• Journal of the Korean Geophysical Society
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• v.6 no.3
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• pp.155-164
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• 2003

The validity and efficiency of the roll-along technique widely used in 2-D electrical resistivity survey are analyzed in case of the dipole-dipole and the Wenner-Schlumberger arrays by numerical modelling. The shallow anomalous resistivity bodies are successfully inverted both in the dipole-dipole and in the Wenner-Schlumberger arrays because the shallow data of pseudosection are not omitted by the roll-along technique. However, the deep anomalous resistivity bodies can not be well resolved due to the skip of observed data which is more significant in the Wenner-Schlumberger array having relatively poor horizontal coverage of obtaining data. Carrying out electrical survey adopting the dipole-dipole array, the skip of data is insignificant because it is unfeasible to expand the electrodes to the maximum electrode separation coefficient($n_max$) owing to low S/N ratio. In case of the Wenner-Schlumberger array, however, because it is generally feasible to expand the electrodes $n_max$ to the owing to high S/N ratio, it is highly possible that skip of data from the roll-along technique causes significant distortion of inversion results. Therefore, adopting the Wenner-Schlumberger array having deeper median depth(Edwards, 1977) than do the dipole-dipole array on condition of the same unit electrode spacing( ($a$) ) and $n_max$, it is recommended to determine $a$ based on not $n_max$but $n_prob$free from the skip of observing data and forward electrodes with keeping overlap interval 3/4 of the survey line length in order to reduce the distortion of resistivity structure and perform resistivity survey efficiently. These results are confirmed by numerical modelling.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1809-1815
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• 2019

Objective: Copy number variations (CNVs) are a major source of genetic diversity complementary to single nucleotide polymorphism (SNP) in animals. The aim of the study was to perform a comprehensive genomic analysis of CNVs based on high density whole-genome SNP markers in Chinese Dongxiang spotted pigs. Methods: We used customized Affymetrix Axiom Pig1.4M array plates containing 1.4 million SNPs and the PennCNV algorithm to identify porcine CNVs on autosomes in Chinese Dongxiang spotted pigs. Then, the next generation sequence data was used to confirm the detected CNVs. Next, functional analysis was performed for gene contents in copy number variation regions (CNVRs). In addition, we compared the identified CNVRs with those reported ones and quantitative trait loci (QTL) in the pig QTL database. Results: We identified 871 putative CNVs belonging to 2,221 CNVRs on 17 autosomes. We further discarded CNVRs that were detected only in one individual, leaving us 166 CNVRs in total. The 166 CNVRs ranged from 2.89 kb to 617.53 kb with a mean value of 93.65 kb and a genome coverage of 15.55 Mb, corresponding to 0.58% of the pig genome. A total of 119 (71.69%) of the identified CNVRs were confirmed by next generation sequence data. Moreover, functional annotation showed that these CNVRs are involved in a variety of molecular functions. More than half (56.63%) of the CNVRs (n = 94) have been reported in previous studies, while 72 CNVRs are reported for the first time. In addition, 162 (97.59%) CNVRs were found to overlap with 2,765 previously reported QTLs affecting 378 phenotypic traits. Conclusion: The findings improve the catalog of pig CNVs and provide insights and novel molecular markers for further genetic analyses of Chinese indigenous pigs.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.69-77
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• 2012

Surface insolation is one of the major indicators for climate research over the Earth system. For the climate research, long-term data and wide range of spatial coverage from the data observed by two or more of satellites of the same orbit are needed. It is important to improve the continuity and consistency of the derived products, such as surface insolation, from different satellites. In this study, surface insolations based on Geostationary Operational Environmental Satellite (GOES-9) and Multi-functional Transport Satellites (MTSAT-1R) were compared during overlap period using physical model of insolation to find ways to improve the consistency and continuity between two satellites through comparison of each channel data and ground observation data. The thermal infrared brightness temperature of two satellites show a relatively good agreement between two satellites : rootmean square error (RMSE)=5.595 Kelvin; Bias=2.065 Kelvin. Whereas, visible channels shown a quite different values, but it distributed similar tendency. And the surface insolations from two satellites are different from the ground observation data. To improve the quality of retrieved insolations, we have reproduced surface insolation of each satellite through adjustment of the Cloud Factor, and the Cloud Factor for GOES-9 satellite is modified based on the analysis result of difference channel data. As a result, the insolations estimated from GOES-9 for cloudy conditions show good agreement with MTSAT-1R and ground observation : RMSE=$83.439W\;m^{-2}$ Bias=$27.296W\;m^{-2}$. The result improved accuracy confirms that the modification of Cloud Factor for GOES-9 can improve the continuity and consistency of the insolations derived from two or more satellites.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.1
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• pp.31-43
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• 2015

Purpose : Stereotactic body radiation therapy (SBRT) has proved its efficacy in several patient populations with primary and metastatic limited tumors. Because SBRT prescription is high dose level than Conventional radiation therapy. SBRT plan is necessary for effective Organ at risk (OAR) protection and sufficient Planning target volume (PTV) dose coverage. In particular, multi-target cases may result excessive doses to OAR and hot spot due to dose overlap. This study evaluate usefulness of Volumetric modulated arc therapy (VMAT) in dosimetric and technical considerations using Flattening filter free (FFF) beam. Materials and Methods : The treatment plans for five patients, being treated on TrueBeam STx(Varian$^{TM}$, USA) with VMAT using 10MV FFF beam and Standard conformal radiotherapy (CRT) using 15MV Flattening filter (FF) beam. PTV, liver, duodenum, bowel, spinal cord, esophagus, stomach dose were evaluated using the dose volume histogram(DVH). Conformity index(CI), homogeneity index(HI), Paddick's index(PCI) for the PTV was assessed. Total Monitor unit (MU) and beam on time was assessed. Results : Average value of CI, HI and PCI for PTV was $1.381{\pm}0.028$, $1.096{\pm}0.016$, $0.944{\pm}0.473$ in VMAT and $1.381{\pm}0.042$, $1.136{\pm}0.042$, $1.534{\pm}0.465$ in CRT respectively. OAR dose in CRT plans evaluated 1.8 times higher than VMAT. Total MU in VMAT evaluated 1.3 times increase than CRT. Average beam on time was 6.8 minute in VMAT and 21.3 minute in CRT. Conclusion : VMAT for SBRT in multi-target liver cancer using FFF beam is effective treatment techniqe in dosimetric and technical considerations. VMAT decrease intra-fraction error due to treatment time shortening using high dose rate of FFF beam.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.89-101
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• 2017

Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.