• Radiation Oncology Journal
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• v.27 no.3
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• pp.140-144
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• 2009

Purpose: This study was performed to retrospectively analyze patient survival by weighting according to the primary tumor oncotype in 160 patients with brain metastasis and who underwent whole brain radiotherapy. Materials and Methods: A total of 160 metastatic brain cancer patients who were treated with whole brain radiotherapy of 30 Gy between 2002 and 2008 were retrospectively analyzed. The primary tumor oncotype of 20 patients was breast cancer, and that of 103 patients was lung cancer. Except for 18 patients with leptomeningeal seeding, a total of 142 patients were analyzed according to the prognostic factors and the Recursive Partitioning Analysis (RPA) class. Weighted Partitioning Analysis (WPA), with the weighting being done according to the primary tumor oncotype, was performed and the results were correlated with survival and then compared with the RPA Class. Results: The median survival of the patients in RPA Class I (8 patients) was 20.0 months, that for Class II (76 patients) was 10.0 months and that for Class III (58 patients) was 3.0 months (p<0.003). The median survival of patients in WPA Class I (3 patients) was 36 months, that for the patients in Class II (9 patients) was 23.7 months, that for the patients in Class III (70 patients) was 10.9 months and that for the patients in Class IV (60 patients) was 8.6 months (p<0.001). The WPA Class might have more accuracy in assessing survival, and it may be superior to the RPA Class for assessing survival. Conclusion: A new prognostic index, the WPA Class, has more prognostic value than the RPA Class for the treatment of patients with metastatic brain cancer. This WPA Class may be useful to guide the appropriate treatment of metastatic brain lesions.

• Genomics & Informatics
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• v.14 no.4
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• pp.196-204
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• 2016

Many researchers have found that one of the most important characteristics of the structure of linkage disequilibrium is that the human genome can be divided into non-overlapping block partitions in which only a small number of haplotypes are observed. The location and distribution of haplotype blocks can be seen as a population property influenced by population genetic events such as selection, mutation, recombination and population structure. In this study, we investigate the effects of the density of markers relative to the full set of all polymorphisms in the region on the results of haplotype partitioning for five popular haplotype block partition methods: three methods in Haploview (confidence interval, four gamete test, and solid spine), MIG++ implemented in PLINK 1.9 and S-MIG++. We used several experimental datasets obtained by sampling subsets of single nucleotide polymorphism (SNP) markers of chromosome 22 region in the 1000 Genomes Project data and also the HapMap phase 3 data to compare the results of haplotype block partitions by five methods. With decreasing sampling ratio down to 20% of the original SNP markers, the total number of haplotype blocks decreases and the length of haplotype blocks increases for all algorithms. When we examined the marker-independence of the haplotype block locations constructed from the datasets of different density, the results using below 50% of the entire SNP markers were very different from the results using the entire SNP markers. We conclude that the haplotype block construction results should be used and interpreted carefully depending on the selection of markers and the purpose of the study.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.608-616
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• 2022

Power peaking factors (PPF) is an important parameter for safe and efficient reactor operation. There are several methods to calculate the PPF at TRIGA research reactors such as MCNP and TRIGLAV codes. However, these methods are time-consuming and required high specifications of a computer system. To overcome these limitations, artificial intelligence was introduced for parameter prediction. Previous studies applied the neural network method to predict the PPF, but the publications using the ANFIS method are not well developed yet. In this paper, the prediction of PPF using the ANFIS was conducted. Two input variables, control rod position, and neutron flux were collected while the PPF was calculated using TRIGLAV code as the data output. These input-output datasets were used for ANFIS model generation, training, and testing. In this study, four ANFIS model with two types of input space partitioning methods shows good predictive performances with R² values in the range of 96%-97%, reveals the strong relationship between the predicted and actual PPF values. The RMSE calculated also near zero. From this statistical analysis, it is proven that the ANFIS could predict the PPF accurately and can be used as an alternative method to develop a real-time monitoring system at TRIGA research reactors.

• Corrosion Science and Technology
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• v.18 no.6
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• pp.267-276
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• 2019

The purpose of this study was to examine the influence of conditions for quenching and/or tempering on the corrosion and hydrogen diffusion behavior of ultra-strong automotive steel in terms of the localized plastic strain related to the dislocation density, and the precipitation of iron carbide. In this study, a range of analytical and experimental methods were deployed, such as field emission-scanning electron microscopy, electron back scatter diffraction, electrochemical permeation technique, slow-strain rate test (SSRT), and electrochemical polarization test. The results showed that the hydrogen diffusion parameters involving the diffusion kinetics and hydrogen solubility, obtained from the permeation experiment, could not be directly indicative of the resistance to hydrogen embrittlement (HE) occurring under the condition with low hydrogen concentration. The SSRT results showed that the partitioning process, leading to decrease in localized plastic strain and dislocation density in the sample, results in a high resistance to HE-induced by aqueous corrosion. Conversely, coarse iron carbide, precipitated during heat treatment, weakened the long-term corrosion resistance. This can also be a controlling factor for the development of ultra-strong steel with superior corrosion and HE resistance.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.965-976
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• 2020

We present in this work a segmentation method of E. coli bacterial images generated via phase contrast microscopy using a deep learning based hybrid feature generation. Unlike conventional machine learning methods that use the hand-crafted features, we adopt the denoising autoencoder in order to generate a precise and accurate representation of the pixels. We first construct a hybrid vector that combines original image, difference of Gaussians and image gradients. The created hybrid features are then given to a deep autoencoder that learns the pixels' internal dependencies and the cells' shape and boundary information. The latent representations learned by the autoencoder are used as the inputs of a softmax classification layer and the direct outputs from the classifier represent the coarse segmentation mask. Finally, the classifier's outputs are used as prior information for a graph partitioning based fine segmentation. We demonstrate that the proposed hybrid vector representation manages to preserve the global shape and boundary information of the cells, allowing to retrieve the majority of the cellular patterns without the need of any post-processing.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.4
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• pp.199-206
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• 2006

Real time vehicle dynamics models have been developed with the subsystem synthesis method for intelligent vehicle HILS system. Three different models for solving subsystem equations are compared in order to find out the best suitable model for HILS applications. The first model is based on the generalized coordinate partitioning technique, and the second one is on the approximate function approach, and the last one is on the constraint stabilization method. To investigate the theoretical efficiency of three proposed methods, arithmetic operators used in the formulations of three models are counted. Bump run simulations with half-sine bump have also carried out with three different models to measure the actual CPU time to validate theoretical investigation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.601-606
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• 1998

In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• Journal of Environmental Health Sciences
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• v.41 no.2
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• pp.116-125
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• 2015

Objective: This study was carried out to use pine needles as a passive air sampler (PAS) for atmospheric polychlorinared dibenzo-p-dioxins/furans (PCDD/Fs). Methods: PCDD/Fs concentrations in ambient air ($C_a$, $pg/m^3$) and deposited pine needles ($C_p$, pg/g dry) were analyzed simultaneously from June 1 to December 31. Air samples were taken using two low volume PUF active air samplers with an overall average air volume of approximately $1,200Sm^3$. Pine needles were collected the end of December near the air sampler. PCDD/Fs was analyzed by HRGC/HRMs. Results: A good correlation was shown ($R^2=0.6357$, p=0.0001) between $C_a$ and $C_p$, but a better correlation ($R^2=0.7372$, p<0.0001) existed between the logarithm of octanol-air partitioning coefficient ($LogK_{oa}$) and Log($C_p/C_a$). The average PCDD/Fs sampling rates from air to pine needles were 0.045($0.018-0.185m^3/day-g\;dry$). Conclusion: It was found that pine needles can be used as PAS for atmospheric PCDD/Fs, and they are especially suitable for long time PAS compared to PUF disk PAS.

• Journal of the Korea Computer Graphics Society
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• v.22 no.2
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• pp.20-26
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• 2016

This paper proposes an automatic hexahedral mesh generation method, in which internal medial surfaces are established to partition a region using the face-offsetting method. In order to test the usability of the suggested method, aspect ratios and Jacobians of the generated mesh for two models are evaluated and compared with ones from existing methods. It is verified that the proposed medial surface generation and partitioning scheme based on the face-offsetting method can be effectively used in the automatic hexahedral mesh generation procedure.

• Korean Institute of Interior Design Journal
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• no.13
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• pp.130-138
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• 1997

This study is to present the visual phenomenon of natural light in the interior space. The continuously changing natural light define the visual phenomenon of the architectural space. First, the objective of this study was finding the importance of the visual phenomena which were generated from correlating natural right with the interior space. And the second was to categorize the factors of the visual phenomenon which can be useful factors for modern interior design practice. As a result of this study, two visual phenomena were classified. First; territorial phenomenon: dividing, partitioning, and sectioning by natural light, Second; phenomena by the inflow methods of natural light; a) by direct inflow; transparency, expansion, and floating, b) by filtering fixtures; the architectural structure, color, and the transluscent material, c) by dramatic spacial present of natural light, d) by the sense of direction of naturel light; continuity, and transformatiov. Found and classified each factor is not presented by itself, rather compounded forms. Because of the limited analysis of modern buildings, these found visual factors can not represent all phenomena. But if we practice these finding factors to design present interior space, it is sure of being very valuable factors to re-introduce the overlooked natural light into interior space.