Hepatoma is one of 3 most common malignancies in Korea, the survival rate is not improved since last decades because of delayed diagnosis and limited treatment conditions. Radiation was one of treatment options but the impact on the survival is not remarkable. High dose exposure to target area was suggested for improved effect but low tolerance dose of normal liver tissue is the main limited factor. IMRT is the advanced form of 3DCRT, for focusing high dose on target with minimal dose to surrounding normal tissues. Motion of the tumor by respiration, cardiac pulsation and peristalsis is the main treatment harrier of IMRT for treatment of hepatoma patients. Development of QA technique for acceptable geometrical uncertainties and dose error on target volume is essential for IMRT in clinical treatment but proper QA technique is not yet developed. This study compared the verification film dosimetry with measured dose in phantom and calculated dose in planning computer on exactly same conditions of patient treatments. Within 3% dose differences between 3 groups were confirmed. We suggest that our verification QA technique is easy, economic, iterative and acceptable in clinical application for advanced hepatoma patients.
This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.
In this paper, a new audio reproduction system was developed in which the cross-talk signals would be reasonably cancelled at an arbitrary listener position. To adaptively remove the cross-talk signals according to the listener's position, a method of tracking the listener position was employed. This was achieved using the two microphones, where the listener direction was estimated using the time-delay between the two signals from the two microphones, respectively. Moreover, room reverberation effects were taken into consideration where linear prediction analysis was involved. To remove the cross-talk signals at the left-and right-ears, the paths between the sources and the ears were represented using the KEMAR head-related transfer functions (HRTFs) which were measured from the artificial dummy head. To evaluate the usefulness of the proposed listener tracking system, the performance of cross-talk cancellation was evaluated at the estimated listener positions. The performance was evaluated in terms of the channel separation ration (CSR), a -10 dB of CSR was experimentally achieved although the listener positions were more or less deviated. A real-time system was implemented using a floating-point digital signal processor (DSP). It was confirmed that the average errors of the listener direction was 5 degree and the subjects indicated that 80 % of the stimuli was perceived as the correct directions.
Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.
The performance of an electrometer directly affects on the accuracy and precision in radiation dosimetry. This study is to list of the quality control for maintaining performance and to perform evaluation tests of an electrometer. Performance tests selected include proper polarizing voltages, warm-up and equalization time, leakages, long-term stability, linearity, and effect of ambient conditions. An electrometer connected with a rigid stem ionization chamber was evaluated with a Strontium-90 check device. Bias voltage was measured directly on the input socket. Equalization time is the time required for reaching threshold of charged state after the power is on or the bias voltage is changed. Pre- and post-signal leakages are defined as the accumulation of signal with no exposure and after exposure, respectively. Over three months period, the electrometer's long-term stability was measured by comparison of the temperature-pressure corrected readings. Linearity was expressed as the deviation of readings from multiple short exposures from one continuous exposure. Effect of ambient conditions was expressed as the zero drift of the electrometer over 17-34$^{\circ}C$ temperature ranges. For two nominal values, 300 and 500 volts, measured voltages were lower by 2.5 and 5.8%, respectively. The warm-up time, 20 minutes, was longer than the lamp time by 9 minutes and the equalization time was less than 1 minute. Without exposure, the zero-drift was 0.002 scale-unit in 15 minutes and the leakage after 10 minutes exposure was minimal. The IQ-4 was stable over 99.4% for three-month periods. Deviation from the linearity was 0.9% for measurement scale, 0.000-9.991. Over 17-34$^{\circ}C$ temperature range, the zero-drift was minimal, less than 0.2%. For a clinically-used electrometer, a list for the basic peformance evaluations is proposed. By running this program, the measurement error using an electrometer can be reduced and in turn the improvement in accuracy and precision of radiation dosimetry can be achieved.
Purpose In a cyclosporine experiment using a robotic liquid handing system has found a deviation of its standard curve and low reproducibility of patients's results. The difference of the test is that methanol is mixed with samples and the extractions are used for the test. Therefore, we assumed that the abnormal test results came from using methanol and conducted this test. In a manual of a robotic liquid handling system mentions that we can choose several setting parameters depending on the viscosity of the liquids being used, the size of the sampling tips and the motor speeds that you elect to use but there's no exact order. This study was undertaken to confirm pipetting ability depending on types of liquids and investigate proper setting parameters for the optimum dispensing ability. Materials and Methods 4types of liquids(water, serum, methanol, PEG 6000(25%)) and $TSH^{125}I$ tracer(515 kBq) are used to confirm pipetting ability. 29 specimens for Cyclosporine test are used to compare results. Prepare 8 plastic tubes for each of the liquids and with multi pipette $400{\mu}l$ of each liquid is dispensed to 8 tubes and $100{\mu}l$ of $TSH^{125}I$ tracer are dispensed to all of the tubes. From the prepared samples, $100{\mu}l$ of liquids are dispensed using a robotic liquid handing system, counted and calculated its CV(%) depending on types of liquids. And then by adjusting several setting parameters(air gap, dispense time, delay time) the change of the CV(%)are calcutated and finds optimum setting parameters. 29 specimens are tested with 3 methods. The first(A) is manual method and the second(B) is used robotic liquid handling system with existing parameters. The third(C) is used robotic liquid handling system with adjusted parameters. Pipetting ability depending on types of liquids is assessed with CV(%). On the basis of (A), patients's test results are compared (A)and(B), (A)and(C) and they are assessed with %RE(%Relative error) and %Diff(%Difference). Results The CV(%) of the CPM depending on liquid types were water 0.88, serum 0.95, methanol 10.22 and PEG 0.68. As expected dispensing of methanol using a liquid handling system was the problem and others were good. The methanol's dispensing were conducted by adjusting several setting parameters. When transport air gap 0 was adjusted to 2 and 5, CV(%) were 20.16, 12.54 and when system air gap 0 was adjusted to 2 and 5, CV(%) were 8.94, 1.36. When adjusted to system air gap 2, transport air gap 2 was 12.96 and adjusted to system air gap 5, Transport air gap 5 was 1.33. When dispense speed was adjusted 300 to 100, CV(%) was 13.32 and when dispense delay was adjusted 200 to 100 was 13.55. When compared (B) to (A), the result increased 99.44% and %RE was 93.59%. When compared (C-system air gap was adjusted 0 to 5) to (A), the result increased 6.75% and %RE was 5.10%. Conclusion Adjusting speed and delay time of aspiration and dispense was meaningless but changing system air gap was effective. By adjusting several parameters proper value was found and it affected the practical result of the experiment. To optimize the system active efforts are needed through the test and in case of dispensing new types of liquids proper test is required to check the liquid is suitable for using the equipment.
TOPMODEL, semi-distributed hydrological model, is frequently applied to predict the amount of discharge, main flow pathways and water quality in a forested catchment, especially in a spatial dimension. TOPMODEL is a kind of conceptual model, not physical one. The main concept of TOPMODEL is constituted by the topographic index and soil transmissivity. Two components can be used for predicting the surface and subsurface contributing area. This study is conducted for the validation of applicability of TOPMODEL at small forested catchments in Korea. The experimental area is located at Gwangneung forest operated by Korea Forest Research Institute, Gyeonggi-do near Seoul metropolitan. Two study catchments in this area have been working since 1979 ; one is the natural mature deciduous forest(22.0 ha) about 80 years old and the other is the planted young coniferous forest(13.6 ha) about 22 years old. The data collected during the two events in July 1995 and June 2000 at the mature deciduous forest and the three events in July 1995 and 1999, August 2000 at the young coniferous forest were used as the observed data set, respectively. The topographic index was calculated using $10m{\times}10m$ resolution raster digital elevation map(DEM). The distribution of the topographic index ranged from 2.6 to 11.1 at the deciduous and 2.7 to 16.0 at the coniferous catchment. The result of the optimization using the forecasting efficiency as the objective function showed that the model parameter, m and the mean catchment value of surface saturated transmissivity, $lnT_0$ had a high sensitivity. The values of the optimized parameters for m and InT_0 were 0.034 and 0.038; 8.672 and 9.475 at the deciduous and 0.031, 0.032 and 0.033; 5.969, 7.129 and 7.575 at the coniferous catchment, respectively. The forecasting efficiencies resulted from the simulation using the optimized parameter were comparatively high ; 0.958 and 0.909 at the deciduous and 0.825, 0.922 and 0.961 at the coniferous catchment. The observed and simulated hyeto-hydrograph shoed that the time of lag to peak coincided well. Though the total runoff and peakflow of some events showed a discrepancy between the observed and simulated output, TOPMODEL could overall predict a hydrologic output at the estimation error less than 10 %. Therefore, TOPMODEL is useful tool for the prediction of runoff at an ungaged forested catchment in Korea.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
/
v.33
no.4
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pp.317-324
/
2015
GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (Tm), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.
Kim, Yeong-Seon;Seo, Myeong-Deok;Lee, Wan-Kyu;Song, Jae-Beom
The Korean Journal of Nuclear Medicine Technology
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v.18
no.2
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pp.8-16
/
2014
Purpose The quantitative analysis of gallbladder emptying is very important in diagnosis of motility disorder of gallbladder and in biliary physiology. The GBEF obtain the statics aquisition method or the dynamic acquisition method in two ways. The purpose of this study is to compare the GBEF value of statics acquisition method and the dynamic acquisition method. And we find the best way for calculate GBEF. Materials and Methods The quantitative hepatobiliary scan with $^{99m}Tc$-mebrofenin was performed of 27 patients. Initial images were acquired statically, for 60 min after injection of the radioactive tracer. And if the gallbladder is visualized to 60 min, performed stimulation of gallbladder (1egg, 200 mL milk). After that, started acquisition of dynamic image for 30 min. After that, image of after fatty meal of the statics method were acquired on equal terms with 60 min image. The statics GBEF was calculated using the images of before fatty meal and post fatty meal by the statics method. The dynamic GBEF was calculated using the images of time of maximum bile juice uptake ($T_{max}$) and time of minimum bile juice uptake ($T_{min}$) images from the gallbladder time-activity curve. A bile juice is secreted from gallbladder while eating a fatty meal. that is named early GBEF and that was calculated using before fatty meal image of the statics method and 1 min image of the dynamic method. Results The result saw very big difference between two according to $T_{max}$. The result, were as follows. 1) In case of less than 1 min, the dynamic mean GBEF was $40.1{\pm}21.7%$, the statics mean GBEF was $51.5{\pm}23.6%$ in 16 cases. The early mean GBEF was $14.0{\pm}29.1%$. The GBEF of statics method was higher because that include secreted bile juice while performed stimulation of gallbladder. A difference of GB counts according to acquisition method and the early bile juice counts was $17.6{\pm}14.8%$ and $13.5{\pm}15.3%$. 2) In case of exceed than 1 min, the dynamic mean GBEF was $31.0{\pm}19.7%$, the statics mean GBEF was $21.3{\pm}19.4%$ in 7 cases. The early GBEF was $-6.9{\pm}4.9%$. The GBEF of dynamic method was higher because that include concentrated bile juice to $T_{max}$. A difference of GB counts according to acquisition method and the early bile juice counts was $14.3{\pm}7.3%$ and $5.9{\pm}3.9%$. Conclusion The statics method is very easy and simple, but in case of $T_{max}$ delay, the GBEF can be lower. The dynamic method is able to calculate accurately in case of $T_{max}$ delay, but in case of $T_{max}$ is less than 1 min, the GBEF can be lower because dynamic GBEF exclude secreted bile juice while performed stimulation of gallbladder. The best way to calculate GBEF is to scan with dynamic method preferentially and to choose suitable method between the two way after conform $T_{max}$ on the T-A curve of the dynamic method.
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