• Journal of Gastric Cancer
• /
• v.14 no.4
• /
• pp.259-265
• /
• 2014

Purpose: Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. Materials and Methods: Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carlo Markov Chain methods, were applied to the data of cancer patients referred to the cancer institute at Imam Khomeini Hospital in Tehran in 2003 to 2008. The data included demographic variables, survival times, and censored variable of 471 patients with gastric cancer. After using imputation methods to account for missing covariate data, the data were analyzed using a Cox regression model and the results were compared. Results: The mean patient survival time after diagnosis was $49.1{\pm}4.4$ months. In the complete case analysis, which used information from 100 of the 471 patients, very wide and uninformative confidence intervals were obtained for the chemotherapy and surgery hazard ratios (HRs). However, after imputation, the maximum confidence interval widths for the chemotherapy and surgery HRs were 8.470 and 0.806, respectively. The minimum width corresponded with MI. Furthermore, the minimum Bayesian and Akaike information criteria values correlated with MI (-821.236 and -827.866, respectively). Conclusions: Missing value imputation increased the estimate precision and accuracy. In addition, MI yielded better results when compared with the expectation maximization algorithm and regression simple imputation methods.

• Journal of the Institute of Convergence Signal Processing
• /
• v.11 no.4
• /
• pp.345-353
• /
• 2010

A general solution in global self-position location of robot is to generate multiple hypothesis in self-position of robot, which is to look for the most positive self-position by evaluating each hypothesis based on features of observed landmark. Markov Localization(ML) or Monte Carlo Localization(MCL) to be the existing typical method is to evaluate all pairs of landmark features and generated hypotheses, it can be said to be an optimal method in sufficiently calculating resources. But calculating quantities was proportional to the number of pairs to evaluate in general, so calculating quantities was piled up in wide environments in the presence of multiple pairs if using these methods. First of all, the positive and promising pairs is located and evaluated to solve this problem in this paper, and the newly locating method to make effective use of calculating time is proposed. As the basic method, it is used both RANSAC(RANdom SAmple Consensus) algorithm and preemption scheme to be efficiency method of RANSAC algorithm. The calculating quantity on each observation of robot can be suppressed below a certain values in the proposed method, and the high location performance can be determined by an experimental on verification.

• Journal of Radiation Industry
• /
• v.5 no.4
• /
• pp.325-330
• /
• 2011

To predict the details of flow in industrial process unit, single photon emission computed tomography (SPECT) is a promising technique. Recently, industrial SPECT based on medical system has developed by researchers of the Korea Atomic Energy Research Institute (KAERI) and Hanyang University. In the present study, to confirm the effect of the number of detectors on image quality, and determine the optimal number of detectors in industrial SPECT, industrial SPECT system with various geometries were evaluated by the Monte Carlo simulation. CsI(Tl) detectors ($12mm{\times}12mm{\times}20mm$) with collimators (the geometric resolution of collimator $R_g$ was 4 cm at the center of the 30 cm diameter cylindrical vessel object) were modeled in a hexagonal array, and the point sources of $^{99m}Tc$, $^{68}Ga$, and $^{137}Cs$ were simulated at the center of the cylindrical vessel object using the MCNPX code. Then, the reconstruction images of each geometry were reconstructed using the expectation maximization (EM) algorithm. In this study, the reciprocity theorem was used to improve computation time required for system matrix of the EM algorithm. The result shows that the resolution of the reconstructed image was significantly improved by increasing the number of detectors in industrial SPECT system and more than 60 detectors will be required for the resolution of the reconstructed image.

• Smart Structures and Systems
• /
• v.24 no.5
• /
• pp.631-639
• /
• 2019

Finite element analysis is one of the important methods to study the structural performance. Due to the simplification, discretization and error of structural parameters, numerical model errors always exist. Besides, structural characteristics may also change because of material aging, structural damage, etc., making the initial finite element model cannot simulate the operational response of the structure accurately. Based on Bayesian methods, the initial model can be updated to obtain a more accurate numerical model. This paper presents the work on the field test, modal identification and model updating of a Chinese reinforced concrete pagoda. Based on the ambient vibration test, the acceleration response of the structure under operational environment was collected. The first six translational modes of the structure were identified by the enhanced frequency domain decomposition method. The initial finite element model of the pagoda was established, and the elastic modulus of columns, beams and slabs were selected as model parameters to be updated. Assuming the error between the measured mode and the calculated one follows a Gaussian distribution, the posterior probability density function (PDF) of the parameter to be updated is obtained and the uncertainty is quantitatively evaluated based on the Bayesian statistical theory and the Metropolis-Hastings algorithm, and then the optimal values of model parameters can be obtained. The results show that the difference between the calculated frequency of the finite element model and the measured one is reduced, and the modal correlation of the mode shape is improved. The updated numerical model can be used to evaluate the safety of the structure as a benchmark model for structural health monitoring (SHM).

• Korean Journal of Artificial Intelligence
• /
• v.9 no.1
• /
• pp.1-7
• /
• 2021

In this paper, We focused the issue of creating a socially problematic nurse schedule. The nurse schedule should be prepared in consideration of three shifts, appropriate placement of experienced workers, the fairness of work assignment, and legal work standards. Because of the complex structure of the nurse schedule, which must reflect various requirements, in most hospitals, the nurse in charge writes it by hand with a lot of time and effort. This study attempted to automatically create an optimized nurse schedule based on legal labor standards and fairness. We developed an I/O Q-Learning algorithm-based model based on Python and Web Application for automatic nurse schedule. The model was trained to converge to 100 by creating an Fairness Indicator Score(FIS) that considers Labor Standards Act, Work equity, Work preference. Manual nurse schedules and this model are compared with FIS. This model showed a higher work equity index of 13.31 points, work preference index of 1.52 points, and FIS of 16.38 points. This study was able to automatically generate nurse schedule based on reinforcement Learning. In addition, as a result of creating the nurse schedule of E hospital using this model, it was possible to reduce the time required from 88 hours to 3 hours. If additional supplementation of FIS and reinforcement Learning techniques such as DQN, CNN, Monte Carlo Simulation and AlphaZero additionally utilize a more an optimized model can be developed.

• Journal of Convergence for Information Technology
• /
• v.11 no.12
• /
• pp.14-21
• /
• 2021

In this paper, it is shown how the performance of the monopulse algorithm in the presence of an additive noise can be obtained analytically. In the previous study, analytic performance analysis based on the first-order Taylor series and the second-order Taylor series has been conducted. By adopting the third-order Taylor series, it is shown that the analytic performance based on the third-order Taylor series can be made closer to the performance of the original monopulse algorithm than the analytic performance based on the first-order Taylor series and the second-order Taylor series. The analytic MSE based on the third-order Taylor approximation reduces the analytic MSE error based on the second-order Taylor approximation by 89.5%. It also shows faster results in all cases than the Monte Carlo-based MSE. Through this study, it is possible to explicitly analyze the angle estimation ability of monopulse radar in an environment where noise jamming is applied.

• Nuclear Engineering and Technology
• /
• v.55 no.2
• /
• pp.681-689
• /
• 2023

Purpose: Muons are characterized by a strong penetrating ability and can travel through thousands of meters of rock, making them ideal to image large volumes and substances typically impenetrable to, for example, electrons and photons. The feasibility of 3D image reconstruction and material identification based on a cosmic ray muons tomography (MT) system with triangular bar plastic scintillator detectors has been verified in this paper. Our prototype shows potential application value and the authors wish to apply this prototype system to 3D imaging. In addition, an MT experiment with the same detector system is also in progress. Methods: A simulation based on GEANT4 was developed to study cosmic ray muons' physical processes and motion trails. The yield and transportation of optical photons scintillated in each triangular bar of the detector system were reproduced. An image reconstruction algorithm and correction method based on muon scattering, which differs from the conventional PoCA algorithm, has been developed based on simulation data and verified by experimental data. Results: According to the simulation result, the detector system's position resolution is below 1 ~ mm in simulation and 2 mm in the experiment. A relatively legible 3D image of lead bricks in size of 20 cm × 5 cm × 10 cm used our inversion algorithm can be presented below 1× 10⁴ effective events, which takes 16 h of acquisition time experimentally. Conclusion: The proposed method is a potential candidate to monitor the cosmic ray MT accurately. Monte Carlo simulations have been performed to discuss the application of the detector and the simulation results have indicated that the detector can be used in cosmic ray MT. The cosmic ray MT experiment is currently underway. Furthermore, the proposal also has the potential to scan the earth, buildings, and other structures of interest including for instance computerized imaging in an archaeological framework.

• Journal of Radiation Protection and Research
• /
• v.29 no.3
• /
• pp.179-186
• /
• 2004

A single-dosimeter worn on the anterior surface of body of a worker was found to provide significant underestimation of dose to the worker when radiation comes from behind of the human body. Recently, several researchers suggested that this kind of underestimation can be corrected to a certain extent by using an extra dosimeter on the back. But this multiple dosimetry also has the disadvantages like overestimation lowering work efficiency or cost burden. In this study, a single dosimeter introducing asymmetric filters enabled to identify PA exposure was designed by monte-carlo simulation and experiments and its dose evaluation algorithm for AP-PA mixed radiation field was established. This algorithm was applicable to penetrating radiation which had the effective energy more than 100 keV. Besides, the dosimeter and algorithm in this study were possible to be applied to near PA exposure.

• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.36D no.3
• /
• pp.48-58
• /
• 1999

In this paper, a new parallel computation method, which fully utilize the parallel processors both in mesh generation and FEM calculation for 2D/3D process simulation, is presented. High performance parallel FEM and parallel linear algebra solving technique was showed that excessive computational requirement of memory size and CPU time for the three-dimensional simulation could be treated successively. Our parallelized numerical solver successfully interpreted the transient enhanced diffusion (TED) phenomena of dopant diffusion and irregular shape of R-LOCOS within 15 minutes. Monte Carlo technique requires excessive computational requirement of CPU time. Therefore high performance parallel solving technique were employed to our cascade sputter simulation. The simulation results of Our sputter simulator allowed the calculation time of 520 sec and speedup of 25 using 30 processors. We found the optimized number of ion injection of our MC sputter simulation is 30,000.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.108-116
• /
• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).