• Title/Summary/Keyword: data field

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CONTINUOUS DATA ASSIMILATION FOR THE THREE-DIMENSIONAL SIMPLIFIED BARDINA MODEL UTILIZING MEASUREMENTS OF ONLY TWO COMPONENTS OF THE VELOCITY FIELD

  • Anh, Cung The;Bach, Bui Huy
    • Journal of the Korean Mathematical Society
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    • v.58 no.1
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    • pp.1-28
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    • 2021
  • We study a continuous data assimilation algorithm for the three-dimensional simplified Bardina model utilizing measurements of only two components of the velocity field. Under suitable conditions on the relaxation (nudging) parameter and the spatial mesh resolution, we obtain an asymptotic in time estimate of the difference between the approximating solution and the unknown reference solution corresponding to the measurements, in an appropriate norm, which shows exponential convergence up to zero.

An Adaptive Watermark Detection Algorithm for Vector Geographic Data

  • Wang, Yingying;Yang, Chengsong;Ren, Na;Zhu, Changqing;Rui, Ting;Wang, Dong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.1
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    • pp.323-343
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    • 2020
  • With the rapid development of computer and communication techniques, copyright protection of vector geographic data has attracted considerable research attention because of the high cost of such data. A novel adaptive watermark detection algorithm is proposed for vector geographic data that can be used to qualitatively analyze the robustness of watermarks against data addition attacks. First, a watermark was embedded into the vertex coordinates based on coordinate mapping and quantization. Second, the adaptive watermark detection model, which is capable of calculating the detection threshold, false positive error (FPE) and false negative error (FNE), was established, and the characteristics of the adaptive watermark detection algorithm were analyzed. Finally, experiments were conducted on several real-world vector maps to show the usability and robustness of the proposed algorithm.

Study of evaluation wind resource detailed area with complex terrain using combined MM5/CALMET system (고해상도 바람지도 구축 시스템에 관한 연구)

  • Lee, Hwa-Woon;Kim, Dong-Hyeuk;Kim, Min-Jung;Lee, Soon-Hwan;Park, Soon-Young;Kim, Hyun-Goo
    • 한국신재생에너지학회:학술대회논문집
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    • 2008.10a
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    • pp.274-277
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    • 2008
  • To evaluate high-resolution wind resources for local and coastal area with complex terrain was attemped to combine the prognostic MM5 mesoscale model with CALMET diagnostic modeling this study. Firstly, MM5 was simulated for 1km resolution, nested fine domain, with FDDA using QuikSCAT seawinds data was employed to improve initial meteorological fields. Wind field and other meteorological variables from MM5 with all vertical levels used as initial guess field for CALMET. And 5 surface and 1 radio sonde observation data is performed objective analysis whole domain cells. Initial and boundary condition are given by 3 hourly RDAPS data of KMA in prognostic MM5 simulation. Geophysical data was used high-resolution terrain elevation and land cover(30 seconds) data from USGS with MM5 simulation. On the other hand SRTM 90m resolution and EGIS 30m landuse was adopted for CALMET diagnostic simulation. The simulation was performed on whole year for 2007. Vertical wind field a hour from CALMET and latest results of MM5 simulation was comparison with wind profiler(KEOP-2007 campaign) data at HAENAM site.

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A Prediction of the Plane Failure Stability Using Artificial Neural Networks (인공신경망을 이용한 평면파괴 안정성 예측)

  • Kim, Bang-Sik;Lee, Sung-Gi;Seo, Jae-Young;Kim, Kwang-Myung
    • Proceedings of the Korean Geotechical Society Conference
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    • 2002.10a
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    • pp.513-520
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    • 2002
  • The stability analysis of rock slope can be predicted using a suitable field data but it cannot be predicted unless suitable field data was taken. In this study, artificial neural networks theory is applied to predict plane failure that has a few data. It is well known that human brain has the advantage of handling disperse and parallel distributed data efficiently. On the basis of this fact, artificial neural networks theory was developed and has been applied to various fields of science successfully In this study, error back-propagation algorithm that is one of the teaching techniques of artificial neural networks is applied to predict plane failure. In order to verify the applicability of this model, a total of 30 field data results are used. These data are used for training the artificial neural network model and compared between the predicted and the measured. The simulation results show the potentiality of utilizing the neural networks for effective safety factor prediction of plane failure. In conclusion, the well-trained artificial neural network model could be applied to predict the plane failure stability of rock slope.

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Electrical resistivity survey and interpretation considering excavation effects for the detection of loose ground in urban area

  • Seo Young Song;Bitnarae Kim;Ahyun Cho;Juyeon Jeong;Dongkweon Lee;Myung Jin Nam
    • Geomechanics and Engineering
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    • v.35 no.2
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    • pp.109-119
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    • 2023
  • Ground subsidence in urban areas due to excessive development and degraded underground facilities is a serious problem. Geophysical surveys have been conducted to estimate the distribution and scale of cavities and subsidence. In this study, electrical resistivity tomography (ERT) was performed near an area of road subsidence in an urban area. The subsidence arose due to groundwater leakage that carried soil into a neighboring excavation site. The ERT survey line was located between the main subsidence area and an excavation site. Because ERT data are affected by rapid topographic changes and surrounding structures, the influence of the excavation site on the data was analyzed through field-scale numerical modeling. The effect of an excavation should be considered when interpreting ERT data because it can lead to wrong anomalous results. A method for performing 2D inversion after correcting resistivity data for the effect of the excavation site was proposed. This method was initially tested using a field-scale numerical model that included the excavation site and subsurface anomaly, which was a loosened zone, and was then applied to field data. In addition, ERT data were interpreted using an existing in-house 3D algorithm, which considered the effect of excavation sites. The inversion results demonstrated that conductive anomalies in the loosened zone were greater compared to the inversion that did not consider the effects of excavation.

Numerical Interpolation on the Simulation of Air Flow Field and the Effect of Data Quality Control in Complex Terrain (객관 분석에 의한 복잡지형의 대기유동장 수치모의와 모델에 의한 자료질 조절효과)

  • Lee Hwa woon;Choi Hyun-Jung;Lee Kang-Yoel
    • Journal of Korean Society for Atmospheric Environment
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    • v.21 no.1
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    • pp.97-105
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    • 2005
  • In order to reduce the uncertainties and improve the air flow field, objective analysis using asynoptic observational data is chosen as a method that enhances the reality of meteorology. In surficial data and their numerical interpolation for improving the interpretation of meteorological components, objective analysis scheme should perform a smooth interpolation, detect and remove the bad data and carry out internal consistency analysis. For objective analysis technique which related to data reliability and error suppression, we carried out two quality control methods. In site quality control, asynoptic observational data at urban area revealed low representation by the complex terrain and buildings. In case of wind field, it was more effective than temperature field when it were interpolated near waterbody data. Many roads, buildings, subways, vehicles are bring about artificial heat which left out of consideration on the simulation of air flow field. Therefore, in temperature field, objective analysis for more effective result was obtained when surficial data were interpolated as many as possible using value quality control rather than the selection of representative site.

Precision Evaluation of Recent Global Geopotential Models based on GNSS/Leveling Data on Unified Control Points

  • Lee, Jisun;Kwon, Jay Hyoun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.2
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    • pp.153-163
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    • 2020
  • After launching the GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) which obtains high-frequency gravity signal using a gravity gradiometer, many research institutes are concentrating on the development of GGM (Global Geopotential Model) based on GOCE data and evaluating its precision. The precision of some GGMs was also evaluated in Korea. However, some studies dealt with GGMs constructed based on initial GOCE data or others applied a part of GNSS (Global Navigation Satellite System) / Leveling data on UCPs (Unified Control Points) for the precision evaluation. Now, GGMs which have a higher degree than EGM2008 (Earth Gravitational Model 2008) are available and UCPs were fully established at the end of 2019. Thus, EIGEN-6C4 (European Improved Gravity Field of the Earth by New techniques - 6C4), GECO (GOCE and EGM2008 Combined model), XGM2016 (Experimental Gravity Field Model 2016), SGG-UGM-1, XGM2019e_2159 were collected with EGM2008, and their precisions were assessed based on the GNSS/Leveling data on UCPs. Among GGMs, it was found that XGM2019e_2159 showed the minimum difference compared to a total of 5,313 points of GNSS/Leveling data. It is about a 1.5cm and 0.6cm level of improvement compare to EGM2008 and EIGEN-6C4. Especially, the local biases in the northern part of Gyeonggi-do, Jeju island shown in the EGM2008 was removed, so that both mean and standard deviation of the difference of XGM2019e_2159 to the GNSS/Leveling are homogeneous regardless of region (mountainous or plain area). NGA (National Geospatial-Intelligence Agency) is currently in progress in developing EGM2020 and XGM2019e_2159 is the experimentally published model of EGM2020. Therefore, it is expected that the improved GGM will be available shortly so that it is necessary to verify the precision of new GGMs consistently.

Development and Application of Total Maximum Daily Loads Simulation System Using Nonpoint Source Pollution Model (비점원오염모델을 이용한 오염총량모의시스템의 개발 및 적용)

  • Kang, Moon-Seong;Park, Seung-Woo
    • Journal of Korea Water Resources Association
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    • v.36 no.1
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    • pp.117-128
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    • 2003
  • The objectives of this study are to develop the total maximum daily loads simulation system, TOLOS that is capable of estimating annual nonpoint source pollution from small watersheds, to monitor the hydrology and water quality of the Balkan HP#6 watershed, and to validate TOLOS with the field data. TOLOS consists of three subsystems: the input data processor based on a geographic information system, the models, and the post processor. Land use pattern at the tested watershed was classified from the Landsat TM data using the artificial neutral network model that adopts an error back propagation algorithm. Paddy field components were added to SWAT model to simulate water balance at irrigated paddy blocks. SWAT model parameters were obtained from the GIS data base, and additional parameters calibrated with field data. TOLOS was then tested with ungauged conditions. The simulated runoff was reasonably good as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

Failure Data Error according to Characteristics of One-Shot Weapon System and its Solution (일회성 무기체계 특성에 따른 고장 데이터의 오차 및 극복방안)

  • Choi, Yunsuk;Ma, Jungmok
    • Journal of the Korea Institute of Military Science and Technology
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    • v.21 no.5
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    • pp.599-606
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    • 2018
  • Failure data of systems in many field can be erroneous, which influences the reliability analysis of the systems. The general form of failure data is right censored data with accurate time information. But due to its nature of data collection in the military field, failure time of one-shot weapon systems can have errors which are related to the maintenance period. So this paper suggests a model that can reduce the error by utilizing interval censored data as an alternative to right censored data in weibull distribution.

Automated data interpretation for practical bridge identification

  • Zhang, J.;Moon, F.L.;Sato, T.
    • Structural Engineering and Mechanics
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    • v.46 no.3
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    • pp.433-445
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    • 2013
  • Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.