• Progress in Medical Physics
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• v.24 no.2
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• pp.99-107
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• 2013

The surgical resection was occurred mainly in liver metastasis before the development of radiation therapy techniques. Recently, Radiation therapy is increased gradually due to the development of radiation dose delivery techniques. 18F-FDG PET image showed better sensitivity and specificity in liver metastasis detection. This image modality is important in the radiation treatment with planning CT for tumor delineation. In this study, we applied automatic image segmentation methods on PET image of liver metastasis and examined the impact of image factors on these methods. We selected the patients who were received the radiation therapy and 18F-FDG PET/CT in Korea Cancer Center Hospital from 2009 to 2012. Then, three kinds of image segmentation methods had been applied; The relative threshold method, the Gradient method and the region growing method. Based on these results, we performed statistical analysis in two directions. 1. comparison of GTV and image segmentation results. 2. performance of regression analysis for relation between image factor affecting image segmentation techniques. The mean volume of GTV was $60.9{\pm}65.9$ cc and the $GTV_{40%}$ was $22.43{\pm}35.27$ cc, and the $GTV_{50%}$ was $10.11{\pm}17.92$ cc, the $GTV_{RG}$ was $32.89{\pm}36.8$4 cc, the $GTV_{GD}$ was $30.34{\pm}35.77$ cc, respectively. The most similar segmentation method with the GTV result was the region growing method. For the quantitative analysis of the image factors which influenced on the region growing method, we used the standardized coefficient ${\beta}$, factors affecting the region growing method show GTV, $TumorSUV_{MAX/MIN}$, $SUV_{max}$, TBR in order. The result of the region growing (automatic segmentation) method showed the most similar result with the CT based GTV and the region growing method was affected by image factors. If we define the tumor volume by the auto image segmentation method which reflect the PET image parameters, more accurate and consistent tumor contouring can be done. And we can irradiate the optimized radiation dose to the cancer, ultimately.

• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.280-290
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• 2002

Three-dimensional (3-D) electromagnetic (EM) modeling algorithm has been developed using finite element method (FEM) to acquire more efficient interpretation techniques of EM data. When FEM based on nodal elements is applied to EM problem, spurious solutions, so called 'vector parasite', are occurred due to the discontinuity of normal electric fields and may lead the completely erroneous results. Among the methods curing the spurious problem, this study adopts vector element of which basis function has the amplitude and direction. To reduce computational cost and required core memory, complex bi-conjugate gradient (CBCG) method is applied to solving complex symmetric matrix of FEM and point Jacobi method is used to accelerate convergence rate. To verify the developed 3-D EM modeling algorithm, its electric and magnetic field for a layered-earth model are compared with those of layered-earth solution. As we expected, the vector based FEM developed in this study does not cause ny vector parasite problem, while conventional nodal based FEM causes lots of errors due to the discontinuity of field variables. For testing the applicability to high frequencies 100 MHz is used as an operating frequency for the layer structure. Modeled fields calculated from developed code are also well matched with the layered-earth ones for a model with dielectric anomaly as well as conductive anomaly. In a vertical electric dipole source case, however, the discontinuity of field variables causes the conventional nodal based FEM to include a lot of errors due to the vector parasite. Even for the case, the vector based FEM gave almost the same results as the layered-earth solution. The magnetic fields induced by a dielectric anomaly at high frequencies show unique behaviors different from those by a conductive anomaly. Since our 3-D EM modeling code can reflect the effect from a dielectric anomaly as well as a conductive anomaly, it may be a groundwork not only to apply high frequency EM method to the field survey but also to analyze the fold data obtained by high frequency EM method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.1-8
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• 2005

In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.385-396
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• 1999

In the process of structural design for large-scale structures with several thousands of degrees of freedom, a plethora of structural calculations with large amount of data storage are required to obtain the forces and displacements of the members. However, current computational environment with single microprocessor such as a personal computer or a workstation is not capable of generating a high-level of efficiency in structural analysis and design process for large-scale structures. In this paper, a high-performance parallel computing system interconnected by a network of personal computers is proposed for an efficient structural analysis. Two distributed structural analysis algorithms are developed in the form of distributed or parallel preconditioned conjugate gradient (DPCG) method. To enhance the performance of the developed distributed structural analysis algorithms, the number of communications and the size of data to be communicated are minimized. These algorithms are applied to the structural analyses of three large space structures as well as a 144-story tube-in-tube framed structure.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• Journal of Soil and Groundwater Environment
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• v.24 no.6
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• pp.16-25
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• 2019

Anthropogenic polycyclic aromatic hydrocarbons (PAHs) are formed by the incomplete combustion of fuels and industrial waste. PAHs can be widely exposed to the environment (water, soil and groundwater). PAHs are potentially toxic, mutagenic and/or carcinogenic. Fundamental studies such as biota uptake (e.g., earthworm and plant) of PAHs are highly needed. It is necessary to develop alternative ways to evaluate bioavailability of PAHs instead of using living organisms because it is time-consuming, difficult to apply in the field, and also exaction method is tedious and time-consuming. In this study, sorption behaviors of phenanthrene were evaluated to predict the fate of PAHs in soils. Moreover, bioaccumulation of PAHs in an artificially contaminated soil was evaluated using pea plant (Pisum sativum) as a bioindicator. A novel passive sampler, organic-diffusive gradient in thin-film (o-DGT) for PAHs was newly synthesized, tested as a biomimic surrogate and compared with plant accumulation. Sorption partitioning coefficient (K_P) and sorption capacity (K_F) were in the order of natural soil > loess corresponding to the increase in organic carbon content (f_oc). Biota-to-soil accumulation factor (BSAF) and DGT-to-soil accumulation factor (DSAF) were evaluated. o-DGT uptake was linearly correlated with pea plant uptake of phenanthrene in contaminated soil (R²=0.863). The Tenax TA based o-DGT as a biomimic surrogate can be used for the prediction of pea plant uptake of phenanthrene in contaminated soil.

• The Journal of Engineering Geology
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• v.16 no.1 s.47
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• pp.85-96
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• 2006

This study was conducted to suggest a method to determine weighting values of each parameter of the RMR system considered with geologic characteristics of a study area. This study reviewed the weighting values of the RMR system for the Cretaceous sedimentary rocks distributed in Ulsan area. Based on the data of field survey at the study area, a multiple regression analysis was used to set up an optimal weighting values of the RMR parameters. For the multiple regression analysis, each parameter of the RMR and the slope gradient were regarded as the independent variable and the dependent variable, respectively. The analysis result suggested a modified weighting values of the RMR parameters as follows; 30 for the intact strength of rock; 18 for RQD; 8 for spacing of discontinuities; 32 for the condition of discontinuities; and 12 for ground water.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.39-49
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• 2000

In this paper, we propose an optimizing feature extraction method for multiclass problems assuming normal distributions. Initially, We start with an arbitrary feature vector Assuming that the feature vector is used for classification, we compute the classification error Then we move the feature vector slightly in the direction so that classification error decreases most rapidly This can be done by taking gradient We propose two search methods, sequential search and global search In the sequential search, an additional feature vector is selected so that it provides the best accuracy along with the already chosen feature vectors In the global search, we are not constrained to use the chosen feature vectors Experimental results show that the proposed algorithm provides a favorable performance.

• IMMUNE NETWORK
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• v.13 no.4
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• pp.133-140
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• 2013

Since the discovery of the immunomodulation property of mesenchymal stem cells (MSCs) about a decade ago, it has been extensively investigated whether MSCs can be used for the treatment of immune-related diseases, such as graft versus-host disease (GvHD). However, how to evaluate the efficacy of human MSCs for the clinical trial is still unclear. We used an MHC-mismatched model of GvHD (B6 into BALB/c). Surprisingly, the administration of the human MSCs (hMSCs) could reduce the GvHD-related mortality of the mouse recipients and xenogeneically inhibit mouse T-cell proliferation and $IFN-{\gamma}$ production in vitro. We recently established a new protocol for the isolation of a homogeneous population of MSCs called subfractionation culturing methods (SCM), and established a library of clonal MSC lines. Therefore, we also investigated whether MSCs isolated by the conventional gradient centrifugation method (GCM) and SCM show different efficacy in vivo. Intriguingly, clonal hMSCs (hcMSCs) isolated by SCM showed better efficacy than hMSCs isolated by GCM. Based on these results, the MHC-mismatched model of GvHD may be useful for evaluating the efficacy of human MSCs before the clinical trial. The results of this study suggest that different MSC lines may show different efficacy in vivo and in vitro.

• The Journal of Engineering Geology
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• v.2 no.2
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• pp.113-130
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• 1992

Groundwater in crystalline basement is controlled primarily by tectonic fractures. It is evident that the delineation of the heavily faulted area and/or fractures deeply developped should be considerable value in deep-seated low enthalphy geothermal water. Electrical and electromagnetic methods have effectively been employed to map hydraulic faults and shear zones for groundwater exploration. In this study VLi; dipoledipole resistivity, controlled source audio~frequency magneto-telluric(CSAMT) and magnetic methods were applied in the Bomun resort area, adjacent to Kyongju city, southeastern part of Korea. The integrated geophysical tools employed in this experiment can be manifested themselves as: 1. Magnetic high for granite intrusions which is more favorable for geothermal gradient increase in depth. 2. VLF cross-over trends for mapping linear shallow conductive fractures and shear zones. 3. Dipole-dipole resistivity distributions for the deep-seated(less than 500m in depth) fractures and shear zones. The dipole-dipole resistivity field data were inverted to the true resistivity distribution with two-dimensional automatic inversion program based on the finite-difference method. 4. CSAMT provides an efficient way of delineating fractures and fault zones if the depth is greater than about 500m.