• Computers and Concrete
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• 제24권1호
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• pp.51-61
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• 2019

Compressive ability is one of the most important mechanical properties of concrete material. The compressive failure process of concrete is pretty complex with internal tension, shear damage and friction between cracks. To simulate the complex fracture process of concrete at meso level, methodology for meso-structural analysis of concrete specimens is developed; the zero thickness cohesive elements are pre-inserted to simulate the crack initiation and propagation; the constitutive applied in cohesive element is established to describe the mechanism of crack separation, closure and friction behavior between the fracture surfaces. A series of simulations were carried out based on the model proposed in this paper. The results reproduced the main fracture and mechanical feature of concrete under compression condition. The effect of key material parameters, structure size, and aggregate content on the concrete fracture pattern and loading carrying capacities was investigated. It is found that the inner friction coefficient has a significant influence on the compression character of concrete, the compression strength raises linearly with the increase of the inner friction coefficient, and the fracture pattern is sensitive to the mesostructure of concrete.

• Laboraroty Animal Research
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• 제34권4호
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• pp.203-210
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• 2018

Stress severely disturbs physiological and mental homeostasis which includes adult neurogenesis in hippocampus. Neurogenesis in hippocampus is a key feature to adapt to environmental changes and highly regulated by multiple cellular signaling pathways. The primary cilium is a cellular organelle, which acts as a signaling center during development and neurogenesis in adult mice. However, it is not clear how the primary cilia are involved in the process of restraint (RST) stress response. Using a mouse model, we examined the role of primary cilia in repeated and acute RST stress response. Interestingly, RST stress increased the number of ciliated cells in the adult hippocampal dentate gyrus (DG). In our RST model, cell proliferation in the DG also increased in a time-dependent manner. Moreover, the analysis of ciliated cells in the hippocampal DG with cell type markers indicated that cells that were ciliated in response to acute RST stress are neurons. Taken together, these findings suggest that RST stress response is closely associated with an increase in the number of ciliated neurons and leads to an increase in cell proliferation.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 추계학술발표대회
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• pp.347-350
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• 2011

This paper propose a statistical color model of background extraction base on Hue-Saturation-Value(HSV) color space, instead of the traditional RGB space, and shows that it provides a better use of the color information. HSV color space corresponds closely to the human perception of color and it has revealed more accuracy to distinguish shadows [3] [4]. The key feature of this segmentation method is based on processing hue component of color in HSV color space on image area. The HSV color model is used, its color components are efficiently analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination condition and shadows. Polar and linear statistical operations are used to calculate the background from the video frames. The experimental results show that the proposed background subtraction method can automatically segment video objects robustly and accurately in various illuminating and shadow environments.

• Journal of Platform Technology
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• 제11권5호
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• pp.3-15
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• 2023

Requirements traceability link information is the basis for determining whether requirement change requested throughout the software development life cycle should be reflected in the system. Setting up complete requirements traceability links requires considerable effort. However, the commensurate benefits can be obtained in later development or further maintenance phases. For this reason, setting up and managing requirements traceability links in the software development phase are tasks that cause considerable resistance to developers. This study proposes a method for generating requirement traceability links in business applications. The key feature of the proposed method is that the traceability link from the requirements element, which is the basis of the corresponding element to the analysis element, is automatically established at the same time the elements of the analysis model are identified. This can be a way to reduce developer effort while increasing the efficiency of the traceability model. A case study on a Course Registration System demonstrates the feasibility of applying the proposed requirements traceability management method to actual software development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• Nuclear Engineering and Technology
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• 제48권3호
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• pp.684-701
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• 2016

The Gaussian process model (GPM) is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitions while dealing with a large number of uncertainties.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.421-427
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• 2013

The dependence between wind speeds in multiple wind sites has a considerable impact on the reliability of power systems containing wind energy. This paper presents a new method to generate dependent wind speed time series (WSTS) based on copulas theory. The basic feature of the method lies in separating multivariate WSTS into dependence structure and univariate time series. The dependence structure is modeled through the use of copulas, which, unlike the cross-correlation matrix, give a complete description of the joint distribution. An autoregressive moving average (ARMA) model is applied to represent univariate time series of wind speed. The proposed model is illustrated using wind data from two sites in Canada. The IEEE Reliability Test System (IEEE-RTS) is used to examine the proposed model and the impact of wind speed dependence between different wind regimes on the generation system reliability. The results confirm that the wind speed dependence has a negative effect on the generation system reliability.

• 경영과학
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• 제23권1호
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• pp.21-41
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• 2006

Given the growing deployment of mobile offices, we need to understand the fectors which affect their successful use and implementation. We in this paper present a parsimonious model which integrates the IS success model and the TAM. The main feature of the model is that it allows one to explore the role of mobility of mobile office systems in determining the level of system usage and dependence. Although the mobility is the key property of any mobile system, there is little research effort exerted to understand how mobility affects the traditional IS factors such as perceived ease of use and usefulness. In addition to the system usage, this model also uses dependence as the dependent variable. This is expected to provide richer understanding of the study context. We collected survey data from 1,614 field service workers of a major domestic electronic company. They use PDAs to retrieve information regarding the specifics of the customer service requests and to report what has been done for each service job. The results from SEM analysis show that mobility improves the perceived ease of use which then leads the field service workers to depend more on the PDA systems. Interestingly enough, however, the workers' satisfaction does not cause more frequent use of the system.

• 유통과학연구
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• 제22권10호
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• pp.43-54
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• 2024

Purpose: Market competition in the fashion industry is intensifying, pushing brands to strive for consumer preference and market leadership. Mobile fashion applications have emerged as key distribution channels, with live streaming being a common feature for product distribution and consumer loyalty. Therefore, this study will analyze the loyalty model in live streaming on mobile fashion applications by integrating the quality loyalty model, parasocial relationships, and uses and gratifications (U&G) theory. Research design, data and methodology: Data were collected from a survey of 427 respondents who are customers of a fashion product that had been purchased through live streaming on a mobile fashion application and processed using the PLS-SEM method Results: The results of the study show that the live streamer and product quality significantly influence satisfaction and loyalty. Conversely, AR content and live streaming content do not directly influence loyalty but have an indirect effect through satisfaction Conclusions: this study is the first to model loyalty in mobile fashion applications by integrating the quality loyalty model, parasocial relationship, and U&G theory. Practically, fashion companies are advised to conduct live streaming by considering aspects of content, live streamer, and product quality to enhance satisfaction and loyalty.

• 정보보호학회논문지
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• 제15권6호
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• pp.93-103
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• 2005

XML에 대한 사용의 증가와 함께, XML. 객체에 대한 보안의 필요성이 계속해서 증가하고 있다. 특히, 다양한 사용자가 서로 결합되어 있는 환경에서 공유되는 XML. 객체에 대한 접근제어 문제의 해결은 매우 중요하다. 본 논문에서는 XML 객체에 대한 접근제어를 위하여 RBAC의 역할 계층과 계층적 키 유도/할당 기법을 결합한 접근제어 모델을 제안한다. RBAC는 자체적으로 주체에 대한 키 할당 기법은 지원하지 않으므로 계층적 키 분배 기법을 도입하여 접근제어 메커니즘이 실현되도록 하였다. 본 논문에서 제안된 방식은 XML. 객체를 위한 접근제어에서 RBAC이 제공하는 관리상의 이점뿐만 아니라, 상위 계층의 사용자가 하위 계층의 키를 유도하여 사용할 수 있게 지원하므로 각 역할계층에서 관리하는 키의 수가 기존 방식에 비하여 줄어드는 특징을 제공한다.