• Title/Summary/Keyword: Cloud Modeling

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Estimation of Cloud Liquid Watetr used by GMS-5 Observations (GMS-5 자료를 이용한 구름 수액량 추정 연구)

  • 차주완;윤홍주
    • Korean Journal of Remote Sensing
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    • v.15 no.1
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    • pp.21-30
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    • 1999
  • The CLW (Cloud Liquid Water) is a parameter of vital interest in both modeling and forecasting weather. In mesoscale models, the magnitude of latent heat effects corresponds to the amount of CLW, which is important in the development of a certain weather system. The goal of this study is the estimation of CLW by GMS-5 data which is compared with that of SSM/I data and GMR(Grounded Microwave Radiometer)data. First of all, we found out the relationship of cloud albedo to cloud thickness, and caculated the CLW using the result of the relationship. The CLW amount of SSM/I or GMR and that of GMS-5 were compared, respectively. The correlation coefficient was about 0.86 and RMSE was 9.23 mg/$cm^2$ between GMS-5 data and GMR data. And also the correlation coefficient was 0.84 and RMSE was 14.02 mg/$cm^2$ between GMS-5 data and SSM/I data.

Direct Observation of Radiative Flux in the Southern Yellow Sea

  • Lu, Lian-Gang;Yu, Fei;Diao, Xinyuan;Guo, Jingsong;Wang, Huiwu;Wei, Chuanjie
    • Ocean Science Journal
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    • v.43 no.2
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    • pp.115-126
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    • 2008
  • Direct measurements of four radiative components at air-sea boundary layer were conducted in the southern Yellow Sea during three cruises (seasons) in 2007. Simultaneous observations of meteorological (cloud cover, air temperature and humidity) and oceanographic (sea surface temperature) parameters were carried out. Observational results of radiative fluxes and meteorological and oceanographic parameters are presented. Mean diurnal cycles of four radiative components, net radiation, and sea surface albedo are calculated to achieve averages in different seasons. Net radiative fluxes in three seasons (winter, spring, autumn) are 8, 146, $60\;W/m^2$, respectively. Comparisons between the observed radiative fluxes and those estimated with formulas are taken.

Modeling of Solar Radiation Using Silicon Solar Module

  • Kim, Joon-Yong;Yang, Seung-Hwan;Lee, Chun-Gu;Kim, Young-Joo;Kim, Hak-Jin;Cho, Seong-In;Rhee, Joong-Yong
    • Journal of Biosystems Engineering
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    • v.37 no.1
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    • pp.11-18
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    • 2012
  • Purpose: Short-circuit current of a solar module that is widely used as a power source for wireless environmental sensors is proportional to solar radiation although there are a lot of factors affecting the short-circuit current. The objective of this study is to develop a model for estimating solar radiation for using the solar module as a power source and an irradiance sensor. Methods: An experiment system collected data on the short-circuit current and environmental factors (ambient temperature, cloud cover and solar radiation) during 65 days. Based on these data, two linear regression models and a non-linear regression model were developed and evaluated. Results: The best model was a linear regression model with short-circuit current, angle of incidence and cloud cover and its overall RMSE(Root Means Square Error) was 66.671 $W/m^2$. The other linear model (RMSE 69.038 $W/m^2$) was also acceptable when the cloud cover data is not available.

3D Scanning Data Coordination and As-Built-BIM Construction Process Optimization - Utilization of Point Cloud Data for Structural Analysis

  • Kim, Tae Hyuk;Woo, Woontaek;Chung, Kwangryang
    • Architectural research
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    • v.21 no.4
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    • pp.111-116
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    • 2019
  • The premise of this research is the recent advancement of Building Information Modeling(BIM) Technology and Laser Scanning Technology(3D Scanning). The purpose of the paper is to amplify the potential offered by the combination of BIM and Point Cloud Data (PCD) for structural analysis. Today, enormous amounts of construction site data can be potentially categorized and quantified through BIM software. One of the extraordinary strengths of BIM software comes from its collaborative feature, which can combine different sources of data and knowledge. There are vastly different ways to obtain multiple construction site data, and 3D scanning is one of the effective ways to collect close-to-reality construction site data. The objective of this paper is to emphasize the prospects of pre-scanning and post-scanning automation algorithms. The research aims to stimulate the recent development of 3D scanning and BIM technology to develop Scan-to-BIM. The paper will review the current issues of Scan-to-BIM tasks to achieve As-Built BIM and suggest how it can be improved. This paper will propose a method of coordinating and utilizing PCD for construction and structural analysis during construction.

Precision Measurement of Vehicle Shape using Industrial Photogrammetry (산업 사진측량에 의한 자동차의 외형 정밀 측정)

  • 정성혁;박찬홍;이재기
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.2
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    • pp.179-186
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    • 2004
  • This study describes that the method of precision measurement of vehicle shape and the method of measurement the deformation that it is occurred the reason of accident using industrial photogrammatry. The curved shape is measured using the projection target which is able to acquire the point cloud data. 3D coordinates of the target were able to acquire through object picturing and analysis of coordinates. The acquired point cloud data was done 3D modeling to form the surface with TIN. Also, It able to interpretate a deformation surveying accurately the occurred parts of deformation, then can furnish to the analysis of traffic accident the precise and effective data.

3D Shape Descriptor for Segmenting Point Cloud Data

  • Park, So Young;Yoo, Eun Jin;Lee, Dong-Cheon;Lee, Yong Wook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.6_2
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    • pp.643-651
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    • 2012
  • Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

Trends in Infertility Research in South Korea: Text Network Analysis and Topic Modeling Analysis

  • Gie Ok Noh
    • International Journal of Advanced Culture Technology
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    • v.12 no.4
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    • pp.190-196
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    • 2024
  • This study was conducted to identify the research trends and key concepts of fertility-related research published in Korea. For the analysis of this study, target papers published from 2014 to 2023 were collected by entering the keywords of 'infertility' or 'Sterility'. 155 papers were analyzed. The co-occurrence network of key words was developed and analyzed, and the research trends were examined through topic modeling of the LSD, and visualized word cloud and sociogram were used. The most common key words across the 155 research studies were infertility, infertile women, assisted reproductive technology, women, and depression. Highly connected keywords were the same as the top 5 most frequent keywords, and highly mediated keywords were fertility, infertile women, assisted reproductive technology, bioethics, and low birthrate. The four topics analyzed were identified as 'infertile women's experiences and care,' 'psychological problems of infertile women,' 'Korean medicine approaches to infertility,' and 'low fertility and fertility procedures'. Based on the results of this study has identified themes and trends in infertility research over the past decade and suggests that future research should focus on intervention studies and policy development for psychological issues related to infertility.

Classification of Public Perceptions toward Smog Risks on Twitter Using Topic Modeling (Topic Modeling을 이용한 Twitter상에서 스모그 리스크에 관한 대중 인식 분류 연구)

  • Kim, Yun-Ki
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.1
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    • pp.53-79
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    • 2017
  • The main purpose of this study was to detect and classify public perceptions toward smog disasters on Twitter using topic modeling. To help achieve these objectives and to identify gaps in the literature, this research carried out a literature review on public opinions toward smog disasters and topic modeling. The literature review indicated that there are huge gaps in the related literature. In this research, this author formed five research questions to fill the gaps in the literature. And then this study performed research steps such as data extraction, word cloud analysis on the cleaned data, building the network of terms, correlation analysis, hierarchical cluster analysis, topic modeling with the LDA, and stream graphs to answer those research questions. The results of this research revealed that there exist huge differences in the most frequent terms, the shapes of terms network, types of correlation, and smog-related topics changing patterns between New York and London. Therefore, this author could find positive answers to the four of the five research questions and a partially positive answer to Research question 4. Finally, on the basis of the results, this author suggested policy implications and recommendations for future study.

3D Reconstruction of Structure Fusion-Based on UAS and Terrestrial LiDAR (UAS 및 지상 LiDAR 융합기반 건축물의 3D 재현)

  • Han, Seung-Hee;Kang, Joon-Oh;Oh, Seong-Jong;Lee, Yong-Chang
    • Journal of Urban Science
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    • v.7 no.2
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    • pp.53-60
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    • 2018
  • Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

The Improvement of Point Cloud Data Processing Program For Efficient Earthwork BIM Design (토공 BIM 설계 효율화를 위한 포인트 클라우드 데이터 처리 프로그램 개선에 관한 연구)

  • Kim, Heeyeon;Kim, Jeonghwan;Seo, Jongwon;Shim, Ho
    • Korean Journal of Construction Engineering and Management
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    • v.21 no.5
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    • pp.55-63
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    • 2020
  • Earthwork automation has emerged as a promising technology in the construction industry, and the application of earthwork automation technology is starting from the acquisition and processing of point cloud data of the site. Point cloud data has more than a million data due to vast extent of the construction site, and the processing time of the original point cloud data is critical because it takes tens or hundreds of hours to generate a Digital Terrain Model (DTM), and enhancement of the processing time can largely impact on the efficiency of the modeling. Currently, a benchmark program (BP) is actively used for the purpose of both point cloud data processing and BIM design as an integrated program in Korea, however, there are some aspects to be modified and refined. This study modified the BP, and developed an updated program by adopting a compile-based development environment, newly designed UI/UX, and OpenGL while maintaining existing PCD processing functions, and expended compatibility of the PCD file formats. We conducted a comparative test in terms of loading speed with different number of point cloud data, and the results showed that 92 to 99% performance increase was found in the developed program. This program can be used as a foundation for the development of a program that reduces the gap between design and construction by integrating PCD and earthwork BIM functions in the future.