• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4226-4230
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• 2022

The Korea Atomic Energy Research Institute (KAERI) has designed a Hybrid-Low Power Research Reactor (H-LPRR) which can be used for critical assembly and conventional research reactor as well. It is an open tank-in-pool type research reactor (Thermal Power: 50 kW_th) of which the most important applications are Neutron Activation Analysis (NAA), Radioisotope (RI) production, education and training. There are eight irradiation holes on the edge of the reactor core: IR (6 holes for RI production) and NA (2 holes for NAA) holes. In order to quantify the elemental concentration in target samples through the Instrumental Neutron Activation Analysis (INAA), it is necessary to measure neutron spectrum parameters such as thermal neutron flux, the deviation from the ideal 1/E epithermal neutron flux distribution (α), and the thermal-to-epithermal neutron flux ratio (f) for the irradiation holes. In this study, the MCNP6.1 code and FORTRAN 90 language are applied to determine the parameters for the two irradiation holes (NA-SW and NA-NW) in H-LPRR, and in particular its α and f parameters are compared to values of other research reactors. The results confirmed that the neutron irradiation holes in H-LPRR are designed to be sufficiently applied to neutron activation analysis, and its performance is comparable to that of foreign research reactors including the TRIGA MARK II.

• PNF and Movement
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• v.22 no.1
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• pp.91-99
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• 2024

Purpose: Backward walking has shown positive effects on gait recovery in rehabilitation patients. It is increasingly used as an aerobic training method in rehabilitation populations, inducing more sensory and motor stimulation than forward walking. Therefore, the purpose of this study is to investigate the effects of visual stimulation during backward walking. Methods: Twenty-seven healthy adults with a visual acuity of 0.8 or higher participated in the study. To compare the effects of visual stimulation during various walking conditions among healthy individuals, the participants randomly selected cards numbered one to six and walked a distance of 10 meters. Walking ability was measured using Optogait. Results: Statistically significant differences were observed in speed, stride, and percentages of single support and contact phase during backward walking. Within eyes-closed conditions during backward walking, significant differences were found in percentages of single support, terminal stance, and contact phase. Moreover, the percentage of terminal swing significantly differed during backward walking with head turn conditions. Conclusion: Gait parameters such as speed, stride, and percentages of single support and contact phase were higher during backward walking than forward walking. These results indicate that backward walking involves multiple sensory systems and varying conditions.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.E2
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• pp.63-73
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• 2008

In this study, neural network models (NNMs) were examined as alternatives to dispersion models in predicting the short-term $SO_2$ concentrations in a coastal area because the performances of dispersion models in coastal areas have been found to be unsatisfactory. The NNMs were constructed for various combinations of averaging time and prediction time in advance by using the historical data of meteorological parameters and $SO_2$ concentrations in 2002 in the coastal area of Boryeung, Korea. The NNMs were able to make much more accurate predictions of 1 hr $SO_2$ concentrations at ground level in the morning in coastal area than the atmospheric dispersion models such as fumigation models, ADMS3 and ISCST3 for identical conditions of atmospheric stability, area, and weather. Even when predictions of 24-h $SO_2$ concentrations were made 24 hours in advance, the predictions and measurements were in good accordance(correlation coefficient=0.65 for n=216). This accordance level could be improved by appropriate expansion of training parameters. Thus it may be concluded that the NNMs can be successfully used to predict short-term ground level concentrations averaged over time less than 24 hours even in complex terrain. The prediction performance of ANN models tends to improve as the prediction lagging time approaches the concentration averaging time, but to become worse as the lagging time departs from the averaging time.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.372-377
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• 2007

For more than 2,500 years, surgical teaching has been based on the so called "see one, do one, teach one" paradigm, in which the surgical trainee learns by operating on patients under close supervision of peers and superiors. However, higher demands on the quality of patient care and rising malpractice costs have made it increasingly risky to train on patients. Minimally invasive surgery, in particular, has made it more difficult for an instructor to demonstrate the required manual skills. It has been recognized that, similar to flight simulators for pilots, virtual reality (VR) based surgical simulators promise a safer and more comprehensive way to train manual skills of medical personnel in general and surgeons in particular. One of the major challenges in the development of VR-based surgical trainers is the real-time and realistic simulation of interactions between surgical instruments and biological tissues. It involves multi-disciplinary research areas including soft tissue mechanical behavior, tool-tissue contact mechanics, computer haptics, computer graphics and robotics integrated into VR-based training systems. The research described in this paper addresses the problem of characterizing soft tissue properties for medical virtual environments. A system to measure in vivo mechanical properties of soft tissues was designed, and eleven sets of animal experiments were performed to measure in vivo and in vitro biomechanical properties of porcine intra-abdominal organs. Viscoelastic tissue parameters were then extracted by matching finite element model predictions with the empirical data. Finally, the tissue parameters were combined with geometric organ models segmented from the Visible Human Dataset and integrated into a minimally invasive surgical simulation system consisting of haptic interface devices and a graphic display.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.11-18
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• 2012

Debris flow deposition model is a model to predict affected areas by debris flow and random walk model (RWM) was used to build the model. Although the model was proved to be effective in the prediction of affected areas, the model has several free parameters decided experimentally. There are several well-known methods to estimate parameters, however, they cannot be applied directly to the debris flow problem due to the small size of training data. In this paper, a modified neural network, called pseudo sample neural network (PSNN), was proposed to overcome the sample size problem. In the training phase, PSNN uses pseudo samples, which are generated using the existing samples. The pseudo samples smooth the solution space and reduce the probability of falling into a local optimum. As a result, PSNN can estimate parameter more robustly than traditional neural networks do. All of these can be proved through the experiments using artificial and real data sets.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Interdisciplinary Bio Central
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• v.1 no.2
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• pp.8.1-8.6
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• 2009

Introduction: It is a challenge to design a protein score function which stabilizes the native structures of many proteins simultaneously. The coarse-grained description of proteins to construct the pairwise-contact score function usually ignores the backbone directionality of protein structures. We propose a new two-body score function which stabilizes all native states of 1,006 proteins simultaneously. This two-body score function differs from the usual pairwise-contact functions in that it considers two adjacent amino acids at two ends of each peptide bond with the backbone directionality from the N-terminal to the C-terminal. The score is a corresponding propensity for a directional alignment of two adjacent amino acids with their local environments. Results and Discussion: We show that the construction of a directional adjacency-score function was achieved using 1,006 training proteins with the sequence homology less than 30%, which include all representatives of different protein classes. After parameterizing the local environments of amino acids into 9 categories depending on three secondary structures and three kinds of hydrophobicity of amino acids, the 32,400 adjacency-scores of amino acids could be determined by the perceptron learning and the protein threading. These could stabilize simultaneously all native folds of 1,006 training proteins. When these parameters are tested on the new distinct 382 proteins with the sequence homology less than 90%, 371 (97.1%) proteins could recognize their native folds. We also showed using these parameters that the retro sequence of the SH3 domain, the B domain of Staphylococcal protein A, and the B1 domain of Streptococcal protein G could not be stabilized to fold, which agrees with the experimental evidence.

• Korean Journal of Clinical Laboratory Science
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• v.50 no.4
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• pp.484-491
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• 2018

Primer $Sj{\ddot{o}}gren's$ Syndrome (pSS) is an autoimmune/inflammatory illness. The platelet indices (PIs) indicate the inflammatory response and activity/severity of many diseases. A vitamin D deficiency is accompanied by the increased tendency of autoimmune diseases. This study investigated whether the vitamin D levels are related to the altered platelet indices in pSS. A total of 261 individuals were included in this analytical cross-sectional study. The laboratory data of pSS patients were evaluated and the relationship between the PIs and vitamin D status was examined. According to these findings, in patients with pSS, the vitamin D levels were lower than the healthy control group (P<0.05). The vitamin D levels were negatively associated with PDW (P=0.012), but positively correlated with PCT (P<0.001). The cut-off point was obtained with receiver operating characteristics (ROC) curves for PDW: 12.53 (AUC 0.921, sensitivity 90%, specificity 85%), for PCT; 0.29 (AUC 0.660, sensitivity 68%, specificity 55%). In multivariate linear regression analysis, the most significant parameters for the effects of PDW are the following: vitamin D (${\beta}=-0.373$; t=-2.626; sig.=0.013) and plateletcrit (${\beta}=-0.308$; t=-2.13; sig.=0.040). A vitamin D deficiency may be accompanied by changes in PIs in pSS. A higher PDW and lower PCT supports the underlying inflammation, which may be vitamin D related useful parameters to consider in approaching to pSS.

• Journal of Korean Neurosurgical Society
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• v.62 no.5
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• pp.577-585
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• 2019

Objective : Comparing the effects of magnetically controlled growing rod (MCGR) and traditional growing rod (TGR) techniques on the sagittal plane in the treatment of early-onset scoliosis (EOS). Methods : Twelve patients were operated using dual MCGR technique in one center, while 15 patients were operated using dual TGR technique for EOS in another center. Patients' demographic characteristics, complications and radiological measurements such as cobb angle, thoracic kyphosis, lumbar lordosis, T1-S1 range (mm), proximal junctional angle, distal junctional angle, sagittal balance, coronal balance, pelvic incidence, sacral slope and pelvic tilt were assessed and compared in preoperative, postoperative and last follow-up period. Results : Age and sex distributions were similar in both groups. The mean number of lengthening in the MCGR group was 12 (8-15) and 4.8 (3-7) in the TGR group. Two techniques were shown to be effective in controlling the curvature and in the increase of T1-S1 distance. In TGR group, four patients had rod fractures, six patients had screw pull-out and four patients had an infection, whereas three patients had screw pull-out and one patient had infection complications in the MCGR group. Conclusion : There was no significant difference between the two groups in terms of cobb angle, coronal and sagittal balance and sagittal pelvic parameters. MCGR can cause hypokyphosis and proximal junctional kyphosis in a minimum 2-year follow-up period. The implant-related complications were less in the MCGR group. However, larger case groups and longer follow-up periods are required for the better understanding of the superiority of one method on other in terms of complications.

• Steel and Composite Structures
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• v.39 no.5
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• pp.615-630
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• 2021

The main purpose of the present work was to study the dynamic instability of a three-layered, thick composite sandwich beam with the functionally graded (FG) flexible core subjected to an axial compressive follower force. Flutter instability of a sandwich cantilever beam was analyzed using the high-order theory of sandwich beams, for the first time. The governing equations in general for sandwich beams with an FG core were extracted and could be used for all types of sandwich beams with any types of face sheets and cores. A polynomial function is considered for the vertical distribution of the displacement field in the core layer along the thickness, based on the results of the first Frosting's higher order model. The governing partial differential equations and the equations of boundary conditions of the dynamic system are derived using Hamilton's principle. By applying the boundary conditions and numerical solution methods of squares quadrature, the beam flutter phenomenon is studied. In addition, the effects of different geometrical and material parameters on the flutter threshold were investigated. The results showed that the responses of the dynamic instability of the system were influenced by the follower force, the coefficients of FGs and the geometrical parameters like the core thickness. Comparison of the present results with the published results in the literature for the special case confirmed the accuracy of the proposed theory. The results showed that the follower force of the flutter phenomenon threshold for long beams tends to the corresponding results in the Timoshenko beam.