• The Journal of Korean Physical Therapy
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• 제14권2호
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• pp.65-73
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• 2002

OBJECTIVE: This study was Far infrared(FIR) irradiating to a rat collagen-induced autoimmune arthritis and observed nitric oxide level of spine. METHODS: Type II collagen(CII) in adjuvant was injected into rats on day 0. The results showed that rats injected with CII plus adjuvant had signs of autoimmune arthritis on day 14. Thereafter, Far infrared(FIR) irradiation was begun on day 15. The rats were irradiated FIR twice per day for 20 min each time. RESULTS: Seven days later(Day 22), the level of NO at FIR irradiated group(FRG; Arth+FIR) was decreased more than FIR-non irradiated group(FNRG; Arth). Twenty-one days later(Day 36), the level of NO at FRG was more closed to the control group's NO level than the FNRG. CONCLUSION: These results indicated that Far infrared irradiating appears to reduce the nitric oxide level at a rat model of autoimmune arthritis induced.

• 지역사회간호학회지
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• 제32권3호
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• pp.344-355
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• 2021

Purpose: With low birth rates and aging population problems in Korea, the number of foreign workers grows rapidly. The purpose of this study was to identify factors influencing physical activity of foreign workers based on a Health Promotion Model by examining relationships between acculturation, perceived benefits, perceived barriers, exercise self-efficacy, activity-related affect, social support, and physical activity. Methods: The participants were foreign workers aged 18 to 60 who were employed at eight shipyards. A questionnaire was distributed to 216 participants. Results: As a result of the multivariate ordinal logistic regression analysis, factors affecting physical activity of foreign workers were perceived benefits (B=.65, 95% CI=0.08~1.22), exercise self-efficacy (B=.16, 95% CI=0.05~0.26), integration (B=.41 95% CI=0.14~0.69), and social support for physical activity (B=.48, 95% CI=0.12~0.83). The total explanatory power was 17.7% (x²=41.95, p<.001). Conclusion: Based on these results, there is a need to develop a customized program to increase physical activities of foreign workers by enhancing integration, perceived benefits, exercise self-efficacy and social support.

• 한국해양공학회지
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• 제23권2호
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• pp.28-36
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• 2009

Many researches have been done to define the physical parameters for the wave generation and transformation over a coastal region. However, most of these have been limited to the application of particular conditions, as they are generally too empirical. To yield more reasonable wave estimation using a spectral wave model, it is important to understand how they work for the wave estimation. This study involved a comprehensive sensitivity test against the spectral resolution and the physical source/sink terms of the spectral wave model using SWAN and TOMAWAC, which have the same physical background with several different empirical/theoretical formulations. The tests were conducted for the East Anglian coast, UK, which is characterized by a complex bathymetry due to several shoals and offshore sandbanks. For the quantitative and qualitative evaluation of the models' performance with different input conditions, the wave elements and spectrums predicted at representative sites the East Anglia coast were compared/analyzed. The spectral resolution had no significant effect on the model results, but the lowest resolution on the frequency and direction induced underestimations of the wave height and period. The bottom friction and depth-induced breaking terms produced relatively high variations in the wave prediction, depending on which formulation was applied. The terms for the quadruplet and whitecapping had little effect on the wave estimation, whereas the triads tended to predict shorter and higher waves by energy transferring to higher frequencies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• 한국IT서비스학회지
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• 제7권4호
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• pp.247-268
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• 2008

This study aims to develop an integration performance measurement model for each stage of information systems integration. In order to achieve the purpose of the research, first of all, the concepts of IS integration or consolidation are analyzed through theoretical and practical reviews. Also, a number of important studies of domestic and overseas cases about the stage models of IS integration or consolidation are critically reviewed. Second, we proposed three step stage model of is integration, Physical Integration stage, Application Integration stage, Service Integration stage, and Also proposed the performance measurement model for each stage of information systems integration. Third, especially in case of performance indicators and performance measurement methodology for physical integration stage are illustratively proposed, based upon the case of NCIA (National Computing Integration Agency) in Korea. This study provides the theoretical basis for reasonably deriving the stage model and performance measurement model for each stage of Information Systems Integration, and they are validating through investigating domestic and foreign practices. The results of this study are very likely to contribute to presenting the practical guideline for desirably implementing is integration or IS consolidation.

• Wind and Structures
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• 제17권5호
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• pp.495-513
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• 2013

Thin, high-strength steel roof cladding is widely used in residential and industrial low-rise buildings and is susceptible to failure during severe wind storms such as cyclones. Current cladding design is heavily reliant on experimental testing for the determination of roof cladding performance. Further study is necessary to evolve current design standards, and numerical modelling of roof cladding can provide an efficient and cost effective means of studying the response of cladding in great detail. This paper details the development of a numerical model that can simulate the static response of corrugated roof cladding. Finite element analysis (FEA) was utilised to determine the response of corrugated cladding subject to a static wind pressure, which included the anisotropic material properties and strain-hardening characteristics of the thin steel roof cladding. The model was then validated by comparing the numerical data with corresponding experimental test results. Based on this comparison, the model was found to successfully predict the fastener reaction, deflection and the characteristics in deformed shape of the cladding. The validated numerical model was then used to predict the response of the cladding subject to a design cyclone pressure trace, excluding fatigue effects, to demonstrate the potential of the model to investigate more complicated loading circumstances.

• Nuclear Engineering and Technology
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• 제55권9호
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• pp.3367-3382
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• 2023

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian computational fluid dynamics method that has been widely used in the analysis of physical phenomena characterized by large deformation or multi-phase flow analysis, including free surface. Despite the recent implementation of eddy-viscosity models in SPH methodology, sophisticated turbulent analysis using Lagrangian methodology has been limited due to the lack of computational performance and numerical consistency. In this study, we implement the standard and dynamic Smagorinsky model and dynamic Vreman model as sub-particle scale models based on a weakly compressible SPH solver. The large eddy simulation method is numerically identical to the spatial discretization method of smoothed particle dynamics, enabling the intuitive implementation of the turbulence model. Furthermore, there is no additional filtering process required for physical variables since the sub-grid scale filtering is inherently processed in the kernel interpolation. We simulate lid-driven flow under transition and turbulent conditions as a benchmark. The simulation results show that the dynamic Vreman model produces consistent results with experimental and numerical research regarding Reynolds averaged physical quantities and flow structure. Spectral analysis also confirms that it is possible to analyze turbulent eddies with a smaller length scale using the dynamic Vreman model with the same particle size.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 춘계학술대회 논문집
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• pp.217-224
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• 2004

개방해역에서의 폭풍고조의 계산은 특히 해안역의 계획 및 건설 작업 분야에서 의미있는 것이다. 본 연구에서 태풍으로 인한 수위의 변화예측은 물리모델에서나 실제현장에서 다루기가 매우 어렵기 때문에 수치모델에 주로 근거를 두었다. 폭풍고조에 대한 단순준이차원 수치모델을 다루었다. 모델배경에서 여러 가지 가정, 유효범위, 적용성을 이해하기 위하여 태풍과 폭풍의 발생과정을 좌우하는 물리적 인자들에 대하여 논하였다. 또한 수학적 관점 뿐만아니라 물리적인 관점에서 모델의 주요특성을 나타내기 위해 모델의 수립과정에 일반적으로 취한 가정과 함께 지배방정식을 따랐다. 본 논문에서 기술한 모델과 일치하는 방정식은 지배방정식을 축약시킨 것으로 이에 따른 수치기법을 제시하였다. 최종적으로 한국 남해안의 마산항에서 폭풍고조의 문제에 위에서 기술한 모델을 적용하여 천문조, 초기수면, 대기압에 따른 수위상승의 효과를 고려하였다. 아울러 해안도시역에서의 침수원인을 분석하고, 침수방지를 위한 합리적인 제안을 제시하였다.

• PNF and Movement
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• 제18권3호
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• pp.305-313
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• 2020

Purpose: The aim of this study was to investigate the relationship between a functional evaluation model and the Fugl-Meyer assessment (FMA) scale in evaluating the upper extremities of stroke patients Methods: Thirty-eight stroke patients were evaluated using the FMA and performed reaching and grasping motions using a three-dimensional motion analysis (Qquas 1 series, Qualisys AB, Sweden). The participants sat on a chair with a backrest. The position of the cup was located at a distance of 80% to the front arm length. The markers were attached to the sternum, acromion, elbow lateral epicondyle, ulnar styloid process, three metacarpal heads, and the distal phalanges of the thumb and index finger. The variables of the correlation between the functional evaluation model and the FMA scale were analyzed. Multiple regression (stepwise) was used to investigate the effect of the kinematic variables. Results: A significant negative correlation was found between the movement time (p < 0.05), movement unit (p < 0.05), and trunk displacement values (p < 0.05) in the FMA total scores, while a positive correlation was found between the peak velocity (p < 0.05) and maximum grip aperture values (p < 0.05). As a result of the multiple regression analysis, the most significant factor was the movement unit, followed by the general movement assessment and trunk displacement. The explained FMA total score value was 62%. Conclusion: This study presents a new functional evaluation model for assessing the reaching and grasping ability of stroke patients. The factors of the proposed functional evaluation model showed significant correlations with the FMA scale scores and confirmed that the new functional evaluation model explained the FMA by 67%. This suggests a new functional evaluation model for reaching and grasping stroke patients.

• 천문학회보
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• 제46권1호
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• pp.42.1-42.1
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• 2021

In this study, we present a visual explanation of a deep learning solar flare forecast model and its relationship to physical parameters of solar active regions (ARs). For this, we use full-disk magnetograms at 00:00 UT from the Solar and Heliospheric Observatory/Michelson Doppler Imager and the Solar Dynamics Observatory/Helioseismic and Magnetic Imager, physical parameters from the Space-weather HMI Active Region Patch (SHARP), and Geostationary Operational Environmental Satellite X-ray flare data. Our deep learning flare forecast model based on the Convolutional Neural Network (CNN) predicts "Yes" or "No" for the daily occurrence of C-, M-, and X-class flares. We interpret the model using two CNN attribution methods (guided backpropagation and Gradient-weighted Class Activation Mapping [Grad-CAM]) that provide quantitative information on explaining the model. We find that our deep learning flare forecasting model is intimately related to AR physical properties that have also been distinguished in previous studies as holding significant predictive ability. Major results of this study are as follows. First, we successfully apply our deep learning models to the forecast of daily solar flare occurrence with TSS = 0.65, without any preprocessing to extract features from data. Second, using the attribution methods, we find that the polarity inversion line is an important feature for the deep learning flare forecasting model. Third, the ARs with high Grad-CAM values produce more flares than those with low Grad-CAM values. Fourth, nine SHARP parameters such as total unsigned vertical current, total unsigned current helicity, total unsigned flux, and total photospheric magnetic free energy density are well correlated with Grad-CAM values.