• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.7
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• pp.1095-1103
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• 1999

Presently, the retractable phone with a whip antenna composed of a helix and a monopole is most widely used for cellular mobile communications. However, since the length of the monopole is usually about λ/4, the strong radiated electric fields are produced in the region where the auricle of a head is contacted directly. This field distribution results in high specific absorption rates(SAR's) in the head. In this paper, SAR distributions and local SAR values for the inversely shaped phone(ISP) whose antenna arrangement is opposite to the original retractable phone(ORP) are compared with those for the ORP. This phone is accomplished by mounting the $\lambda$/4-whip antenna on the bottom, not on the top of the handset. The time-averaged field distribution in a computational space including a human model and a phone model is computed using the finite-difference time-domain(FDTD) method. SAR distributions and local SAR values for these phones are calculated with the field distributions. An anatomical head model and an approximate hand model were used to consider a real situation. From the analyzed data, it is shown that this arrangement of the antenna considerably reduces the spatial peak SAR in a human head.

• Water for future
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• v.56 no.2
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• pp.62-68
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• 2023

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.346-349
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• 2005

In this paper, we propose SAR(Specific absorption rate) reduction methods based on surface electric field distribution relation. Proposed the new method that is able to consider improvement of the SAR from the very beginning step of developing the wireless transceiver. Analysis of wireless handset with human body(head) using finite element method(FEM). Results of this method, SAR reduced about 50 %.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.2
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• pp.149-158
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• 1998

The SAR patterns of biological objects contacted with coaxial waveguide antennal has been investigated, in which the biological object was modeled by a homogeneous and four-layered lossy human body. We derived the finite-difference time-domain(FDTD) algorithm and equation of MUR and generalized perfectly matched layer(GPML) ABCs in cylindrical coordination. The coupling between coaxial waveguide antenna and a biological object was analyzed by use of MUR and GPML ABCs in the FDTD method to obtain the absorbed power patterns in the media. The specific absorption rates (SAR) distribution which was corresponding to the temperature distribution was calculated in each region by use of the steady-state response in the FDTD method. The SAR patterns of the FDTD method using MUR absorbing boundary conditions(ABCs) was compared with those of the FDTD method using GPML ABCs. The comparison exhibits that the penetration depth of the SAR patterns using MUR ABCs is deeper than that of the SAR patterns using GPML ABCs because of loss in free space. However, the spread in the lateral directions of the SAR patterns using GPML ABCs is smaller than of the SAR patterns using MUR ABCs.

• Proceedings of the KSRS Conference
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• v.2
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• pp.981-984
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• 2006

Oil pollution of the ocean is a major environmental problem, especially in its coastal zones. Synthetic aperture radar (SAR) flown on satellites, such as ERS-2 and Envisat, has been proved to be a useful tool in oil spill monitoring due to its wide coverage, day and night, and all-weather capability. The total 120 SAR images containing oil spill over the East China Sea were collected and analyzed, ranging in date from July 23, 2002 to November 11, 2005. After preprocessed, SAR images were segmented by adaptive threshold method. The oil spill images were incorporated into GIS after distinguished from look-like phenomena, finally we presented the oil spills distribution map for the East China Sea. The wide-swath and quick-looks SAR imagery for mapping of oil spill distribution over large marine areas were proved to be useful when full resolution data are not available. After the temporal and spatial distribution of the oil spills were analyzed, we found that most of oil spills were distributed along the main ship routes, which means the illegal discharge by ships, and the occurrence of oil spill detected on SAR images acquired during morning and summer is much higher than during evening and winter.

• Journal of Soil and Groundwater Environment
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• v.27 no.3
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• pp.22-40
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• 2022

The goal of this study was to estimate the possible scattering distance of deicer from the highway and the impact range of deicer on soil quality in terms of plant growth. Among the major elements (Ca²⁺, Cl^- and Na⁺) of deicer, Ca²⁺and Cl^- are usually applied as fertilizer to soil. Therefore both elements (Ca²⁺and Cl^-) were not appropriate for a tracer of deicer at the agricultural area. In this study, SAR (sodium adsorption ratio) of soil was proposed as an alternative tracer to confirm the distribution of the deicer around the highway areas. Because deicer is the main anthropogenic source of Na⁺ around the highway areas and does harm to the physical properties of soil and plant growth through the destruction of soil aggregate, SAR would be an recommendable tracer to access the distribution of deicer as well as adverse effect on soil quality at highway areas. The influence range of deicer based on SAR of soil was estimated to be less than 20 m distance from the highway even though the possible flying distance of deicer was found to be more than 100 m from the highway. However the deicer seriously deposited within 10 m from the highway.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.270-273
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• 2007

In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.455-464
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• 2007

Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.33-42
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. MRFs have been used to model spatially correlated and signal-dependent phenomena for SAR speckled images. The MRF is incorporated into digital image analysis by viewing pixel types as slates of molecules in a lattice-like physical system defined on a GRF Because of the MRF-SRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular interactions. The proposed Point-Jacobian Iterative MAP estimation method was first evaluated using simulation data generated by the Monte Carlo method. The methodology was then applied to data acquired by the ESA's ERS satellite on Nonsan area of Korean Peninsula. In the extensive experiments of this study, The proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.