• Title/Summary/Keyword: Varying coefficient

Search Result 584, Processing Time 0.023 seconds

Optimization of Subtraction Brain Perfusion SPECT with Basal/Acetazolamide Consecutive Acquisition (기저/아세타졸아미드 부하 연속 촬영 뇌관류 SPECT 최적화)

  • Lee, Dong-Soo;Lee, Tae-Hoon;Kim, Kyeong-Min;Chung, June-Key;Lee, Myung-Chul;Koh, Chang-Soon
    • The Korean Journal of Nuclear Medicine
    • /
    • v.31 no.3
    • /
    • pp.330-338
    • /
    • 1997
  • This study investigated the method to adjust acquisition time(a) and injection dose (i) to make the best basal and subtraction images in consecutive SPECT. Image quality was assumed to be mainly affected by signal to noise ratio(S/N). Basal image was subtracted from the second image consecutively acquired at the same position. We calculated S/N ratio in basal SPECT images($S_1/N_1$) and subtraction SPECT images(Ss/Ns) to find a(time) and i(dose) to maximize S/N of both images at the same time. From phantom images, we drew the relation of image counts and a(time) and i(dose) in our system using fanbeam-high-resolution collimated triple head SPECT. Noise by imaging process depended on Poisson distribution. We took maximum tolerable duration of consecutive acquisition as 30 minutes and maximum injectible dose as 1,850MBq(50 mCi)(sum of two injections) per study. Counts of second-acquired image($S_2$), counts($S_s$) and noise($N_s$) of subtraction SPECT were as follows. $C_1$ was the coefficient of measurement with our system. $$S_2=S_1{\cdot}(\frac{30-a}{a})+background{\cdot}(1-\frac{30-a}{a})+C_1{\cdot}(30-a){\cdot}{\epsilon}{\cdot}(50-i)$$ $$Ss=S_2-\{S_1{\cdot}(\frac{30-a}{a})+background{\cdot}(1-\frac{(30-a)}{a})\}$$ $$Ns={\sqrt{N_2^2+N_1^2{\cdot}\frac{(30-a)^2}{a^2}}={\sqrt{S_2+S_1{\cdot}\frac{(30-a)^2}{a^2}}$$ In case of rest/acetazolamide study, effect(${\epsilon}$) of acetazolamide to increase global brain uptake of Tc-99m-HMPAO could be 1.5 or less. Varying ${\epsilon}$ from 1 to 1.5, a(time) and i(dose) pair to maximize both $S_1/N_l$ and Ss/Ns was determined. 15 mCi/17 min and 35mCi/13min was the best a(time) and i(dose) pair for rest/acetazolamide study(when ${\epsilon}$ were 1.2) and came to be used for our clinical routine after this study. We developed simple method to maximize S/N ratios of basal and subtraction SPECT from consecutive acquisition. This method could be applied to ECD/HMPAO and brain activation studies as well as rest/acetazolamide studies.

  • PDF

Study on the Concentration Estimation Equation of Nitrogen Dioxide using Hyperspectral Sensor (초분광센서를 활용한 이산화질소 농도 추정식에 관한 연구)

  • Jeon, Eui-Ik;Park, Jin-Woo;Lim, Seong-Ha;Kim, Dong-Woo;Yu, Jae-Jin;Son, Seung-Woo;Jeon, Hyung-Jin;Yoon, Jeong-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.20 no.6
    • /
    • pp.19-25
    • /
    • 2019
  • The CleanSYS(Clean SYStem) is operated to monitor air pollutants emitted from specific industrial complexes in Korea. So the industrial complexes without the system are directly monitored by the control officers. For efficient monitoring, studies using various sensors have been conducted to monitor air pollutants emitted from industrial complex. In this study, hyperspectral sensors were used to model and verify the equations for estimating the concentration of $NO_2$(nitrogen dioxide) in air pollutants emitted. For development of the equations, spectral radiance were observed for $NO_2$ at various concentrations with different SZA(Solar Zenith Angle), VZA(Viewing Zenith Angle), and RAA(Relative Azimuth Angle). From the observed spectral radiance, the calculated value of the difference between the values of the specific wavelengths was taken as an absorption depth, and the equations were developed using the relationship between the depth and the $NO_2$ concentration. The spectral radiance mixed gas of $NO_2$ and $SO_2$(sulfur dioxide) was used to verify the equations. As a result, the $R^2$(coefficient of determination) and RMSE(Root Mean Square Error) were different from 0.71~0.88 and 72~23 ppm according to the form of the equation, and $R^2$ of the exponential form was the highest among the equations. Depending on the type of the equations, the accuracy of the estimated concentration with varying concentrations is not constant. However, if the equations are advanced in the future, hyperspectral sensors can be used to monitor the $NO_2$ emitted from the industrial complex.

Analysis of Waterbody Changes in Small and Medium-Sized Reservoirs Using Optical Satellite Imagery Based on Google Earth Engine (Google Earth Engine 기반 광학 위성영상을 이용한 중소규모 저수지 수체 변화 분석)

  • Younghyun Cho;Joonwoo Noh
    • Korean Journal of Remote Sensing
    • /
    • v.40 no.4
    • /
    • pp.363-375
    • /
    • 2024
  • Waterbody change detection using satellite images has recently been carried out in various regions in South Korea, utilizing multiple types of sensors. This study utilizes optical satellite images from Landsat and Sentinel-2 based on Google Earth Engine (GEE) to analyze long-term surface water area changes in four monitored small and medium-sized water supply dams and agricultural reservoirs in South Korea. The analysis covers 19 years for the water supply dams and 27 years for the agricultural reservoirs. By employing image analysis methods such as normalized difference water index, Canny Edge Detection, and Otsu'sthresholding for waterbody detection, the study reliably extracted water surface areas, allowing for clear annual changes in waterbodies to be observed. When comparing the time series data of surface water areas derived from satellite images to actual measured water levels, a high correlation coefficient above 0.8 was found for the water supply dams. However, the agricultural reservoirs showed a lower correlation, between 0.5 and 0.7, attributed to the characteristics of agricultural reservoir management and the inadequacy of comparative data rather than the satellite image analysis itself. The analysis also revealed several inconsistencies in the results for smaller reservoirs, indicating the need for further studies on these reservoirs. The changes in surface water area, calculated using GEE, provide valuable spatial information on waterbody changes across the entire watershed, which cannot be identified solely by measuring water levels. This highlights the usefulness of efficiently processing extensive long-term satellite imagery data. Based on these findings, it is expected that future research could apply this method to a larger number of dam reservoirs with varying sizes,shapes, and monitoring statuses, potentially yielding additional insights into different reservoir groups.

Studies on the morphological variation of plant organs of elongating node-part in rice plant (수도 신장 절위 경엽의 형태변이에 관한 연구)

  • 김만수
    • KOREAN JOURNAL OF CROP SCIENCE
    • /
    • v.5 no.1
    • /
    • pp.1-35
    • /
    • 1969
  • Attempts were made to obtain the fundamental knowledge on the quantitative constitution status of leaves and stem of elongating node-part, and the relationships between these morphological characteristics along with the nitrogen contents of leaves and grain yield were examined varing application amounts of nitrogen in rice plant. I. The agronomic characteristics of leaves and nodes of elongation node-part (4-node parts from the top of stem) were observed at heading stage with 20 leading rice varieties of Kang Won district. The results are summarized as follows: 1. Leaf area magnitude of the flag and the fourth leaf was smaller than that of the second and the third with the average value of flag leaf 18.61 $cm^2$, the second leaf 21.84 $cm^2$, the third 21.52 $cm^2$ and the fourth 18.56 $cm^2$. The weight of leaf blade showed an isotonic tendency with the magnitude of leaf area with the value of the flag leaf 97.0 mg, the second leaf 117.1 mg, the third 115.4 mg, and the fourth 95.3 mg. The weight of each leaf sheath was remarkably larger at the higher node-part than at the lower node-part of the stem with the value of flag leaf sheath 176.3 mg, the second 163.7 mg, the third 163.4 mg and the fourth 123.9 mg. Accordingly, the total leaf weight of each part was larger at the second and the third leaf than at the first and the fourth. Total plant weight of each part (weight of leaf blade, leaf sheath, and culm) also was larger at the middle node-part. 2. Coefficients of variation for the varietal differences of the morphological characteristics of elongating node-part were 12.75% for the leaf area, 15.29% for the weight of leaf blade, 15.90%, for the weight of leaf sheath, 11.42% for the weight of internode, 15.45% for the leaf weight (leaf blade & leaf sheath) and 13.24% for the straw weight. And these coefficient values of the most characteristics were, on the whole, smaller at the second and the third node-part than at the first and the fourth node-part, but the coefficient value of the internode weight was rather small at the third and fourth node-part. 3. Constitutional ratio of each plant organ to the total plant weight in term of dry matter weight (excluding head and root wight) was 39.2% for the leaf sheath, 34.2% for the culm, 26.6% for the leaf blade. And ocnstitutional ratio of leaf sheath in term of dry matter weight was larger at the higher position in contrast with that of culm. 4. Average weight ration of leaf blade to culm, leaf sheath to culm, leaf blades to sheath and the leaf blades to culm plus leaf sheath were 77.7 %, 114.5%, 67.9% and 36.2%, respectively. With regard to the position of the plant organ, the weight ratio of leaf blade to culm and that of leaf sheath to culm were larger at higher part in contrast with that of leaf blade to leaf sheath. 5. Generally, there founded deep relationships between grain yield and each morphological characteristics of plant organ of elongating node-part as follows; Correlation coefficient between total area of 4 leaves (from flag to the fourth leaf) and grain yield was ${\gamma}$=0.666$^{**}$ In regard to the position of leaves, correlation coefficient values of flag, the second, the third and the fourth leaf were ${\gamma}$=0.659$^{**}$, ${\gamma}$=0.609$^{**}$, ${\gamma}$=0.464$^{*}$ and ${\gamma}$=0.523$^{*}$, respectively. Correlation coefficient between total weight of leaf blades and the grain yield was ${\gamma}$=0.678$^{**}$. In regard to the position of leaves, that of flag leaf was ${\gamma}$=0.691$^{**}$, and ${\gamma}$=0.654$^{**}$ for the second leaf, ${\gamma}$=0.570$^{**}$ for the third, and ${\gamma}$=0.544$^{**}$ for the fourth. Correlation between the weight of leaves (blade weight plus sheath weight) and the grain yield showed similar values. In the relationship between plant weight and grain yield there also was significant correlation, but with highly significant value only for the first node-part. There appeared correlation between total weight of leaf sheath and grain yield with the value of ${\gamma}$=0.572$^{**}$ and in regard to the position of each leaf sheath the values were ${\gamma}$=0.623$^{**}$ for the flag leaf, ${\gamma}$=0.486$^{**}$ for the second leaf, ${\gamma}$=0.513$^{**}$ for the third, ${\gamma}$=0.450$^{**}$ for the fourth. However, there was no significant correlation between culm weight and grain yield. 6. With respect to in gain yield, varietal differences in magnitude of leaf area, weight of leaf blade, leaf weight per unit area, weight of leaf sheath, culm weight, total leaf and stem weight were larger in the case of high yielding varieties and decreased in accordance with decreasing yield. And this tendency also was shown in the varietal differences of magnitude of each part. Variation in magnitude of each part for the leaf area, weight of leaf blade, culm weight was significantly small in high yielding varieties compared to low yielding varieties. 7. Plant constitutional ratio of each organ of the elongating node-part in term of weight magnitnde varied to som extent according to varieties indicating leaf blade 27.6%, leaf sheath 39.5%, culm 32.9% in the case of high yielding varieties, leaf blade 25.5%, leaf sheath 38.1%, culm 36.4% in the case of low yielding varieties, and medium yielding varieties showed intermadiate values. 8. Far higher values of the weight ration of leaf blade to culm and leaf sheath to culm were given to the high yielding varieties compared to low yielding varieties. And medium yielding varieties showed intermadiate values. II. Effects of application rate of nitrogen on the morphological characteristics of the elongating node-part, nitrogen content of leaf blade, and their relation with the grain yield of the rice were observed with 3 rice varieties; Shin No.2, Shirogane, and Jinheung varying application amounts of nitrogen as 8kg, 12kg and 16kg per 10 are. 1. As for the variation of morphological magnitude s affected by the amounts of nitrogen application, total leaf area (4 leaves from the flag leaf) increased to 16.5% at 12kg N plot, and about 30% at 16kg N polt compared to 8kg N plot and total weight of leaf blade also increased to similar extent, respectively, in contrast with weight of leaf sheath increasing 4.9% and 7.8%, respectively. However, the weight of culm decreased to 1.5% and 11.2%at the 12kg N plot and 16kg N plot, respectively, and these decreasing rate was noted at the nodes of lower part. 2. As for the verietal differences in variation of morphological magnitude as affected by the amount of nitrogen fertilization, leaf area coefficient value of variation of the total leaf area was 15.40% for Shin No. 2, 12.87% for Shirogane, and 10.99% for Jinheung. With respect to the position of nodes, the largest variation of leaf blade magnitude was observed at the fourth for Shin No. 2, the second for Shirogan, and flag leaf for Jinheung. And there also was an isotonic varietal difference in the weight of leaf blade. Variation in total culm weight showed varietal differences with the coefficient value of 7.72% for Shin No.2, 12.11% for Shirogane, and 0.94% for Jinheung. There also was varietal differences in the variation according to the position of nodes. 3. Variation of each elongating node-part related to the fertilization amount decreased with the increase of fertilization amount in the items of leaf area, weight of leaf sheath, culm weight, but weight of leaf sheath varied more at heavier fertilization than at others. 4. Constitutional ratio of each organ excluding head also varied with fertilization amount; constitutional ratio of leaf blade increased much with the increasing amount of fertilization in contrast with the response of culm eight. However, constitutional ration of the weight of leaf sheath was not much affected. 5. Lower value of the ration of leaf blade to culm was given to the 8kg N per 10 are plot, and the ratio of leaf blade to leaf sheath decreased with the increasing amount of fertilization in contrast with the increase in the ratio of leaf sheath to culm. however, the ration of leaf blade to culm plus leaf sheath decreased. 6. With the increase of nitrogen fertilization, leaf area, weight of leaf blade and leaf sheath increased. Accordingly, grin yield also increased to some extent. It was noted that culm weight was changed inversely to the changes in grain yield, but the degree of this variation varied with varietal characteristics. 7. Nitrogen content of leaves at heading and fruiting stage varied with the fertilization amount, and average nitrogen content of leaves of the varieties used 2.19%, 2.49% and 2.74% at the plot of 8kg N, and 12kg N and 16kg N per 10 are, respectively, at heading time, and 0.80%, 0.92% and 1.03% at each plot at fruiting stage. Thus, nitrogen content of leaves increased much with the increasing amount of fertilization, and higher value was given to the leaves on the higher position of elongating node-part. 8. There also was variation of nitrogen content of leaves in accordance with the varieties. However higher grain yield was obtained from the plants retaining higher nitrogen content in leaves at heading or fruiting stage.

  • PDF