• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.396-404
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• 2021

It is important to verify that the contracted speed-power performance of a ship is satisfied in sea trials. International Organization for Standardization (ISO) has published the procedure for measuring and assessing ship speed during sea trials. The results obtained from actual sea conditions inevitably include various uncertainty factors. In this study, double run tests were performed on one container ship to analyze the uncertainty of sea trial on three maximum continuous rating conditions. The uncertainty factors and scale of uncertainty were examined based on the measured raw data during sea trial. The results indicate that the expanded uncertainty for ideal power performance is approximately ±1.4% at 95% confidence level (coverage factor k = 2) and most of the uncertainty factors were because of the shaft power measurement system.

• Journal of Veterinary Clinics
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• v.31 no.6
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• pp.469-476
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• 2014

The aims of this study were to explore the effects of conjugated linoleic acid (CLA) on reactive oxygen species (ROS) production in lipopolysaccharide (LPS)-naïve and LPS-stimulated RAW 264.7 macrophages and to examine whether these effects affect the regulation of tumor necrosis factor-alpha (TNF-${\alpha}$) production, and nuclear factor-kappa B (NF-${\kappa}B$) and peroxisome proliferator-activated receptor gamma ($PPAR{\gamma}$) activation. Trans-10, cis-12(t10c12)-CLA increased the production of ROS, as well as TNF-${\alpha}$ in LPS-naïve RAW 264.7 cells. The CLA-induced TNF-${\alpha}$ production was suppressed by treatment of diphenyleneiodonium chloride (DPI), a NADPH oxidase inhibitor. In addition, CLA enhanced the activities of NF-${\kappa}B$ and $PPAR{\gamma}$ in LPS-naïve RAW 264.7 cells, and this effect was abolished with DPI treatment. LPS treatment increased ROS production, whereas CLA reduced LPS-induced ROS production. LPS increased both TNF-${\alpha}$ production and NF-${\kappa}B$ activity, whereas t10c12-CLA reduced TNF-${\alpha}$ production and NF-${\kappa}B$ activity in LPS-stimulated RAW 264.7 cells. DPI treatment suppressed LPS-induced ROS production and NF-${\kappa}B$ activity. Moreover, DPI enhanced the inhibitory effects of t10c12-CLA on TNF-${\alpha}$ production and NF-${\kappa}B$ activation in LPS-stimulated RAW 264.7 cells. However, neither t10c12-CLA nor DPI affected $PPAR{\gamma}$ activity in LPS-stimulated RAW 264.7 cells. Taken together, these data indicate that t10c12-CLA induces TNF-${\alpha}$ production by increasing ROS production in LPS-naïve RAW 264.7 cells, which is mediated by the enhancement of NF-${\kappa}B$ activity via $PPAR{\gamma}$ activation. By contrast, t10c12-CLA suppresses TNF-${\alpha}$ production by inhibiting ROS production and NF-${\kappa}B$ activation via a $PPAR{\gamma}$-independent pathway in LPS-stimulated RAW 264.7 cells. These results suggest that t10c12-CLA can modulate TNF-${\alpha}$ production and NF-${\kappa}B$ activation through formation of ROS in RAW 264.7 macrophages.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.11-20
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• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.E2
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• pp.66-73
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• 2007

The introduction of tracer gas techniques to ventilation studies in indoor environments provides valuable information that used to be unattainable from conventional testing environments. Data acquisition systems (DASs) containing analogue-to-digital (A/D) converters are usually used to function the key role that records signals to storage in digital format. In the testing process, there exist a number of components in the measuring equipment which may produce system-based inference to the monitored results. These unwanted fluctuations may cause significant error in data analysis, especially when non-linear algorithms are involved. In this study, a pre-processor is developed and applied to separate the unwanted fluctuations (noise or interference) in raw measurements and to reduce the uncertainty in the measurement. Moving average, notch filter, FIR (Finite Impulse Response) filters, and IIR (Infinite Impulse Response) filters are designed and applied to collect the desired information from the raw measurements. Tracer gas concentrations are monitored during leakage and ventilation tests in the model test room. The signal analysis functions are introduced to carry out the digital signal processing (DSP) work. Overall the FIR filters process the $CO_2$ measurement properly for ventilation rate and mean age of air calculations. It is found that, the Kaiser filter was the most applicable digital filter for pre-processing the tracer gas measurements. Although the IIR filters help to reduce the random noise in the data, they cause considerable changes to the filtered data, which is not desirable.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.1
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• pp.17-31
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• 2004

The subway play an important part in serious traffic problems. However, because subway system is a closed environment, many serious air pollution problems occurred in subway stations and injured passenger's health. Therefor, it is a necessary to identify sources and to estimate pollutant sources in order to protect passenger's health and to keep clean subway environment. The purpose of this study was to analyze a air quality in the subway stations and to apply a new receptor methodology for quantitatively estimate of PM10 sources. In this study, the size distributions of particulate matters has been measured by using Aerosizer LD (U.S.A., API, Inc.). It's real time measurement capability of time-of-flight technique offers a significant advantage of user convenience and air pollution management. Also, the mass concentrations of PM 10 has been measured by using mini-vol portable sampler (U.S.A., Airmetrics Co.). The sampling performed in Seoul subway stations during the period of February 2000 and April 2000. The number distribution data used in this study consisted of 26 raw data sets in the Jongno-sam-ga station. Correlation Analysis can be used in subway stations for source separation and identification. Then, number contribution from each source is determined by the particle number balance (PNB). The mass concentration data used in this study consisted of 31 raw data in the 8 different stations. The mass contributions of PM10 sources in the concourse by using PMF/CMB model.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.11
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• pp.71-81
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• 1999

In this paper, digital holographic data storage system is implemented to record and retrieve the color images using new direct access method and binary image processing. As a result of applying image processing via a proposed direct access method, we can reduce the number of data page than binary image processing using raw file and replay color image of resolution of $128{\times}80{\times}256$ (6.6KB). Also it is showed that the input data can be transformed into digital holograms regardless of any kinds of file such as character data, moving picture. etc.

• Particle and aerosol research
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• v.7 no.1
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• pp.31-44
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• 2011

The hourly volatile organic compounds(VOCs) concentrations between 2005 and 2008 at Bulgwang photochemical assessment monitoring station were investigated to establish a method for quality assurance and quality control(QA/QC) procedure. Systematic error, erratic error, and random error, which was manifested by outlier and highly fluctuated data, were checked and removed. About 17.3% of the raw data were excluded according to the proposed QA/QC procedure. After QA/QC, relative standard deviation for representing 15 species concentrations decreased from 94.7-548.0% to 63.4-125.8%, implying the QA/QC procedure is proper. For further evaluation about the adequacy of QA/QC procedure, principal components analysis(PCA) was carried out. When the data after QA/QC procedure was used for PCA, the extracted principal components were different from the result from the raw data and could logically explain the major emission sources(gasoline vapor, vehicle exhaust, and solvent usage). The QA/QC procedure based on the concept of errors is inferred to proper to be applied on VOCs. However, an additional QA/QC step considering the relationship between species in the atmosphere needs to be further considered.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.241-243
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1㎝, ${\pm}$24.7㎝, ${\pm}$35.9㎝, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.600-608
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• 2020

Machine learning constructs an objective function from learning data, and predicts the result of the data generated by checking the objective function through test data. In machine learning, input data is subjected to a normalisation process through a preprocessing. In the case of numerical data, normalization is standardized by using the average and standard deviation of the input data. In the case of nominal data, which is non-numerical data, it is converted into a one-hot code form. However, this preprocessing alone cannot solve the problem. For this reason, we propose a method that uses ontology to normalize input data in this paper. The test data for this uses the received signal strength indicator (RSSI) value of the Wi-Fi device collected from the mobile device. These data are solved through ontology because they includes noise and heterogeneous problems.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.3-23
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• 1997

Internet can provide raw multimedia information; organization of information is the key challenge for the future. Keep the person in the loop, but provide tools to separate wheat from chaff.(omitted)