• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.163-171
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• 2009

Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.225-233
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• 2013

The accuracy of the automatic NMO velocity analysis, which is used for an effective and objective NMO velocity analysis, is highly affected by the velocity resolution of the velocity spectrum. In this study, we have developed an automatic NMO velocity algorithm, where the velocity spectra are created using high-resolution bootstrapped differential semblance (BDS), and the velocity analysis on CMP gathers is performed in parallel with MPI. We also compared the velocity models from the developed automatic NMO velocity algorithm with high-resolution BDS to those from BDS. To verify the developed automatic velocity analysis module we created synthetic seismic data from a velocity model including horizon layers. We confirmed that the developed automatic velocity analysis module estimated velocity more accurately. In addition, NMO velocity which yielded a CMP stacked section, where the coherency of the events were improved, was estimated when the developed module was applied to a marine field data set.

• The Korea Journal of Herbology
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• v.24 no.2
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• pp.49-56
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• 2009

Objectives : Inflammation is important event in the development of vascular diseases including hypertension, atherosclerosis, and restenosis. Bodusan (BDS) was a traditional Korean herbal medicine and widely used in treatment of gastrointestinal complaint and stomach ulcer. The aim of this study was to determine whether BDS and its components inhibit production of nitrite, PGE2 and proinflammatory cytokines in lipopolysaccharide (LPS)-treated RAW 264.7 macrophages. Methods : Cytotoxic activity of BDS and its components on RAW 264.7 cells was using 5-(3caroboxymcrophages. eth-oxyphenyj)-2H-tetra-zolium inner salt (MTS) assay. The nitric oxide (NO) production was measured by Griess reagent system. And proinflammatory cytokines were measured by ELISA kit. The levels of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expression were detected by western blot. Results : Our results indicated that BDS and its components significantly inhibited the LPS-induced NO and PGE2 production. Moreover. BDS and its components inhibited iNOS and COX-2 expression accompanied by an attenuation of TNF-${\alpha}$, IL-11${\beta}$, IL-6 and MCP-1 formation in macrophages. Conclusions: These results indicate that BDS and its components have potential as an anti-inflammatory agent.

• Journal of Korean Association for Spatial Structures
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• v.8 no.4
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• pp.22-27
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• 2008

• International Journal of Contents
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• v.2 no.1
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• pp.34-38
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• 2006

In this paper, an overview of anti-collision algorithm for RFID system of a standard EPC Class1 protocol is presented, and the binslotted dynamic search algorithm (BDS) based upon the slotted ALOHA and binary tree procedure is proposed and analyzed. Also, the performance is evaluated as comparing the BDS algorithm with the standard bin-slotted algorithm (BSA) through the simulation program. The performance of the proposed BDS algorithm is improved by dynamically identifying the collided-bit position and the collided bins stored in the stack of the reader. As the results, the number of request command that a reader send to tags in the reader s interrogation zone and the total recognition time are decreased to 59% as compared with BSA algorithm. Therefore, the tag identification performance is fairly improved by resolving a collision problem using the proposed BDS algorithm.

• Review of KIISC
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• v.5 no.2
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• pp.49-63
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• 1995

본 논문은 정보시스템 보안관리에 대한 개념적 모형을 INFORSEC 및 한국전산원이 제시한 모형을 중심으로 기술했으며 보안관리의 표준적인 분류체계를 근거로 BDSS의 위협. 자산, 취약성의 분류체계를 비교함으로써 위협, 자산, 취약성의 관련성을 탐색 하고자 했다. 특히 위협의 원천과 가해자 측면에서 BDSS와 CRAMM의 경우를 비교함으로써 분류체계의 장단점을 파악하고자 했다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.37-45
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• 2011

We studied noise influence on nonlinear chaotic system by using Logistic data series which is known as a typical nonlinear chaotic system. We regenerated Logistic data series by the method of adding noise according to noise level. And, we performed some analyses such as phase space reconstruction, correlation dimension, BDS statistics, and DVS Algorithms which are known as the methods of nonlinear deterministic or chaotic analysis. If we see the results of analysis, the characteristics of data series are gradually changed from nonlinear chaotic data series to random stochastic data series according to increasing noise level. We applied Low Pass Filter (LPF) and Kalman Filter techniques for the investigation of removing effect of the added noise to data series. Typical nonparametric method cannot distinguish nonlinear random series but the BDS statistic can distinguish the nonlinear randomness of the time series. Therefore this study used the BDS statistic which is well known as nonlinear statistical method for the investigation of randomness of time series for the effect of removing noise of data series. We found that Kalman filter is better method to remove the noise of chaotic data series even for high noise level.

• Particle and aerosol research
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• v.13 no.1
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• pp.25-31
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• 2017

This paper offer the characteristics for the detection and classification of biological and non-biological aerosol particles in the air by using laser-induced-fluorescence (LIF) based Bio-aerosol Detection System (BDS). The BDS is mainly consist of an optical chamber, in-outlet nozzle system, 405 nm diode laser, an avalanche photo detector (APD) for scattering signal and photomultiplier tubes (PMT) for fluorescence signals in two different wavelength range ; F1, 510-600 nm and F2, 435-470 nm. The detection characteristics, especially ratio of fluorescence signal intensity were examined using well-known components : polystylene latex (PSL), fluorescence PSL, $2{\mu}m$ of SiO2 micro sphere, dried yeast, NADH, ovalbumin, fungicide powder and standard dust. The results indicated that the 405 nm diode laser-based LIF instrument can be a useful bio-aerosol detection system for unexpected biological threaten alter in real-time to apply for dual-use technology in military and civilian fields.

• Journal of Distribution Science
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• v.17 no.4
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• pp.27-32
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• 2019

Purpose - The business model is a method of creating corporate value, in existing "classification of business model", limitations and redundancy phenomena are applied when a new type flows in, and as consumer's purchasing decision of consumer behavior 5 steps. The classification schemes can be used for more accurate data analysis by proposing a new mapping technique in the fourth industry. Research design, data, and methodology - It was far more classified on the business model (BMS by BDS), and so on. Designing the new horizons of logistics, marketing, methodology by reclassifying these existing data to new useful data with the old methods, in order to analyze the areas where the problem has been raised for the point that the existing methods are not suitable configured. This will be applicable to the system of quaternary industry from the perspective of the buyer. Results - The mapping results of the consumer purchase decision were as follows,the 1^st stage (interest) was 23.73%, 2^nd stages (publicity) 33.90%, 3^rd stages (sales) 13.56%, 4^th stages (decision) 11.86%, 5^th stages (repurchaser) 16.95%. This verified that "the business model can be classified through "BMS by BDS". Conclusions - This structural classification is the basis of logistics marketing in the 4th industry, and proposes a innovative and effective model of constructing theory.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.864-865
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• 2011

Battery Disconnecting System (BDS) is the important equipment in electric vehicle system. Therefore, most of electric vehicle companies, i.e. Hyundai Motors, Renault Motors, General Motors, want to have the reliability of 15 years - 150, 000 miles. Recently, reliability prediction through Siemens Norm SN 29500 is considered without testing. In this paper, we will introduce the standard and various input parameters. Also the case study will be shown for BDS. Prediction model is constructed by listing all the components of BDS. It calculates the $\pi$ factors for each components using the conversion equation in the standard and converts the reference failure rates to the expected operating failure rates. According to the result, the parts which will be improved are EV-Relays.