Derivation of Stem Taper Equations and a Stem Volume Table for Quercus acuta in a Warm Temperate Region (난대지역 붉가시나무의 수간곡선식 도출 및 수간재적표 작성)
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- Journal of Korean Society of Forest Science
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- v.112 no.4
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- pp.417-425
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- 2023
The aim of this study was to derive stem taper equations for Quercus acuta, one of main evergreen broad-leaved tree species found in warm temperate regions, and to prepare a stem volume table using those stem taper equations. A total of 688 individual trees were used in the analysis, which were collected from Jeonnam-do, Gyeongnam-do, and Jeju-do. The stem taper models applied to derive the stem curve pattern were the Max and Burkhart, Kozak, and Lee models. Among the three stem taper models, the best explanation of the stem curve shape of Q. acuta was found to be given by the Kozak model, which showed a fitness index of 0.9583, bias of 0.0352, percentage of estimated standard error of 1.1439, and mean absolute deviation of 0.6751. Thus, the stem taper of Q. acuta was estimated using the Kozak model. Moreover,thestemvolumecalculationwasperforme d by applying the Smalian formula to the diameter and height of each stem interval. In addition, an analysis of variance (ANOVA) was conducted to compare the two existing Q. acuta stem volume tables (2007 and 2010) and the newly created stem volume table (2023). This analysis revealed that the stem volume table constructed in the Wando region in 2007 included about twice as much as the stem volume tables constructed in 2010 and 2023. The stem volume table (2023) developed in this study is not only based on the regional collection range and number of utilized trees but also on a sound scientific basis. Therefore, it can be used at the national level as an official stem volume table for Q. acuta.
Purpose: Latest linear accelerator and the introduction of new measurement equipment to the agency that the introduction of this equipment in the future, by analyzing the process of confirming the usefulness of the preparation process for applying it in the clinical causes some problems, should be helpful. Materials and Methods: All measurements TrueBEAM STX (Varian, USA) was used, and a file specific to each energy, irradiation conditions, the dose distribution was calculated using a computerized treatment planning equipment (Eclipse ver 10.0.39, Varian, USA). Measuring performance and cause errors in MapCHECK 2 were analyzed and measured against. In order to verify the performance of the MapCHECK 2, 6X, 6X-FFF, 10X, 10X-FFF, 15X field size
The Purpose of Study 1. Inspection of clinical application on TCD to CVA 2. Objective Comparement and analysis about treatment effect of Western-Medicine, Korean Medicine, Cooperative consultation of Korean and Western medicice for CVA The Subject of Study We intended for the eighty six patient of CVA who had been treated in the Oriental Medical Hospital at Dong Eui Medical Center from 1997. 8. I to 1998. 7. 31 1. View of CT, MRI : the patient of Cb infarction 2. Attack Time : The patient who coming hospital falling ill within the early one week The method of study 1. Treat four group of Korean medicine, Constitution medicine, Western medicine, cooperative consultation of Korean medicine and Western medicine. 2. Application of TCD Check the result for three times, immediatly after the attack, two months later, four months later 3. Comparative analysis of each treatment effect by clinical symptoms and pathologic examination 4. The Judgement of the patient The Result From 8/1/1997 to 7/31/1998, We have the following result by clinical analysis intended for CVA 86 patients who had been treated in the Oriental Medical Hospital at Dong Eui Medical Center from 1997. 8. 1 to 1998. 7. 31 in 1. Analysis according to Age The first stage of thirties, forties, seventies is heavier than forties, fifties in improvement and Index of improvement of symptom 2. Analysis according to sex We have no special relation in an average of symptom and improvement, Index improvement 3. Analysis according to Family History We have the better result in first stage and improvement, index improvement when no family history. 4. Analysis according to Past History We have no special relation in past history like hypertension, DM, heart problem 5. Analysis devided two group, above group and under group on the basis of the average in first stage of all patient. We have the better result when the first stage is light, that the first score of barthel index and CNS is high. 6. Analysis of the effect of treatment about Korean medical treatment, Western medical treatment, cooperative treatment. In this study, the highest group of rate of treatment at four contrast groups (Korean medicine, Constitution medicine, Western medicine, cooperative treatment according to dyagnosis and range of treatment was the patient group of doing dyagnosis and method of treatment based on constitution medicine theory. This is that of doing demostation, A-Tx, po-herb-medication according to dyagnosis and treat method of constitution of Lee Je-ma In case of left, the case of dyagnosis any disease according to doctor view but, normal in TCDwas 22-beginning of attack, 20- two weeks later, 11 case-four weeks later in case of right, 15-beginning of attack, 12-two weeks later, 9 case four weeks later. So left vessel compares to right vessel is more interference, in fact more than a 1/2 of the patients of MCA disease can't do dyagnosis. In rate of imparement, the state of pacient improved but there isn't the improved case of result in TCD. 7. In TCD dyagnosis, between the case of inconsus the doctor view specially MCA in brain blood vessel is in large numbers and in total 86's patient, impossible case of dyagnosis according to interferiance of temporal is 21 case. 7. Result study about application of Kreaan medical treatment 1) The impossible patient of observation MCA blood vescular for interference temporal bone happened in large numbers. 2) There is the case having difference result to CT,MRI, MRA result. 3) Because individual difference is large, excluding to ananalogy of symptom. This is normal numerical value that has possibility of being checked as abnormal numerical value 4) there are a lot of cases that the speed of normal part is as similarly measured as that of abnormal part. It means that we cannot judge the disease by this measure 5) It is rare that this measure represent degree of improvement in patient's condition of disease. When we observe patient's condition become better, but we have no case that the result of TCD test better. 6) The result could be appear differently by the technique of the tester or by the experience of the tester 7) In the TCD test, abnormal symptoms is checked at 0 week, but at 2th week, normal symptoms is checked, again at 4th week abnormal is checked. According to the above result, CVA diagnosis is difficult only with TCD, as it appear in diagnosis error check which is suggested in the problem connected to project, for the aged persons who have the worst hardening of part of the cranium (1998. 5. 26 77 of 83 patients is 50s) there is a lot of cases that the measurement is impossible by TCD and the correction of measurement numerical value is decreased, as the age of cerebral infarction is high, TCD is inappropriate to diagnosis equipment through this study.
The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.
Purpose: We evaluated usefulness of abdominal compressor for stereotactic body radiotherapy (SBRT) with unresectable hepatocellular carcinoma (HCC) patients and hepato-biliary cancer and metastatic liver cancer patients. Materials and Methods: From November 2011 to March 2012, we selected HCC patients who gained reduction of diaphragm movement >1 cm through abdominal compressor (diaphragm control, elekta, sweden) for HT (Hi-Art Tomotherapy, USA). We got planning computed tomography (CT) images and 4 dimensional (4D) images through 4D CT (somatom sensation, siemens, germany). The gross tumor volume (GTV) included a gross tumor and margins considering tumor movement. The planning target volume (PTV) included a 5 to 7 mm safety margin around GTV. We classified patients into two groups according to distance between tumor and organs at risk (OAR, stomach, duodenum, bowel). Patients with the distance more than 1 cm are classified as the 1st group and they received SBRT of 4 or 5 fractions. Patients with the distance less than 1 cm are classified as the 2nd group and they received tomotherapy of 20 fractions. Megavoltage computed tomography (MVCT) were performed 4 or 10 fractions. When we verify a MVCT fusion considering priority to liver than bone-technique. We sent MVCT images to Mim_vista (Mimsoftware, ver .5.4. USA) and we re-delineated stomach, duodenum and bowel to bowel_organ and delineated liver. First, we analyzed MVCT images to check the setup variation. Second we compared dose difference between tumor and OAR based on adaptive dose through adaptive planning station and Mim_vista. Results: Average setup variation from MVCT was