• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2625-2634
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• 2022

Discretization errors are extremely challenging conundrums of discrete ordinates calculations for radiation transport problems with void regions. In previous work, we have presented a multi-collision source method (MCS) to overcome discretization errors, but the efficiency needs to be improved. This paper proposes a goal-oriented algorithm for the MCS method to adaptively determine the partitioning of the geometry and dynamically change the angular quadrature in remaining iterations. The importance factor based on the adjoint transport calculation obtains the response function to get a problem-dependent, goal-oriented spatial decomposition. The difference in the scalar fluxes from one high-order quadrature set to a lower one provides the error estimation as a driving force behind the dynamic quadrature. The goal-oriented algorithm allows optimizing by using ray-tracing technology or high-order quadrature sets in the first few iterations and arranging the integration order of the remaining iterations from high to low. The algorithm has been implemented in the 3D transport code ARES and was tested on the Kobayashi benchmarks. The numerical results show a reduction in computation time on these problems for the same desired level of accuracy as compared to the standard ARES code, and it has clear advantages over the traditional MCS method in solving radiation transport problems with reflective boundary conditions.

• Steel and Composite Structures
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• v.42 no.3
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• pp.375-388
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• 2022

In this work, limit elastic speed analysis of functionally graded porous rotating disks has been reported. The work proposes an effective approach for modeling the mechanical properties of a porous functionally graded rotating disk. Four different types of porosity models namely: uniform, symmetric, inner maximum, and outer maximum distribution are considered. The approach used is the variational principle, and the solution has been achieved using Galerkin's error minimization theory. The study aims to investigate the effect of grading indices, aspect ratio, porosity volume fraction, and porosity types on limit angular speed for uniform and variable disk geometries of constant mass. To validate the current study, finite element analysis has been used, and there is good agreement between the two methods. The study yielded a decrease in limit speed as grading indices and aspect ratio increase. The porosity volume fraction is found to be more significant than the aspect ratio effect. The research demonstrates a range of operable speeds for porous and non-porous disk profiles that can be used in industries as design data. The results show a significant increase in limit speed for an exponential disk when compared to other disk profiles, and thus, the study demonstrates a range of FG-based structures for applications in industries that will not only save material (lightweight structures) but also improve overall performance.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.11
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• pp.43-51
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• 2021

A robust tracking controller design was developed for a rotary motion control system. The friction force versus the angular velocity was measured and modeled as a combination of linear and nonlinear components. By adding a model-based friction compensator to a nominal proportional-integral-derivative controller, it was possible to build a simulated control system model that agreed well with the experimental results. A zero-phase error tracking controller was selected as the feedforward tracking controller and implemented based on the estimated closed-loop transfer function. To provide robustness against external disturbances and modeling uncertainties, a disturbance observer was added in the position feedback loop. The performance improvement of the overall tracking controller structure was verified through simulations and experiments.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.427-435
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• 2023

This paper proposes a method of estimating the pose of a mobile robot by using a learning model. When estimating the pose of a mobile robot, wheel encoder and inertial measurement unit (IMU) data are generally utilized. However, depending on the condition of the ground surface, slip occurs due to interaction between the wheel and the floor. In this case, it is hard to predict pose accurately by using only encoder and IMU. Thus, in order to reduce pose error even in such conditions, this paper introduces a pose estimation method based on a learning model using data of the wheel encoder and IMU. As the learning model, long short-term memory (LSTM) network is adopted. The inputs to LSTM are velocity and acceleration data from the wheel encoder and IMU. Outputs from network are corrected linear and angular velocity. Estimated pose is calculated through numerically integrating output velocities. Dataset used as ground truth of learning model is collected in various ground conditions. Experimental results demonstrate that proposed learning model has higher accuracy of pose estimation than extended Kalman filter (EKF) and other learning models using the same data under various ground conditions.

• The korean journal of orthodontics
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• v.30 no.1 s.78
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• pp.53-66
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• 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.

• Imaging Science in Dentistry
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• v.50 no.1
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• pp.15-22
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• 2020

Purpose: This study was conducted to objectively and subjectively compare the accuracy and reliability of 2-dimensional(2D) photography and 3-dimensional(3D) soft tissue imaging. Materials and Methods: Facial images of 50 volunteers(25 males, 25 females) were captured with a Nikon D800 2D camera (Nikon Corporation, Tokyo, Japan), 3D stereophotogrammetry (SPG), and laser scanning (LS). All subjects were imaged in a relaxed, closed-mouth position with a normal smile. The 2D images were then exported to Mirror^® Software (Canfield Scientific, Inc, NJ, USA) and the 3D images into Proplan CMF^® software (version 2.1, Materialise HQ, Leuven, Belgium) for further evaluation. For an objective evaluation, 2 observers identified soft tissue landmarks and performed linear measurements on subjects' faces (direct measurements) and both linear and angular measurements on all images(indirect measurements). For a qualitative analysis, 10 dental observers and an expert in facial imaging (subjective gold standard) completed a questionnaire regarding facial characteristics. The reliability of the quantitative data was evaluated using intraclass correlation coefficients, whereas the Fleiss kappa was calculated for qualitative data. Results: Linear and angular measurements carried out on 2D and 3D images showed excellent inter-observer and intra-observer reliability. The 2D photographs displayed the highest combined total error for linear measurements. SPG performed better than LS, with borderline significance (P=0.052). The qualitative assessment showed no significant differences among the 2D and 3D imaging modalities. Conclusion: SPG was found to a reliable and accurate tool for the morphological evaluation of soft tissue in comparison to 2D imaging and laser scanning.

• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.361-370
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• 2004

The DSN(Deep Space Network) measurement model for interplanetary navigations which is essential for precise orbit determination has been developed. The DSN measurement model produces fictitious DSN observables such as range, doppler and angular data, containing the potential observational errors in geometric data obtained from orbit propagator. So the important part of this research is to model observational errors in DSN observation and to characterize the errors. The modeled observational errors include the range delay effect caused by troposphere, ionosphere, antenna offset, and angular refraction effect caused by troposphere. Non-modeled errors are justified as the parameters. All of these results from developed models show about $10\%$ errors compared to the JPL's reference results, that are within acceptable error range.

• Journal of Astronomy and Space Sciences
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• v.24 no.1
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• pp.69-78
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• 2007

The international EARTHSHINE mission is to measure 1% anomaly of the Earth global albedo and total solar irradiance using Amon-Ra instrument around Lagrange point 1. We developed a new ray truing based integrated end-to-end simulation tool that overcomes the shortcomings of the existing end-to-end performance simulation techniques. We then studied the in-orbit radiometric performance of the breadboard Anon-Ra visible channel optical system. The TSI variation and the Earth albedo anomaly, reported elsewhere, were used as the key input variables in the simulation. The output flux at the instrument focal plane confirms that the integrated ray tracing based end-to-end science simulation delivers the correct level of incident power to the Amon-Ra instrument well within the required measurement error budget of better than ${\pm}0.28%$. Using the global angular distribution model (ADM), the incident flux is then used to estimate the Earth global albedo and the TSI variation, confirming the validity of the primary science cases at the L1 halo orbit. These results imply that the integrated end-to-end ray tracing technique, reported here, can serve as an effective and powerful building block of the on-line science analysis tool in support of the international EARTHSHINE mission currently being developed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.19-29
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• 2003

This paper presents a novel hybrid classifier for face recognition with artificially generated virtual training samples. We utilize both the nearest neighbor approach in feature angle space and a connectionist model to obtain a synergy effect by combining the results of two heterogeneous classifiers. First, a classifier called the nearest feature angle (NFA), based on angular information, finds the most similar feature to the query from a given training set. Second, a classifier has been developed based on the recall of stored frontal projection of the query feature. It uses a frontal recall network (FRN) that finds the most similar frontal one among the stored frontal feature set. For FRN, we used an ensemble neural network consisting of multiple multiplayer perceptrons (MLPs), each of which is trained independently to enhance generalization capability. Further, both classifiers used the virtual training set generated adaptively, according to the spatial distribution of each person's training samples. Finally, the results of the two classifiers are combined to comprise the best matching class, and a corresponding similarit measure is used to make the final decision. The proposed classifier achieved an average classification rate of 96.33% against a large group of different test sets of images, and its average error rate is 61.5% that of the nearest feature line (NFL) method, and achieves a more robust classification performance.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.271-278
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• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.