The goal of radiation treatment is to deliver a prescribed radiation dose to the target volume accurately while minimizing dose to normal tissues. Due to inaccurate placement of field and shielding block and patient's movement, there could be displacement errors between the planed and treatment regions. In order to verify the location of radiation treatment, we in this study developed the registration algorithm of the x-ray simulator images and portal images and quantified the inaccuracy in terms of shift, scale and rotation. The algorithm for registration of pairs of radiation fields consists of the alignment of pairs of radiation images by points matching and field displacement analysis by field boundary matching. In the first step, paired surface landmarks are matched to calculate the transformation parameters (scale, rotation and shift) using the corresponding line pairs which are created by connecting two landmarks of each image. In the next step, portal field boundary is extracted and then the two field boundaries are matched by the $\rho$-$\theta$ technique. Applying the phantom portal images, detection errors were calculated to be less than 2mm in translation, 1$^{\circ}$ in rotation and 1% in scale. In conclusion, we quantitatively analyzed the displacement error of x-ray simulator images and portal images. The present results could contribute to the study of the radiation treatment verification.
The Journal of the Institute of Internet, Broadcasting and Communication
/
v.15
no.3
/
pp.99-105
/
2015
This paper deals with the mMMA (modified MMA) which possible to improving the convergence speed that employing the serial connecting form of two stage digital filter instead of signal filter of MMA adaptive equalizer without applying the variable step size for compensates the intersymbol interference by channel distortion in the nonconstant modulus signal. The adaptive equalizer can be implemented by signal digital filter using the finite order tap delay line. In this paper, the equalizer is implemented by the two stage serial form and the filter coefficient are updated by the error signal using the same algorithm of MMA in each stage. The fast convergence speed is determined in the first stage, and the residual isi left at the output of first stage output is minimized in the second stage filter. The same digital filter length was considered in single stage and two stage system and the performance of these systems were compared. The performance index includes the output signal constellation, the residual isi and maximum distortion, MSE that is measure of the convergence characteristics, the SER. As a result of computer simulation, mMMA that has a FIR structure of two stage, has more good performance in every performance index except the constellation diagram due to equalization noise and improves the convergence speed about 1.5~1.8 time than the present MMA that has a FIR structure of single stage.
Journal of the Institute of Electronics Engineers of Korea SD
/
v.45
no.1
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pp.7-13
/
2008
This paper proposes a newly structured circuit that can compensate current deviation of a data driver circuit for OLED. A conventional data drivel circuit for OLED cannot compensate the current deviation at the data drivel circuit output terminal generated by MOS process change, but the proposed data drivel circuit can authorize uniform value of current to an OLED panel by calibrating the current deviation at the output terminal. The proposed circuit can minimize current deviation of the output current via process change by connecting the circuit for data output current with a common interconnect line through addition of a switching transistor to the existing data output circuit. The circuit proposed in this paper has been designed based on an OLED panel supporting $128{\times}128$ resolution, and the process used for driver circuit development is 0.35um. As a result of the experiment in this study, the output current of the data driver circuit proposed here has 1% range of error, while 9% range of severe changes was demonstrated in the case of the previous data driver circuit. When using the data driver circuit for OLED proposed in this paper, high definition OLED display can be actualized and the circuit can be applied to mobile display devices requiring high quality display features.
Journal of the Korean Institute of Telematics and Electronics
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v.27
no.11
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pp.119-125
/
1990
This paper describes fiber optic voltage sensor using EOM-BSO (Electro-Optic Modulator-Bismuth Silicon Oxcide). Transceiver has an electical/optical converter and an optical/electrical converter which consist of light emitting diode, PIN-PD, and electronic circuits. Multimode fiber cable of $100/140{\mu}m$ core/clad diameter is used for connecting the transceiver to fiber cable and fiber optic voltage sensor. Before our experiments, by applying the Maxwell equations and wave equations, We derive matrix equation on wave propagation in the BSO single crystal. And also we derive optimal equation on intensity modulation arising through an analyzer. According to experi-mental results, fiber optic voltage sensor has maximum $2.5{\%}$ error within the applied AC voltage of 800V. As the applied voltage increases, saturation values of voltage sensor also increase. This phenomenon is caused by optical rotatory power of BSO single crystal. And temperature dependence of sensitivity for fiber optical rotatory power of BSO single crystal. And temperature dependence of sensitivity for fiber optic voltage sensor in the temperature range from$-20^{\circ}C\to\60^{\circ}C$ are measured within ${\pm}0.6{\%}$. And frequency characteristics of the voltage sensor has good frequency characteristics from DC to 100kHz.
The fuel-cut coast-down driving mode is activated when the acceleration pedal is released with transmission gear engaged, and it's a default function for electronic-controlled engine of vehicles. The fuel economy becomes better because fuel injection stops during fuel-cut driving mode. A fuel-cut detection method is suggested in the study and it's based on the speed, acceleration and road gradient data from GPS sensor. It detects fuel-cut driving mode by comparing calculated acceleration and realtime acceleration value. The one is estimated with driving resistance in the condition of fuel-cut driving and the other is from GPS sensor. The detection accuracy is about 80% when the method is verified with road driving data. The result is estimated with 9,600 data set of vehicle speed, acceleration, fuel consumption and road gradient from test driving on the road of 12km during 16 minutes, and the road slope is rather high. It's easy to detect fuel-cut without injector signal obtained by connecting wire. The detection error is from the fact that the variation range of speed, acceleration and road gradient data, used for road resistance force, is larger than the value of fuel consumption data.
Kim, Kwang-Soo;Hwang, Mee-Sun;Choi, Eui-Hwan;Kim, Kwang-Won;Yoon, Young-Jooh
The korean journal of orthodontics
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v.30
no.1
s.78
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pp.53-66
/
2000
This study was performed to find out the effect of projection errors on cephalometric linear and angular measurements according to head rotation during taking lateral cephalometric radiographs. Seventeen skulls with permanent dentition and no gross asymmetry were obtained from the Department of Anatomy, Medical School, Chosun University. Total 527 x-ray films were taken with $1^{\circ}$ interval from the reference position($0^{\circ}$) to ${\pm}15^{\circ}$ around the vertical axis (Z axis) which is perpendicular to the midpoint of the line connecting the center of two ear rods in submento-vertex direction. Statistical analysis was performed by paired t-test if there were statistically significant differences between the mean of the reference position($0^{\circ}$) and that of each rotation angle. The following results were obtained. 1. The projection errors of angular measurements were smaller than those of linear measurements. 2. The projection errors of angular measurements including midline landmarks were smaller than those including bilateral landmarks. 3. The horizontal linear measurements were gradually decreased when the stroll was rotated toward the film, but slightly increased and then decreased when the skull was rotated toward the focal spot. However, the changes were smaller in focal direction. 4. The projection errors of horizontal linear measurements were larger than those of vertical linear measurements. 5. The projection errors of vertical linear measurements were increased with increased distance from the rotation axis to vertical measurements. It is concluded that the use of angular measurements rather than linear measurements is recommended to minimize the projection errors.
It is a hot issue to determine the spatial location and shape of tumor boundary in fractionated stereotactic radiotherapy (FSRT). We could get consecutive transaxial plane images from the phantom (paraffin) and 4 patients with brain tumor using helical computed tomography(HCT). K-means classification algorithm was adjusted to change raw data pixel value in CT images into classified average pixel value. The classified images consists of 5 regions that ate tumor region (TR), normal region (NR), combination region (CR), uncommitted region (UR) and artifact region (AR). The major concern was how to separate the normal region from tumor region in the combination area. Relative average deviation analysis was adjusted to alter average pixel values of 5 regions into 2 regions of normal and tumor region to define maximum point among average deviation pixel values. And then we drawn gross tumor volume (GTV) boundary by connecting maximum points in images using semi-automatic contour method by IDL(Interactive Data Language) program. The error limit of the ROI boundary in homogeneous phantom is estimated within ${\pm}1%$. In case of 4 patients, we could confirm that the tumor lesions described by physician and the lesions described automatically by the K-mean classification algorithm and relative average deviation analyses were similar. These methods can make uncertain boundary between normal and tumor region into clear boundary. Therefore it will be useful in the CT images-based treatment planning especially to use above procedure apply prescribed method when CT images intermittently fail to visualize tumor volume comparing to MRI images.
The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.
In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (108 or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 108. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.3A
/
pp.297-307
/
2010
Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.
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