• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.649-658
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• 2006

Recently, Software Development was applied to new-approach methods as a various form : client-server system and web-programing, object-orient concept, distributed development with a network environments. On the other hand, it be concerned about the distributed development technology and increasing of object-oriented methodology. These technology is spread out the software quality and improve of software production, reduction of the software develop working. Futures, we considered about the distributed software development technique with a many workstation. In this paper, we discussed optimal release problem based on a stochastic differential equation model for the distributed Software development environments. In the past, the software reliability applied to quality a rough guess with a software development process and approach by the estimation of reliability for a test progress. But, in this paper, we decided to optimal release times two method: first, SRGM with an error counting model in fault detection phase by NHPP. Second, fault detection is change of continuous random variable by SDE(stochastic differential equation). Here, we decide to optimal release time as a minimum cost form the detected failure data and debugging fault data during the system test phase and operational phase. Especially, we discussed to limitation of reliability considering of total software cost probability distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.103-103
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• 2012

본 연구에서는 시험포장($1276.6m^2$)에서의 지표피복 BMPs (Best Management Practices) 시나리오를 적용하여 얻은 평균 유출저감율을 HSPF 모델에 적용하여 유역차원에서의 비점원오염 저감효과를 평가하고자 한다. 본 연구에서는 별미천 유역($1.21km^2$)을 대상으로 모형의 적용을 위한 입력자료로 기상자료와 지형자료를 구축하였으며 기상자료로 수원, 양평, 이천 기상관측소 자료를 구축하였으며, 지형자료로 격자크기 2m의 DEM (Digital Elevation Model)과 토지이용도는 2006년 5월 1일 QuickBird 영상을 제공받아 기존 환경부, 건교부, USGS의 토지피복분류체계 및 현장조사를 통하여 QuickBird 영상으로부터 추출 가능한 정밀농업정보에 대한 항목을 결정하였으며, 정사보정된 QuickBird 영상을 스크린 디지타이징 기법(On-Screen Digitizing Method)을 이용하여 총 21개 토지이용항목의 정밀토지이용도를 구축하였다. 실제모니터링으로 측정된 자료를 바탕으로 수위-유량곡선 산정 및 오염부하곡선을 선정, 2011년 6월 8일부터 10월 31일 분석기간으로 HSPF 모델링을 실시하였으며 모의결과 월별 통계에 따른 적용성 분석으로 RMSE (Root Mean Square Error) 는 1.15 ~ 1.76(mm/day), $R^2$는 0.62 ~ 0.78, Nash-Sutcliffe model efficiency (NSE)는 0.62 ~ 0.76로 모의치는 실측치와 유의성이 있는 것으로 분석되었다. 또한, Sediment, T-N, T-P의 $R^2$는 각각 0.72, 0.62, 0.63으로 상관성을 보이는 것으로 분석되었다. 시험포장으로부터 얻어진 event별 볏짚을 이용한 지표피복시나리오적용 후 밭에서의 평균 유출 약 10 % 유출율 감소 조건과 실제 평균 비점원오염 저감효과 89.7 % ~ 99.4 %의 결과로부터 지표피복효과의 침투효과를 HSPF 모델로 적용하기 위해 침투량(INFILT)를 조절하여 평균유출 약 10 %가 감소되는 16.0 mm/hr 값을 선정하였다. 그 결과, Sediment. T-N, T-P의 평균 저감율은 각각 87.2 %, 28.5 %, 85.1 %로 나타났으며 이는 시험포장에서의 실제 평균 비점오염 저감효과 89.7 % ~ 99.4 %에 근접함을 알 수 있었다. 이 결과로부터 침투량 조절에 따른 지표피복(침투짚단)효과는 Sediment, T-P에서 저감효율이 80 % 이상으로 높았지만 T-N은 약 30 %로 낮은 저감율을 보임으로써 저감효과가 크지 않음을 나타냈다.

• Land and Housing Review
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• v.12 no.2
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• pp.109-120
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• 2021

Global warming due to increased carbon dioxide is perceived as one of the factors threatening the future. Efforts are being made to reduce carbon dioxide emissions in each industry around the world. In particular, environmental loads and impacts during the life cycle of SOC structures and buildings have been quantitatively assessed through a quantitative method called Life Cycle Assessment (LCA). However, the construction sector has gone through difficulty in quantitative assessment for several reasons: 1) LCI DB is not fully established; 2) the life cycle is very long; 3) the building structures are unique. Therefore, it takes enormous effort and time to carry out LCA. Rather than estimating carbon emissions with accuracy, this study aims to present a simplified estimation model that allows owners or designers to easily estimate carbon dioxide emissions with little effort, given that rapid and rough decisions regarding environmental load reduction are to be made. This study performs the LCA using data from 25 road construction projects across the country, followed by multiple regression analyses to derive a simplified carbon estimation model (SLCA). The study also carries out a comparative analysis with values estimated by performing a typical LCA. The comparison analysis shows an error rate of less than 5% for 16 road projects.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.425-433
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• 2019

In this paper, the RCS analysis of the 10m unmanned surface vehicles was performed, and the factors of RCS increase were analyzed. Modeling techniques by transforming a geometric shape can reduce the RCS area, which can be used to develop stealth unmanned surface vehicles. In order to reduce the RCS, the existing Top Mast part was moved 1m to the tail part, the 5 degree tilt angle was moved below 0.5 m, and additional guided walls were installed to minimize the influence on the center and surrounding corner reflecting structures. As a result of comparing and analyzing the RCS analysis value with the existing model, it can be seen that the reduced countermeasure model is -3.79 dB lower than the existing model for all elevations. In particular, it can be seen that the strong scattering phenomenon is substantially removed in the region except the sacrificial angle region. In addition, it can be seen that in the case of -5m to 2m where the guide wall is added, the reflected signal is improved up to 20 to 40 dB or more, so that it does not appear on the 2D ISAR image. RCS analysis of unmanned surface vehicles explained the process of analyzing and identifying problem location through distance profile analysis and ISAR image analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.2
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• pp.122-133
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• 2021

Cultivar parameter calibration can be affected by the reliability of the input data to a crop growth model. In South Korea, two sets of weather stations, which are included in the automated synoptic observing system (ASOS) or the automatic weather system (AWS), are available for preparation of the weather input data. The objectives of this study were to estimate the cultivar parameter using those sets of weather data and to compare the uncertainty of these parameters. The cultivar parameters of CERES-Rice model for Shindongjin cultivar was calibrated using the weather data measured at the weather stations included in either ASO S or AWS. The observation data of crop growth and management at the experiment farms were retrieved from the report of new cultivar development and research published by Rural Development Administration. The weather stations were chosen to be the nearest neighbor to the experiment farms where crop data were collected. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to calibrate the cultivar parameters for 100 times, which resulted in the distribution of parameter values. O n average, the errors of the heading date decreased by one day when the weather input data were obtained from the weather stations included in AWS compared with ASO S. In particular, reduction of the estimation error was observed even when the distance between the experiment farm and the ASOS stations was about 15 km. These results suggest that the use of the AWS stations would improve the reliability and applicability of the crop growth models for decision support as well as parameter calibration.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.188-195
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• 1999

The fMRI signals are composed of many various signals. It is very difficult to find the accurate parameter for the model of fMRI signal containing only neural activity, though we may estimating the signal patterns by the modeling of several signal components. Besides the nose by the physiologic motion, the motion of object and noise of MR instruments make it more difficult to analyze signals of fMRI. Therefore, it is not easy to select an accurate reference data that can accurately reflect neural activity, and the method of an analysis of various signal patterns containing the information of neural activity is an issue of the post-processing methods for fMRI. In the present study, fMRI data was analyzed with the Independent Component Analysis(ICA) method that doesn't need a priori-knowledge or reference data. ICA can be more effective over the analytic method using cross-correlation analysis and can separate the signal patterns of the signals with delayed response or motion related components. The Principal component Analysis (PCA) threshold, wavelet spatial filtering and analysis of a part of whole images can be used for the reduction of the freedom of data before ICA analysis, and these preceding analyses may be useful for a more effective analysis. As a result, ICA method will be effective for the degree of freedom of the data.

• Journal of Plant Biotechnology
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• v.40 no.1
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• pp.37-42
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• 2013

Rice is one of the most important cereal crops as a model plant for functional genomics of monocotyledons and usually transformed using Agrobacterium tumefaciens. However, the transformation's process using previous method is still time consuming and uneconomical, low efficiency. In this study, we established a new method by modifying the general Agrobacterium protocol especially in the infection and co-cultivation, Agrobacterium elimination, infected calli's selection steps using liquid media. We directly inoculated Agrobacterium containing a ZjLsL gene under the control of constitutive promoter into the 1- to 3-week-old rice calli derived from mature seeds. After 3 days of co-cultivation, the infected calli were transferred onto liquid media of Agrobacterium elimination and calli's selection for 3 days. The calli were transferred to calli's growth solid media for 14 days and then the calli transferred to shoot induction and root induction media. Putative transformants were initially selected on the medium containing phosphinothricin, and the PAT protein verified by PAT strip test. This method in this study would lead to reduction of substantial labor and time to generate transgenic plants.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1215-1225
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• 2021

Although Artificial Intelligence (AI) techniques have shown impressive performance in various fields, they are vulnerable to adversarial examples which induce misclassification by adding human-imperceptible perturbations to the input. Previous studies to defend the adversarial examples can be classified into three categories: (1) model retraining methods; (2) input transformation methods; and (3) adversarial examples detection methods. However, even though the defense methods against adversarial examples have constantly been proposed, there is no research to classify the type of adversarial attack. In this paper, we proposed an adversarial attack family classification method based on dimensionality reduction and clustering. Specifically, after extracting adversarial perturbation from adversarial example, we performed Linear Discriminant Analysis (LDA) to reduce the dimensionality of adversarial perturbation and performed K-means algorithm to classify the type of adversarial attack family. From the experimental results using MNIST dataset and CIFAR-10 dataset, we show that the proposed method can efficiently classify five tyeps of adversarial attack(FGSM, BIM, PGD, DeepFool, C&W). We also show that the proposed method provides good classification performance even in a situation where the legitimate input to the adversarial example is unknown.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.5
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• pp.160-168
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• 2012

This study generated regression models to estimate the carbon storage and uptake from the urban deciduous landscape trees through a direct harvesting method, and established essential information to quantify carbon reduction from urban greenspace. Tree species for the study included Acer palmatum, Zelkova serrata, Prunus yedoensis, and Ginkgo biloba, which are usually planted as urban landscape trees. Tree individuals for each species were sampled reflecting various diameter sizes at a given interval. The study measured biomass for each part including the roots of sample trees to compute the total carbon storage per tree. Annual carbon uptake per tree was quantified by analyzing radial growth rates of stem samples at breast height. The study then derived a regression model easily applicable in estimating carbon storage and uptake per tree for the 4 species by using diameter at breast height(dbh) as an independent variable. All the regression models showed high fitness with $r^2$ values of 0.94~0.99. Carbon storage and uptake per tree and their differences between diameter classes increased as the diameter sizes got larger. The carbon storage and uptake tended to be greatest with Zelkova serrata in the same diameter sizes, followed by Prunus yedoensis and Ginkgo biloba in order. A Zelkova serrata tree with 15cm in dbh stored about 54kg of carbon and annually sequestered 7 kg, based on a regression model for the species. The study has broken new grounds to overcome limitations of the past studies which substituted, due to a difficulty in direct cutting and root digging of urban landscape trees, coefficients from the forest trees such as biomass expansion factors, ratios of below ground/above ground biomass, and diameter growth rates. Study results can be useful as a tool or skill to evaluate carbon reduction by landscape trees in urban greenspace projects of the government.

• Herbal Formula Science
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• v.20 no.1
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• pp.25-40
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• 2012

The purpose of this study explain the experimental effects of Guizhishaoyaozhimu-Tang (桂枝芍藥知母湯) that have clinical efficacy in rheumatoid Arthritis. Materials of present study were Guizhishaoyaozhimu-Tang freeze dried powder (GSZT), Sprague-dawley rats (300 g or so, male), various kinds of needing experimental studis. In order to study the therapeutic effects of GSZT, this Prescription (GSZT 500 mg/kg, 1,000 mg/kg) were administered per oral to the rats with the arthritis induced by Freund's complete adjuvant ($0.2m{\ell}/kg$), several experimental items were measured and compared each other ; that is body weight, rate of edema, analgesic effect by hot plate method, WBC, total protein, TNF-${\alpha}$, IL-10 and expression and localization of H&E, COX-2 staining in synovial tissues from rat with rheumatoid arthritis by immunohistochemical staining using polyclonal COX-2 antibodies. Rats were divided into four groups. Normal group was not treated with Freund's complete adjuvant and treated with DDW 1.0 $m{\ell}$, Control group was treated with Freund's complete adjuvant 0.2 $m{\ell}/kg$ and DDW 1.0 $m{\ell}$, Sample A group was treated with Freund's complete adjuvant 0.2 $m{\ell}/kg$ and GSZT (500 $mg/m{\ell}$) $1.0m{\ell}$, Sample B group was treated with Freund's complete adjuvant 0.2 $m{\ell}/kg$ and GSZT (1,000 $mg/m{\ell}$) 1.0 $m{\ell}$. 0 was day that did not start experiment, 14 was day that confirmed rheumatism induced by Freund's complete adjuvant, 28 was day that completed experiment. The following results were obtained in this study ; Sample A group was increased in body weight, escape time and paw licking time statistical significance compared with Control group, and were decreased in edema, WBC, total protein, TNF-${\alpha}$ with statistical significance compared with Control group. Sample B group was increased in escape time with statistical significance compared with Control group, and were decreased in edema, WBC, total protein with statistical significance compared with Control group. Sample A and Sample B groups were increased in IL-10 compared with Control group, and Sample B group was decreased in TNF-${\alpha}$ compared with Control group. And, Control, Sample A and Sample B groups were showed considerable reduction of positive expression in comparison to Normal group. Especially, Sample B group was most significantly reduction of positive expression than the other groups. From above results, I suggest that GuizhiShaoyaoZhimu-Tang can be used for curing rheumatoid arthritis.