• International Journal of Highway Engineering
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• v.12 no.2
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• pp.17-23
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• 2010

Since the relatively stiff binder shows a higher tensile strength as well as higher rutting resistance, it is believed that the binder stiffness is an important factor for rutting and tensile strength of asphalt mixtures. The typical tensile property is measured by indirect tensile strength (ITS) test at $25^{\circ}C$ and the rutting resistance is most widely measured by wheel tracking (WT) test at $60^{\circ}C$. The deformation strength ($S_D$) is newly developed property to estimate rut resistance of asphalt concretes at $60^{\circ}C$. The ITS and $S_D$ are very simple to measure by static test techniques, but the WT is measured by repeated loading procedure which requires relatively longer time and more efforts. Since these three properties are highly dependent upon the binder stiffness, it may be possible to estimate one property from another. Therefore, this study investigate the possibility of estimating the rutting characteristics (measured by WT test) by ITS or $S_D$ test, and the ITS by $S_D$. Because of binder stiffness effect, in the WT estimation by ITS, a tendency was observed for the higher ITS mixture to have the lower rut depth, giving $R^2{\fallingdotseq}$0.6, on the average. The ITS estimation by $S_D$ showed $R^2{\fallingdotseq}$0.64, and the WT estimation by SD showed $R^2{\fallingdotseq}$0.84, which is highest correlation among the three. Therefore, it was concluded that there is relatively good possibility of estimating WT result by $S_D$, and even though $R^2$ is somewhat low, there is some correlation between WT and ITS.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.101-111
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• 2015

Stream restoration projects have become threats to riparian ecosystem in Rep. of korea. Riparian wildlife becomes isolated and the animals are often experience difficulties in crossing riparian corridors. The purposes of this study is to select suitable wildlife passages for wild animals crossing riparian corridors. Maximum entropy model and snow tracking data on embankment in winter seasons were used to develop species distribution models to select suitable wildlife passages for water deer. The analysis suggests the following. Firstly, most significant factors for water deer's habitat in area nearby riparian area are shown to distance to water, age-class, land cover, slope, aspect, digital elevation model, tree density, and distance to road. For the riparian area, significant factors are shown to be land cover, size of riparian area, distance to tributary, and distance to built-up. Secondly, the suitable wildlife passages are recommended to reflect areas of high suitability with Maximum Entropy model in riparian areas and the surrounding areas and moving passages. The selected suitable areas are shown to be areas with low connectivity due to roads and vertical levee although typical habitats for water deer are forest, grassland, and farmland. In addition, the analysis of traces on snow suggests that the water deer make a detour around the artificial structures. In addition, the water deer are shown to make a detour around the fences of roads and embankment around farmland. Lastly, the water deer prefer habitats around riparian areas following tributaries. The method used in this study is expected to provide cost-efficient and functional analysis in selecting suitable areas.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.11
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• pp.1007-1018
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• 2009

Hydrocyclone is widely used in industry, because of its simplicity in design, high capacity, low maintenance and operational cost. The separation action of a hydrocyclone treating particulate slurry is a consequence of the swirling flow that produces a centrifugal force on the fluid and suspended particles. In spite of hydrocyclone have many advantage, the application for treatment of urban stormwater case study were rare. We conducted a laboratory scale study on treatable potential of micro particles using hydrocyclone filter (HCF) that was a combined modified hydrocyclone with perlite filter cartridge. Since it was not easy to use actual storm water in the scaled-down hydraulic model investigations, it was necessary to reproduce ranges of particles sizes with synthetic materials. The synthesized storm runoff was made with water and addition of particles; ion exchange resin, road sediment, commercial area manhole sediment, and silica gel particles. Experimental studies have been carried out about the particle separation performance of HCF-open system and HCF-closed system. The principal structural differences of these HCFs are underflow zone structure and vortex finder. HCF was made of acryl resin with 120 mm of diameter hydrocyclone and 250 mm of diameter filter chamber and overall height of 800 mm. To determine the removal efficiency for various influent concentrations of suspended solids (SS) and chemical oxygen demand (COD), tests were performed with different operational conditions. The operated maximum of surface loading rate was about 700 $m^3/m^2$/day for HCF-open system, and 1,200 $m^3/m^2$/day for HCF-closed system. It was found that particle removal efficiency for the HCF-closed system is better than the HCF-open system under same surface loading rate. Results showed that SS removal efficiency with the HCF-closed system improved by about 8~20% compared with HCF-open system. The average removal efficiency difference for HCF-closed system between measurement and CFD particle tracking simulation was about 4%.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.