• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.393-407
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• 2012

This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multi-temporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of $3{\times}3$, $5{\times}5$, $7{\times}7$, and $9{\times}9$ pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of $7{\times}7$ produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of $9{\times}9$ produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.262-267
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• 2004

The unloading compliance method is the most commonly used method to evaluate the fracture resistance characteristics of a material. In dynamic loading condition, the direct current potential drop(DCPD) method has been used because the unloading compliance method can not be applied due to the discontinuity of loading. However, even in the dynamic test using DCPD method, there is a problem that the voltage drops sharply on the initiation of crack. For the reason metioned above, the normalization method was suggested on ASTM E 1820 which is revised recently, as a new method to evaluate the dynamic fracture resistance characteristic. The nomalization method can be used to obtain a fracture resistance curve directly from a load-load line displacement. In this study, we obtained two fracture resistance curves from static test of welding part of nuclear piping both by unloading compliance and nomalization method. The two curves were almost same each other, so the adaptability of the nomalization method has been proved. We conducted a dynamic fracture resistance test for the same material. The fracture resistance curve from the dynamic test was obtained by normalization method and compared to that of the static test result.

• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.291-296
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• 2016

The ideal chemical sensor must show the similar result under the same condition for accurate measurement of gases regardless of time. However, the actual responses of chemical sensors have been shown the lacks of repeatability and reproducibility because of the drift which has been caused by aging and pollution of the sensor and the environment change such as temperature and humidity. If the problems are not properly taken into considerations, the stability and reliability of the system using chemical sensors would be decreased. In this paper, we analyzed the sensor's drift and applied the three different compensation methods(DWT( Discrete Wavelets Transform), Baseline Manipulation, Internal Normalization) for reducing the effects of the drift in order to improve the stability and the reliability of short term of the chemical sensors. And in order to compare the results of the methods, the standard deviation was used as a criterion. The sensor drift was analyzed by a trend line graph. We applied the three methods to the successive data measured for three days and compared the results. As a result of comparison, the standard deviation of DWT showed lowest value. (Before compensation: 7.1219, DWT: 1.3644, Baseline Manipulation: 2.5209, Internal Normalization: 3.1425).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.385-388
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• 2013

In this paper, we show the weakness of the image matching method by using MPEG-7 EHD(Edge Histogram Descriptor) and suggest how to improve this weakness by using image normalization. EHD algorithm is an image matching technique that collects edge's slope of distribution and same distribution. However, the EHD error rate is high because EHD is sensitive for changes of object distortion and rotation that will be matched. We improve matching performance by accurately extract edge information in image by using normalization. We compare and analyze the normalized EHD algorithm by using distortion and rotation and it shows robustness for changes of the size and rotation.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.69-75
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• 2011

This paper investigates phrase positional effects on the timing of F0 (pitch) peaks in Tokyo Japanese disyllabic words with varying accent type (HL or LH) and phrase position (final or non final). The F0 peak timing was normalized by the total word duration ('normalized H timing'). The normalized H timing was significantly affected by accent type and phrase position. The H timing was later in the LH accent type than in the HL accent type, and in non final positions than in final positions. In addition, to examine the validity of the quantitative results, different models of phrase position effects were compared by measuring H timing in two approaches: normalization versus relative distance measures. For the normalization measures, the H timing was measured as the time of the F0 peak divided by the total word duration or by the duration of the tone bearing syllable. For the relative distance measures, the H timing was measured as the distance in milliseconds from the end of the word or from the end of the associated syllable. The best model was the normalization by the total word duration, rather than by the duration of the tone bearing syllable. This means that phrase positional effects on the timing of F0 peaks in Japanese disyllabic words are best modeled in terms of proportion of the total word duration.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.75-80
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• 2008

This paper proposes a method to detect scene change using global decision tree that extract boundary cut that have width of big change that happen by camera brake from difference value of frames. First, calculate frame difference value through regional X2-histogram and normalization, next, calculate distance between difference value using normalization. Shot boundary detection is performed by compare global threshold distance with distance value for two adjacent frames that calculating global threshold distance based on distance between calculated difference value. Global decision tree proposed this paper can detect easily sudden scene change such as motion from object or camera and flashlight.

• Journal of Biosystems Engineering
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• v.35 no.6
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• pp.450-457
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• 2010

Although cherry tomato is one of major vegetables consumed in fresh vegetable market, the quality grading method is mostly dependant on size measurement using drum shape sorting machines. Using Visible/Near-infrared spectroscopy, apparatus to be able to acquire transmittance spectrum data was made and used to estimate firmness, sugar content, and acidity of cherry tomatoes grown at hydroponic and soil culture. Partial least square (PLS) models were performed to predict firmness, sugar content, and acidity for the acquired transmittance spectra. To enhance accuracy of the PLS models, several preprocessing methods were carried out, such as normalization, multiplicative scatter correction (MSC), standard normal variate (SNV), and derivatives, etc. The coefficient of determination ($R^2_p$) and standard error of prediction (SEP) for the prediction of firmness, sugar, and acidity of cherry tomatoes from green to red ripening stages were 0.859 and 1.899 kgf, with a preprocessing of normalization, 0.790 and $0.434^{\circ}Brix$ with a preprocessing of the 1st derivative of Savitzky Golay, and 0.518 and 0.229% with a preprocessing normalization, respectively.

• Journal of the Korean Professional Engineers Association
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• v.31 no.1
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• pp.38-45
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• 1998

• Korean Journal of Cognitive Science
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• v.7 no.2
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• pp.39-56
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• 1996

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.04a
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• pp.99-101
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• 1986