• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.13 no.1
• /
• pp.42-55
• /
• 2008

To evaluate the accuracy of currents measured by HF radar in the coastal sea off Keum River estuary, we compared the facing radial vectors of two HF radars, and HF radar-derived currents with in-situ measurement currents. Principal component analysis was used to extract regression line and RMS deviation in the comparison. When two facing radar's radial vectors at the mid-point of baseline are compared, RMS deviation is 4.4 cm/s in winter and 5.4 cm/s in summer. When GDOP(Geometric Dilution of Precision) effect is corrected from the RMS deviations that is analyzed from the comparison between HF radar-derived and current-metermeasured currents, the error of velocity combined by HF radar-derived current is less than 5.1 cm/s in the stations having moderate GDOP values. These two results obtained from different method suggest that the lower limit of HF radar-derived current's accuracy is 5.4 cm/s in our study area. As mentioned in previous researches, RMS deviations become large in the stations located near the islands and increase as a function of mean distance from the radar site due to decrease of signal-to-noise level and the intersect angle of radial vectors. We found that an uncertain error bound of HF radar-derived current can be produced from the separation process of RMS deviations using GDOP value if GDOP value for each component is very close and RMS deviations obtained from current component comparison are also close. When the current measured in the stations having moderate GDOP values is separated into tidal and subtidal current, characteristics of tidal current ellipses analyzed from HF radar-derived current show a good agreement with those from current-meter-measured current, and time variation of subtidal current showed a response reflecting physical process driven by wind and density field.

• Investigative Magnetic Resonance Imaging
• /
• v.8 no.2
• /
• pp.100-108
• /
• 2004

Purpose : Early degeneration of articular cartilage is accompanied by a loss of glycosaminoglycan (GAG) and the consequent change of the integrity. The purpose of this study was to biochemically quantify the loss of GAG, and to evaluate the $Gd(DTPA)^{2-}$-enhanced, and T1, T2, rho relaxation map for detection of the early degeneration of cartilage. Materials and Methods : A cartilage-bone block in size of $8mm\;\times\;10mm$ was acquired from the patella in each of three pigs. Quantitative analysis of GAG of cartilage was performed at spectrophotometry by use of dimethylmethylene blue. Each of cartilage blocks was cultured in one of three different media: two different culture media (0.2 mg/ml trypsin solution, 1mM Gd $(DTPA)^{2-}$ mixed trypsin solution) and the control media (phosphate buffered saline (PBS)). The cartilage blocks were cultured for 5 hrs, during which MR images of the blocks were obtained at one hour interval (0 hr, 1 hr, 2 hr, 3 hr, 4 hr, 5 hr). And then, additional culture was done for 24 hrs and 48 hrs. Both T1-weighted image (TR/TE, 450/22 ms), and mixed-echo sequence (TR/TE, 760/21-168ms; 8 echoes) were obtained at all times using field of view 50 mm, slice thickness 2 mm, and matrix $256\times512$. The MRI data were analyzed with pixel-by-pixel comparisons. The cultured cartilage-bone blocks were microscopically observed using hematoxylin & eosin, toluidine blue, alcian blue, and trichrome stains. Results : At quantitation analysis, GAG concentration in the culture solutions was proportional to the culture durations. The T1-signal of the cartilage-bone block cultured in the $Gd(DTPA)^{2-}$ mixed solution was significantly higher ($42\%$ in average, p<0.05) than that of the cartilage-bone block cultured in the trypsin solution alone. The T1, T2, rho relaxation times of cultured tissue were not significantly correlated with culture duration (p>0.05). However the focal increase in T1 relaxation time at superficial and transitional layers of cartilage was seen in $Gd(DTPA)^{2-}$ mixed culture. Toluidine blue and alcian blue stains revealed multiple defects in whole thickness of the cartilage cultured in trypsin media. Conclusion : The quantitative analysis showed gradual loss of GAG proportional to the culture duration. Microimagings of cartilage with $Gd(DTPA)^{2-}$-enhancement, relaxation maps were available by pixel size of $97.9\times195\;{\mu}m$. Loss of GAG over time better demonstrated with $Gd(DTPA)^{2-}$-enhanced images than with T1, T2, rho relaxation maps. Therefore $Gd(DTPA)^{2-}$-enhanced T1-weighted image is superior for detection of early degeneration of cartilage.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2002.09a
• /
• pp.139-162
• /
• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• Trans-
• /
• v.12
• /
• pp.51-79
• /
• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.