• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.252-252
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• 2017

Nowadays water shortage is becoming one of the biggest problems in the Korea. Many different methods are developed for conservation of water. Soil water management has become the most indispensable factor for augmenting the crop productivity especially on soybean (Glycine max L.) because of their high susceptibility to both water stress and water logging at various growth stages. The farmers have been using irrigation techniques through manual control which farmers irrigate lands at regular intervals. Automatic irrigation systems are convenient, especially for those who need to travel. If automatic irrigation systems are installed and programmed properly, they can even save you money and help in water conservation. Automatic irrigation systems can be programmed to provide automatic irrigation to the plants which helps in saving money and water and to discharge more precise amounts of water in a targeted area, which promotes water conservation. The objective of this study was to determine the possible effect of automatic irrigation systems based on soil moisture on soybean growth. This experiment was conducted on an upland field with sandy loam soils in Department of Southern Area Crop, NICS, RDA. The study had three different irrigation methods; sprinkle irrigation (SI), surface drip irrigation (SDI) and fountain irrigation (FI). SI was installed at spacing of $7{\times}7m$ and $1.8m^3/hr$ as square for per irrigation plot, a lateral pipe of SDI was laid down to 1.2 m row spacing with $2.3L\;h^{-1}$ discharge rate, the distance between laterals was 20 cm spacing between drippers and FI was laid down in 3m interval as square for per irrigation plot. Soybean (Daewon) cultivar was sown in the June $20^{th}$, 2016, planted in 2 rows of apart in 1.2 m wide rows and distance between hills was 20 cm. All agronomic practices were done as the recommended cultivation. This automatic irrigation system had valves to turn irrigation on/off easily by automated controller, solenoids and moisture sensor which were set the reference level as available soil moisture levels of 30% at 10cm depth. The efficiency of applied irrigation was obtained by dividing the total water stored in the effective root zone to the applied irrigation water. Results showed that seasonal applied irrigation water amounts were $60.4ton\;10a^{-1}$ (SI), $47.3ton\;10a^{-1}$ (SDI) and $92.6 ton\;10a^{-1}$ (FI), respectively. The most significant advantage of SDI system was that water was supplied near the root zone of plants drip by drip. This system saved a large quantity of water by 27.5% and 95.6% compared to SI, FI system. The average soybean yield was significantly affected by different irrigation methods. The soybean yield by different irrigation methods were $309.7kg\;10a^{-1}$ from SDI $282.2kg\;10a^{-1}$ from SI, $289.4kg\;10a^{-1}$ from FI, and $206.3kg\;10a^{-1}$ from control, respectively. SDI resulted in increase of soybean yield by 50.1%, 7.0% 9.8% compared to non-irrigation (control), FI and SI, respectively. Therefore, the automatic irrigation system supplied water only when the soil moisture in the soil went below the reference. Due to the direct transfer of water to the roots water conservation took place and also helped to maintain the moisture to soil ratio at the root zone constant. Thus the system is efficient and compatible to changing environment. The automatic irrigation system provides with several benefits and can operate with less manpower. In conclusion, improving automatic irrigation system can contribute greatly to reducing production costs of crops and making the industry more competitive and sustainable.

• Korean Journal of Environment and Ecology
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• v.28 no.5
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• pp.550-558
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• 2014

This study was conducted to investigate the distribution and the population dynamics of Hipparchia autonoe by using a line transect and Mark-Release-Recapture (MRR) at the Mt. Halla in Jeju Island. The results showed that H. autonoe was found from 1,500 m above the sea level. Total 1,493 H. autonoe with 978 males and 515 females were captured and released in the MRR study site. Among them, 518 individuals including 284 males and 234 females were recaptured. The average survival time was 2.31 days with 2.14 days for males and 3.47 days for females, indicating longer survival time in case of females than males. The daily population size of males estimated in the MRR study site was maintained about 1,000 individuals in July and gradually decreased less than 200 in August. The number of females showed peak at 335 individuals on July 24, and gradually decreased less than 120 in August. Thus, female population was 1/3 of males. The average travel distance of male and female H. autonoe were $116.8{\pm}191.9m$ and $118.4{\pm}161.5m$, respectively, indicating almost same between sexes. H. autonoe in the Mt. Halla formed single population group in the wide meadow around the Baekrokdam Lake. The highest population density of H. autonoe was occurred in the restored area from damages, where host plants such as the sheep's fescue or the food plant are abundant by artificial restoration efforts.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.1
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• pp.39-43
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• 2012

Purpose: In hospital image-guided radiation therapy in patients with bladder cancer to enhance the reproducibility of the appropriate amount, depending on the patient's condition, and image-guided injection of saline system (On-Board Imager system, OBI, VARIAN, USA) three of the Cone-Beam CT dimensional matching (3D-3D matching) to be the treatment. In this study, the treatment of patients with bladder cancer at Cone-Beam CT image obtained through the analysis of the bones based matching and matching based on the bladder to learn about the differences, the bladder's volume change injected saline solution by looking at the bladder for the treatment of patients with a more appropriate image matching is to assess how the discussion. Materials and Methods: At our hospital from January 2009 to April 2010 admitted for radiation therapy patients, 7 patients with bladder cancer using a Folly catheter of residual urine in the bladder after removing the amount determined according to individual patient enough to inject saline CT-Sim was designed after the treatment plan. After that, using OBI before treatment to confirm position with Cone-Beam CT scan was physician in charge of matching was performed in all patients. CBCT images using a total of 45 bones, bladder, based on image matching and image matching based on the difference were analyzed. In addition, changes in bladder volume of Eclipse (version 8.0, VARIAN, USA) persuaded through. Results: Bones, one based image matching based on the bladder and re-matching the X axis is the difference between the average $3{\pm}2mm$, Y axis, $1.8{\pm}1.3mm$, Z-axis travel distance is $2.3{\pm}1.7mm$ and the overall $4.8{\pm}2.0mm$, respectively. The volume of the bladder compared to the baseline showed a difference of $4.03{\pm}3.97%$. Conclusion: Anatomical location and nature of the bladder due to internal movement of the bones, even after matching with the image of the bladder occurred in different locations. In addition, the volume of saline-filled bladder showed up the difference between the 4.03 percent, but matched in both images to be included in the planned volumes were able to confirm. Thus, after injection of saline into the bladder base by providing a more accurate image matching will be able to conduct therapy.

• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.1-10
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• 2016

The hypocenter distribution of microseismic events generated by hydraulic fracturing for shale gas development provides essential information for understanding characteristics of fracture network. In this study, we evaluate how inaccurate velocity models influence the inversion results of two widely used location programs, hypoellipse and hypoDD, which are developed based on an iterative linear inversion. We assume that 98 stations are densely located inside the circle with a radius of 4 km and 5 artificial hypocenter sets (S0 ~ S4) are located from the center of the network to the south with 1 km interval. Each hypocenter set contains 25 events placed on the plane. To quantify accuracies of the inversion results, we defined 6 parameters: difference between average hypocenters of assumed and inverted locations, $d_1$; ratio of assumed and inverted areas estimated by hypocenters, r; difference between dip of the reference plane and the best fitting plane for determined hypocenters, ${\theta}$; difference between strike of the reference plane and the best fitting plane for determined hypocenters, ${\phi}$; root-mean-square distance between hypocenters and the best fitting plane, $d_2$; root-mean-square error in horizontal direction on the best fitting plane, $d_3$. Synthetic travel times are calculated for the reference model having 1D layered structure and the inaccurate velocity model for the inversion is constructed by using normal distribution with standard deviations of 0.1, 0.2, and 0.3 km/s, respectively, with respect to the reference model. The parameters $d_1$, r, ${\theta}$, and $d_2$ show positive correlation with the level of velocity perturbations, but the others are not sensitive to the perturbations except S4, which is located at the outer boundary of the network. In cases of S0, S1, S2, and S3, hypoellipse and hypoDD provide similar results for $d_1$. However, for other parameters, hypoDD shows much better results and errors of locations can be reduced by about several meters regardless of the level of perturbations. In light of the purpose to understand the characteristics of hydraulic fracturing, $1{\sigma}$ error of velocity structure should be under 0.2 km/s in hypoellipse and 0.3 km/s in hypoDD.