The result shows that the proposed method is promising to improve the fidelity of the strain.

Analysis of living population characteristics to measure urban vitality - Focusing on mobile big data - (도시활력 측정을 위한 생활인구 특성 분석 - 이동통신 빅데이터를 중심으로 -)

  • Yoko Kamata;Kwang Woo NAM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.173-187
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    • 2023
  • In an era of population decline, depopulated regions facing challenges in attracting inbound population migration must enhance urban vitality through the attraction of living populations. This study focuses on Busan, a city experiencing population decline, comparing the spatiotemporal distribution characteristics of registered residents and living populations in various administrative districts (Eup-Myeon-Dong) using mobile communication big data. Administrative districts are typified based on population change patterns, and regional characteristics are analyzed using indicators related to urban decline and vitality. Spatiotemporal distribution analysis reveals generally similar density patterns between registered residents and living populations; however, a distinctive feature is observed in the city center areas where the density of registered residents is low, while the density of living populations is high. Divergent trends in spatial patterns of change between registered residents and living populations show clusters of registered population decline in low-density areas and clusters of living population decline in high-density areas. Areas adjacent to declining living populations exhibit large clusters of population changes, indicating a spillover effect from high-density to neighboring areas. Typification results reveal that, even in areas with a decline in registered residents, there is active population influx due to commuting or visiting. These areas sustain an increase in the number of businesses, confirming the presence of industrial and economic growth. However, approximately 47% of administrative districts in Busan are experiencing a decline in both registered residents and living populations, indicating ongoing regional decline. Urgent measures are needed for enhancing urban vitality. The study emphasizes the necessity of utilizing living population data as an urban planning indicator, considering the increasing limit distance of urban activities and growing interregional interaction due to advancements in transportation and communication.

Statistical Analysis of Protein Content in Wheat Germplasm Based on Near-infrared Reflectance Spectroscopy (밀 유전자원의 근적외선분광분석 예측모델에 의한 단백질 함량 변이분석)

  • Oh, Sejong;Choi, Yu Mi;Yoon, Hyemyeong;Lee, Sukyeung;Yoo, Eunae;Hyun, Do Yoon;Shin, Myoung-Jae;Lee, Myung Chul;Chae, Byungsoo
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.64 no.4
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    • pp.353-365
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    • 2019
  • A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R2, and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.

A study on solar radiation prediction using medium-range weather forecasts (중기예보를 이용한 태양광 일사량 예측 연구)

  • Sujin Park;Hyojeoung Kim;Sahm Kim
    • The Korean Journal of Applied Statistics
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    • v.36 no.1
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    • pp.49-62
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    • 2023
  • Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

A STUDY OF THE IONOSPHERIC ELECTRON MEASUREMENT ON THE MEDIUM-SIZED SCIENTIFIC ROCKET , KSR-II (중형과학로켓, KSR-II를 이용한 이온층 전자 밀도 및 온도 분포 측정에 관한 연구)

  • Lee, Jae-Jin;Kim, Jhoon;Lee, Soo-Jin;Min, Kyoung-Wook;Pyo, You-Surn;Cho, Gwang-Rae;Rhee, Hwang-Jae
    • Journal of Astronomy and Space Sciences
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    • v.15 no.2
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    • pp.401-415
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    • 1998
  • This paper reports the results obtained from the Langmuir probe (LP) and Electron Temperature Probe (ETP) experiments on the sounding rocket KSR-II (Korean Scientific Rocket - II) which was launched on Jun 11, 1998 at 10:00 KST from Tae-An peninsula (37$^{\circ}$ N, 126$^{\circ}$ E). The instruments successfully measured the electron density, electron temperature, and the floating potential at altitudes of 73km to 130km. While the electron temperature measurement is not easy in this region, since the temperature is very low and the contamination effect of the probe may give rise to a problem, we were able to obtain a reasonable electron temperature profile by employing two independent methods, the pulse modulated Langmuir Probe and Electron Temperature Probe. The preliminary results show that electron density increases sharply at about 90km, and forms a peak at 102km. The density profile is roughly consistent with IRI (International Reference Ionosphere)95-model or PIM (Parameterized Ionospheric Model) results except that the peak density appears at 110km in the model and model electron density is slightly lower than the observed one. Electron temperature obtained from ETP fluctuates between 200$^{\circ}$K and 700$^{\circ}$K, an effect presumably coming from the wakes developed by LP, and it tends to increase with the altitude, which is consistent with the LP results.

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A Stability Test of the Regression Coefficients for the Linear Models using Chow Test (차우검정을 활용한 선형회귀모형간 유사성 검증)

  • Lee, Ki-Young;Lee, Seongkwan Mark;Jeong, So-Young;Heo, Tae-Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.2
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    • pp.73-82
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    • 2017
  • In this research, we tried to check the applicability of a Chow test to the linear models which are generated in the process of transportation planning or traffic flow analyses. The Chow test is a very popular statistical method which is being used to see if the coefficients from two separate linear regression models are equal or not. In order to prove the effectiveness of the Chow test, we found the linear relationships between speed and density under the situations such as driving in daytime and in nighttime on a rainy day. Based on the two months of Joong-Bu Expressway traffic data, we proved that the Chow test is useful to testify the similarity between two linear regression models. And this statistical tool seems to be able to have a very important role in traffic flow analysis or in transportation planning process. Finally, we expect the Chow test be implemented even to the non-linear regression models or to the multi-variate models.

An Analysis on the Characteristics of Wind Distribution in the Coast of Busan Using AWS Data (AWS 데이터를 이용한 부산 해안의 바람분포 특성 해석)

  • Seol, Dong-Il
    • Journal of Navigation and Port Research
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    • v.33 no.8
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    • pp.549-554
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    • 2009
  • Wind velocity and wind direction are very important in the viewpoint of ship's safety and stability of port structure. The characteristics of wind distribution in the coast of Busan are analyzed for 10 years from 1997 to 2006 using AWS(Automatic Weather System) data. The characteristics of wind distribution of Miryang, is not affected by the land and sea breeze are also examined to understand clearly the characteristics of wind distribution in the coast of Busan. The mean wind velocity in the coast of Busan is stronger than that of Miryang. The mean wind velocitie at Youngdo and Gadukdo stations of Busan are stronger about 2.0 times than those at IlGwang, Haeundae and Daeyeon stations. The correlation a states show that the variation tendencies of monthly mean wind velocitie in the coast of Busan are very similar. The maximum monthly mean velocitie in the coast of Busan are recorded in September. This re ult is closely related to the influence of typhoon. The maximum instantaneous wind velocitie are also strong at Youngdo and Gadukdo stations and the peaks of maximum instantaneous wind $velocit^9$ are observed mainly from August to September. In the coast of Busan, the SW'ly-NNE'ly wind are prevailing in the winter and the SW'ly and NE'ly wind are predomi snt in the spring. w that the vs of wind direction in the summer and athumn are similar with those in the spring and winter, respectively.

Estimation of Mass Size Distribution of Atmospheric Aerosols Using Real-Time Aerosol Measuring Instruments (실시간 에어로졸 측정장비를 이용한 대기 중 입자상 물질의 무게 농도 분포의 추정)

  • Ji, Jun-Ho;Bae, Gwi-Nam
    • Particle and aerosol research
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    • v.9 no.2
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    • pp.39-50
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    • 2013
  • Real-time aerosol measuring instruments have been widely used for the measurement of atmospheric aerosol, diesel particulate matter, or material synthesis. A scanning mobility particle sizer (SMPS) measures the number size distribution of particles using electrical mobility detection technique. An aerodynamic particle sizer (APS) is used to determine the number concentration and the mean aerodynamic diameter of test particles. An electrical low-pressure impactor (ELPI) is a multi-stage impaction device to separate airborne particles into aerodynamic size classes using particle charging and electrical detection techniques. In this study, the performance of these instruments were evaluated to assess their ability to obtain mass concentrations from particle number concentration measurements made as a function of particle size. The effect of determination of particle density on the measurement of mass concentration was investigated for the three instruments.