• Journal of the Korean Physical Society
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• 제73권11호
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• pp.1764-1773
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• 2018

A-PET is a quad-head PET scanner developed for use in small-animal imaging. The dimensions of its volumetric field of view (FOV) are $46.1{\times}46.1{\times}46.1mm^3$ and the gap between the detector modules has been minimized in order to provide a highly sensitive system. However, such a small FOV together with the quad-head geometry causes image quality degradation. The main factor related to image degradation for the quad-head PET is the mispositioning of events caused by the penetration effect in the detector. In this paper, we propose a precise method for modelling the system at the high spatial resolution of the A-PET using a LOR (line of response) based ML-EM (maximum likelihood expectation maximization) that allows for penetration effects. The proposed system model provides the detection probability of every possible ray-path via crystal sampling methods. For the ray-path sampling, the sub-LORs are defined by connecting the sampling points of the crystal pair. We incorporate the detection probability of each sub-LOR into the model by calculating the penetration effect. For comparison, we used a standard LOR-based model and a Monte Carlo-based modeling approach, and evaluated the reconstructed images using both the National Electrical Manufacturers Association NU 4-2008 standards and the Geant4 Application for Tomographic Emission simulation toolkit (GATE). An average full width at half maximum (FWHM) at different locations of 1.77 mm and 1.79 mm are obtained using the proposed system model and standard LOR system model, which does not include penetration effects, respectively. The standard deviation of the uniform region in the NEMA image quality phantom is 2.14% for the proposed method and 14.3% for the LOR system model, indicating that the proposed model out-performs the standard LOR-based model.

• 응용통계연구
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• 제33권6호
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• pp.723-738
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• 2020

본 논문에서는 추세-정상시계열과 차분-정상시계열을 판별하는 방법에 대해 연구한다. 두 시계열 모형은 시계열적 특징, 충격의 지속성 여부, 시계열을 정상화시키는 방법 등이 모두 다르므로, 어떤 모형을 선택하냐에 따라 분석 방법이나 해석에 차이가 발생한다. 따라서 시계열 자료를 분석할 때 추세-정상성과 차분-정상성을 판별하는 것은 매우 중요한 일이다. 두 시계열을 구분하는 중요한 기준은 단위근의 존재 여부이므로, 단위근 검정 결과를 활용할 수 있다. 최근 연구 결과들을 살펴보면, 다양한 시계열 모형을 적합시킬 때 뿐만 아니라 비정상 자기회귀모형의 차분 차수를 결정할 때도 adaptive lasso와 같은 벌점화 추정방법을 도입, 사용하고 있다. 본 논문에서도 adaptive lasso를 이용하여 추세-정상시계열과 차분-정상시계열을 판별하는 방법을 제안, 연구를 진행하였다. 단위근 검정을 이용한 분류 방법과 adaptive lasso 추정량을 기초로 한 분류 방법에 대한 비교 모의실험을 수행하였고, 그 결과 추세-정상시계열이 참인 경우는 adaptive lasso 방법의 분류 정확도가 단위근 검정방법보다 좀 더 우세하며, 차분-정상시계열의 경우에는 반대로 정확도가 떨어지는 것을 확인할 수 있었다.

• Geomechanics and Engineering
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• 제30권2호
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• pp.187-199
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• 2022

Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• Current Optics and Photonics
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• 제6권5호
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• pp.489-496
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• 2022

Our previous study on monitoring cerebral oxygenation with a variation of isoflurane concentration in a rat model showed that near-infrared spectroscopy (NIRS) signals have potential as a new depth of anesthesia (DOA) index. However, that study obtained results from the brain in a completely invasive way, which is inappropriate for clinical application. Therefore, in this follow-up study, it was investigated whether the NIRS signals measured in a minimally invasive model including the skull and cerebrospinal fluid layer (CSFL) are similar to the previous study used as a gold standard. The experimental method was the same as the previous study, and only the subject model was different. We continuously collected NIRS signals before, during, and after isoflurane anesthesia. The isoflurane concentration started at 2.5% (v/v) and decreased to 1.0% by 0.5% every 5 min. The results showed a positive linear correlation between isoflurane concentration and ratio of reflectance intensity (RRI) increase, which is based on NIRS signals. This indicates that the quality of NIRS signals passed through the skull and CSFL in the minimally invasive model is as good as the signal obtained directly from the brain. Therefore, we believe that the results of this study can be easily applied to clinics as a potential indicator to monitor DOA.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2334-2340
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• 2021

Radioactive particle tracking (RPT) is a minimally invasive nuclear technique that tracks a radioactive particle inside a volume of interest by means of a mathematical location algorithm. During the past decades, many algorithms have been developed including ones based on artificial intelligence techniques. In this study, RPT technique is applied in a simulated test section that employs a simplified mixer filled with concrete, six scintillator detectors and a¹³⁷Cs radioactive particle emitting gamma rays of 662 keV. The test section was developed using MCNPX code, which is a mathematical code based on Monte Carlo simulation, and 3516 different radioactive particle positions (x,y,z) were simulated. Novelty of this paper is the use of a location algorithm based on a deep learning model, more specifically a 6-layers deep rectifier neural network (DRNN), in which hyperparameters were defined using a Bayesian optimization method. DRNN is a type of deep feedforward neural network that substitutes the usual sigmoid based activation functions, traditionally used in vanilla Multilayer Perceptron Networks, for rectified activation functions. Results show the great accuracy of the DRNN in a RPT tracking system. Root mean squared error for x, y and coordinates of the radioactive particle is, respectively, 0.03064, 0.02523 and 0.07653.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.258-265
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• 2021

High levels for noise and a loss of true signal make the quantitative interpretation of nuclear medicine (NM) images difficult. An application of profile optimization using a sigmoidal function in this study was used to acquire the NM images with high quality. And the images were acquired by using three kinds of reconstruction method using each same sinogram: a standard filtered back-projection (FBP), an iterative reconstruction (IR) technique, and the sigmoidal function profile optimization (SFPO). Comparison of image according to reconstruction method was performed to show a superiority of the SFPO for imaging. The images reconstructed by using the SFPO showed an average of 1.49 times and of 1.17 times better in contrast than the results obtained using the standard FBP and the IR technique, respectively. Higher signal to noise ratios were obtained as an average of 12.30 times and of 3.77 times than results obtained using the standard FBP and the IR technique, respectively. This study confirms that reconstruction with SFPO (vs FBP and vs IR) can lead to better lesion detectability and characterization with noise reduction. It can be developed for future reconstruction technique for the NM imaging.

• Nuclear Engineering and Technology
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• 제53권6호
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• pp.2000-2010
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• 2021

Mechanical moduli, such as Young's modulus (E), Bulks modulus (B), Shear modulus (S), longitudinal modulus (L), Poisson's ratio (σ) and micro Hardness (H) were theoretically calculated for (100-x)TeO₂+x MgO glasses, where x = 10, 20, 30, 40 and 45 mol%, based on the Makishima-Mackenzie model. The estimated results showed that the mechanical moduli and the microhardness of the glasses were improved with the increase of the MgO contents in the TM glasses, while Poisson's ratio decreased with the increase in MgO content. Moreover, the radiation shielding capacity was evaluated for the studied TM glasses. Thus, the linear attenuation coefficient (LAC), mass attenuation coefficient (MAC), transmission factor (TF) and half-value thickness (𝚫_0.5) were simulated for gamma photon energies between 0.344 and 1.406 MeV. The simulated results showed that glass TM10 with 10 mol % MgO possess the highest LAC and varied in the range between 0.259 and 0.711 cm^-1, while TM45 glass with 45 mol % MgO possess the lowest LAC and vary in the range between 0.223 and 0.587 cm^-1 at gamma photon energies between 0.344 and 1.406 MeV. Furthermore, the BXCOM program was applied to calculate the effective atomic number (Z_eff), equivalent atomic number (Z_eq) and buildup factors (EBF and EABF) of the glasses. The effective removal cross-section for the fast neutrons (ERCSFN, ∑_R) was also calculated theoretically. The received data depicts that the lowest ∑_R was achieved for TM10 glasses, where ∑_R = 0.0193 cm² g^-1, while TM45 possesses the highest ERCSFN where ∑_R = 0.0215 cm² g^-1.

• 한국인공지능학회지
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• 제9권1호
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• pp.1-7
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• 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 Radiation Protection and Research
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• 제46권2호
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• pp.58-65
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• 2021

Background: The evaluation of skyshine distribution, release of airborne radioactive nuclides, and soil activation and groundwater migration were required for radiological assessment of the impact on the environment surrounding In-Flight (IF)-system facility of the RAON (Rare isotope Accelerator complex for ON-line experiment) accelerator complex. Materials and Methods: Monte Carlo simulation by MCNPX code was used for evaluation of skyshine and activation analysis for air and soil. The concentration model was applied in the estimation of the groundwater migration of radionuclides in soil. Results and Discussion: The skyshine dose rates at 1 km from the facility were evaluated as 1.62 × 10^-3 μSv·hr^-1. The annual releases of ³H and ¹⁴C were calculated as 9.62 × 10^-5 mg and 1.19 × 10^-1 mg, respectively. The concentrations of ³H and ²²Na in drinking water were estimated as 1.22 × 10^-1 Bq·cm^-3 and 8.25 × 10^-3 Bq·cm^-3, respectively. Conclusion: Radiological assessment of environmental impact on the IF-facility of RAON was performed through evaluation of skyshine dose distribution, evaluation of annual emission of long-lived radionuclides in the air and estimation of soil activation and groundwater migration of radionuclides. As a result, much lower exposure than the limit value for the public, 1 mSv·yr^-1, is expected during operation of the IF-facility.