• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.1144-1153
• /
• 2015

The resonant mechanism of reradiation interference (RRI) over 1.7MHz from power transmission lines cannot be obtained from IEEE standards, which are based on researches of field intensity. Hence, the resonance is ignored in National Standards of protecting distance between UHV power lines and radio stations in China, which would result in an excessive redundancy of protecting distance. Therefore, based on the generalized resonance theory, we proposed the idea of applying model-based parameter estimation (MBPE) to estimate the generalized resonance frequency of electrically large scattering objects. We also deduced equation expressions of the generalized resonance frequency and its quality factor Q in a lossy open electromagnetic system, i.e. an antenna-transmission line system in this paper. Taking the frequency band studied by IEEE and the frequency band over 1.7 MHz as object, we established three models of the RRI from transmission lines, namely the simplified line model, the tower line model considering cross arms and the line-surface mixed model. With the models, we calculated the scattering field of sampling points with equal intervals using method of moments, and then inferred expressions of Padé rational function. After calculating the zero-pole points of the Padé rational function, we eventually got the estimation of the RRI’s generalized resonant frequency. Our case studies indicate that the proposed estimation method is effective for predicting the generalized resonant frequency of RRI in medium frequency (MF, 0.3~3 MHz) band over 1.7 MHz, which expands the frequency band studied by IEEE.

• Geophysics and Geophysical Exploration
• /
• v.19 no.3
• /
• pp.136-144
• /
• 2016

Since seismic inversion is based on the wave equation, it is important to calculate the solution of wave equation exactly. In particular, full waveform inversion would produce reliable results only when the forward modeling is accurately performed because it uses full waveform. When we use finite-difference or finite-element method to solve the wave equation, the convergence of numerical scheme should be guaranteed. Although the general proof of convergence is provided theoretically, the consistency and stability of numerical schemes should be verified for practical applications. The implementation of source function is the most crucial factor for the consistency of modeling schemes. While we have to use the sinc function normalized by grid spacing to correctly describe the Dirac delta function in the finite-difference method, we can simply use the value of basis function, regardless of grid spacing, to implement the Dirac delta function in the finite-element method. If we use frequency-domain wave equation, we need to use a conservative criterion to determine both sampling interval and maximum frequency for the source wavelet generation. In addition, the source wavelet should be attenuated before applying it for modeling in order to make it obey damped wave equation in case of using complex angular frequency. With these conditions satisfied, we can develop reliable inversion algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.1
• /
• pp.51-66
• /
• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.403-406
• /
• 2005

In order to evaluate the Capability of ETM+ remotely- sensed data to provide 'Forest-shrub land-Rangeland' cover type map in areas near the timberline of northern forests of Iran, the data were analyzed in a portion of nearly 790 ha located in Neka-Zalemroud region. First, ortho-rectification process was used to correct the geometric errors of the image, yielding 0/68 and 0/69 pixels of RMS. error in X and Y axis, respectively. The original and panchromatic bands were fused using PANSHARP Statistical module. The ground truth map was made using 1 ha field plots in a systematic-random sampling grid, and vegetative form of trees, shrubs and rangelands was recorded as a criteria to name the plots. A set of channels including original bands, NDVI and IR/R indices and first components of PCI from visible and infrared bands, was used for classification procedure. Pair-wise divergence through CHNSEL command was used, In order to evaluate the separability of classes and selection of optimal channels. Classification was performed using ML classifier, on both original and fused data sets. Showing the best results of $67\%$ of overall accuracy, and 0/43 of Kappa coefficient in original data set. Due to the results represented above, it's concluded that ETM+ data has an intermediate capability to fulfill the spectral variations of three form- based classes over the study area.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.5
• /
• pp.2205-2210
• /
• 2015

Experimental studies have been carried out to study the principle operation of the conductive type wire-mesh tomography sensor and analyse the wire-mesh tomography sensor for the liquid/gas two-phase flow interface and void fraction distribution in a process column. The measurement of the two-phase flows in the process column is based on the cross-sectional local instantaneous conductivity. The sensor consists of two planes of parallel electrode wires with 16 electrodes each and was placed orthogonally with each plane. The sensor electrode wires were made of tinned copper wire with an outer diameter of 0.91 mm which stretched over the sensor fixture. Therefore, this result in the mesh grid size with 5.53×5.53mm². The wire-mesh sensor was tested in a horizontal liquid/gas two-phase flows process column with nominal diameter of 95.6 mm and the sampling frequency of 5882.3529 Hz. The tomogram results show that the wire-mesh tomography provides significant results to represent the void fraction distribution in the process column and estimation error was found in the liquid/gas interface level

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.10
• /
• pp.118-128
• /
• 2015

Compressive sensing (CS) has to face with two challenges of computational complexity reconstruction and low coding efficiency. As a solution, this paper presents a novel spatially scalable Kronecker two layer compressive sensing framework which facilitates reconstruction up to three spatial resolutions as well as much improved CS coding performance. We propose a dual-resolution sensing matrix based on the quincunx sampling grid which is applied to the base layer. This sensing matrix can provide a fast-preview of low resolution image at encoder side which is utilized for predictive coding. The enhancement layer is encoded as the residual measurement between the acquired measurement and predicted measurement data. The low resolution reconstruction is obtained from the base layer only while the high resolution image is jointly reconstructed using both two layers. Experimental results validate that the proposed scheme outperforms both conventional single layer and previous multi-resolution schemes especially at high bitrate like 2.0 bpp by 5.75dB and 5.05dB PSNR gain on average, respectively.

• Journal of Soil and Groundwater Environment
• /
• v.15 no.6
• /
• pp.17-28
• /
• 2010

As a preliminary survey to improve efficiency of well-based permeable reactive barrier system for groundwater remediation, this site-scale study was carried to identify the flowpaths and controlling factors of plume at a remediation site in Suwon City, Korea. A total of 22 monitoring wells were installed as a grid system in the $4m{\times}4m$ square area by 1-m interval. For the groundwater characterization, various tests were performed including water-level monitoring, water sampling & analysis, pumping and slug tests, and tracer tests. The aquifer appeared to be unconfined with hydraulic conductivities (K) ranging from $2.6{\times}10^{-4}cm/s$ to $9.5{\times}10^{-3}cm/s$. The average linear velocity of groundwater was estimated to be $2.94{\times}10^{-6}m/s$, and the longitudinal dispersivity of a conservative tracer to be $5.94{\times}10^{-7}m^2/s$. Groundwater plume moves preferentially through the high-K zones, and the relatively high ion concentrations along the low-K zones implying deterred groundwater flow. Consequently, the spatial variation of hydraulic conductivity caused by aquifer heterogeneity and anisotropy appears to be the most important factor to maximize the effect of plume treatment system for application of in-situ groundwater remediation techniques.

• Journal of KIISE:Software and Applications
• /
• v.26 no.11
• /
• pp.1306-1313
• /
• 1999

본 연구는 인터넷 기반 공유가상공간에서 시스템의 확장성을 유지하기 위하여 이동객체를 대상으로 하는 이벤트 필터링 기법을 제안하고자 한다. 제안된 다중격자 모델 기법은 이동객체의 경로 상에서 대표적인 이벤트를 샘플링하는 방식을 사용한다. 이 방식은 메시지 트래픽의 양을 동적으로 조절하기 위하여 이동객체 간의 관심정도 정보를 수치적으로 변환하여 이벤트 갱신빈도에 반영한다. 대량의 이동객체를 생성하여 제안된 기법을 적용한 성능평가 실험에서 기존의 방식에 비하여 평균 메시지 전송량이 50%이상 감소하는 것으로 확인할 수 있었다. 다중격자 모델은 참여자의 수와 메시지 트래픽 상황에 따라 가상환경의 공유 QoS를 동적으로 조절할 수 있으며, 인터넷 상에서 다수 사용자를 위한 3차원 가상사회 구축 및 온라인 네트워크 게임 개발 등에 활용될 수 있을 것이다.Abstract This paper proposes an event filtering technique that can dynamically control a large amount of event messages produced by moving objects like avatars or autonomous objects in a distributed virtual environment. The proposed multi-level grid model technique uses the method that extracts the representative events from the paths of moving objects. For dynamic control of message traffics, this technique digitizes the DOIs of the avatars and reflects the interest information controlling the frequency of message transmission. For the performance evaluation, a large number of moving objects were created and the model was applied to these avatar groups. In the experiments, more than 50% of messages have been reduced in comparison with the existing AOI-based filtering techniques. The proposed technique can dynamically control the QoS in proportion to the number of users and the amount of messages where a large number of users share a virtual space. This model can be applied to the development of 3D collaborative virtual societies and multi-user online games in the Internet.

• Journal of the Korean association of regional geographers
• /
• v.12 no.5
• /
• pp.614-630
• /
• 2006

Improved estimates of populations at risk for quick and effective response to natural and man-made disasters require spatial disaggregation of zonal population data because of the spatial mismatch problem in areal units between census and impact zones. This paper implements a dasymetric surface model to facilitate spatial disaggregation of the population of a census block group into populations associated with each constituent pixel and evaluates the performance of the surface-based spatial disaggregation model visually and statistically. The surface-based spatial disaggregation model employed geographic information systems (GIS) to enable dasymetric interpolation to be guided by satellite-derived land use and land cover data as additional information about the geographic distributor of population. In the spatial disaggregation, percent cover based empirical sampling and areal weighting techniques were used to objectively determine dasymetric weights for each grid cell. The dasymetric population surface for the Atlanta metropolitan area was generated by the surface-based spatial disaggregation model. The accuracy of the dasymetric population surface was tested on census counts using the root mean square error (RMSE) and an adjusted RMSE. The errors related to each census track and block group were also visualized by percent error maps. Results indicate that the dasymetric population surface provides high-precision estimates of populations as well as the detailed spatial distribution of population within census block groups. The results also demonstrate that the population surface largely tends to overestimate or underestimate population for both the rural and forested and the urban core areas.

• Economic and Environmental Geology
• /
• v.56 no.3
• /
• pp.331-341
• /
• 2023

When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.