• International Journal of Concrete Structures and Materials
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• 제10권1호
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• pp.99-112
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• 2016

During earthquake, reinforced concrete walls show complicated post-yield behavior varying with shear span-to-depth ratio, re-bar detail, and loading condition. In the present study, a macro-model for the nonlinear analysis of multi-story wall structures was developed. To conveniently describe the coupled flexure-compression and shear responses, a reinforced concrete wall was idealized with longitudinal and diagonal uniaxial elements. Simplified cyclic material models were used to describe the cyclic behavior of concrete and re-bars. For verification, the proposed method was applied to various existing test specimens of isolated and coupled walls. The results showed that the predictions agreed well with the test results including the load-carrying capacity, deformation capacity, and failure mode. Further the proposed model was applied to an existing wall structure tested on a shaking table. Three-dimensional nonlinear time history analyses using the proposed model were performed for the test specimen. The time history responses of the proposed method agreed with the test results including the lateral displacements and base shear.

• 한국직업건강간호학회지
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• 제31권1호
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• pp.31-41
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• 2022

Purpose: This study aimed to identify the effects of organizational culture, organizational silence, and organizational commitment on the intention of retention as perceived by nurses Methods: The research model was designed on the basis of the PROCESS Macro model 6 proposed by Hayes. The participants were 142 nurses from general hospitals. Measurements included the scales of organizational culture, organizational silence, organizational commitment, and intention of retentione. Data were analyzed using descriptive statistics, Pearson's correlation coefficient analysis, and Hayes's PROCESS macro method for mediation. Results: Retention intention showed a significantly positive correlation with relationship-orientated culture (r=.32, p<.001), innovation-orientated culture (r=.30, p<.001), and organizational commitment (r=.48, p<.001). However retention intention showed a significantly negative correlation with organizational silence (r=-.42, p<.001). Furthermore, organizational silence and commitment had a mediating effect on the relationship between organizational culture and intention of retention. Conclusion: The impact of organizational culture on intention of retention in general hospitals was mediated by organizational silence and organizational commitment. Considering the mediating effects of organizational silence and organizational commitment on the relationship between nursing organizational culture and retention intention, a strategy should be developed to enhance organizational commitment and weaken organizational silence by strengthening related and innovative nursing culture.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 동계학술발표대회 논문집
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• pp.584-589
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• 2008

It is known that slab thermal storage which uses concrete slab as thermal material is effective in the load leveling and using the nighttime electric power. The temperature distribution is not constant in plenum in thermal storage time by beams, ducts such as several factor. It is considered that this fact will effect on efficiency of thermal storage and indoor thermal environment. The purpose of this paper is to examine the thermal environment inside plenum. A macro model was made for the analysis of indoor thermal environment as the first step. The flow rate distribution and temperature distribution of object room model was examined by use of basic equations such as airflow by the pressure difference between unit cells, heat flow by air and heat transfer.

• Journal of Information Processing Systems
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• 제8권3호
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• pp.409-420
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• 2012

The decision-making by agents in games is commonly based on reinforcement learning. To improve the quality of agents, it is necessary to solve the problems of the time and state space that are required for learning. Such problems can be solved by Macro-Actions, which are defined and executed by a sequence of primitive actions. In this line of research, the learning time is reduced by cutting down the number of policy decisions by agents. Macro-Actions were originally defined as combinations of the same primitive actions. Based on studies that showed the generation of Macro-Actions by learning, Macro-Actions are now thought to consist of diverse kinds of primitive actions. However an enormous amount of learning time and state space are required to generate Macro-Actions. To resolve these issues, we can apply insights from studies on the learning of tasks through Programming by Demonstration (PbD) to generate Macro-Actions that reduce the learning time and state space. In this paper, we propose a method to define and execute Macro-Actions. Macro-Actions are learned from a human subject via PbD and a policy is learned by reinforcement learning. In an experiment, the proposed method was applied to a car simulation to verify the scalability of the proposed method. Data was collected from the driving control of a human subject, and then the Macro-Actions that are required for running a car were generated. Furthermore, the policy that is necessary for driving on a track was learned. The acquisition of Macro-Actions by PbD reduced the driving time by about 16% compared to the case in which Macro-Actions were directly defined by a human subject. In addition, the learning time was also reduced by a faster convergence of the optimum policies.

• 한국안전학회지
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• 제33권4호
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• pp.98-104
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• 2018

Macroscopic accident analyses have been conducted to incorporate transportation safety into long-term transportation planning. In macro-level accident prediction model, exposure variable(e.g. a settled population) have been used as fundamental explanatory variable under the concept that each trip will be subjected to a probable risk of accident. However, a settled population may be embedded error by exclusion of active population concept. The objective of this research study is to develop macro-level accident prediction model using floating population variable(concept of including a settled population and active population) collected from mobile phone data. The concept of accident prediction models is introduced utilizing exposure variable as explanatory variable in a generalized linear regression with assumption of a negative binomial error structure. The goodness of fit of model using floating population variable is compared with that of the each models using population and the number of household variables. Also, log transformation models are additionally developed to improve the goodness of fit. The results show that the log transformation model using floating population variable is useful for capturing the relationships between accident and exposure variable and generally perform better than the models using other existing exposure variables. The developed model using floating population variable can be used to guide transportation safety policy decision makers to allocate resources more efficiently for the regions(or zones) with higher risk and improve urban transportation safety in transportation planning step.

• Journal of Power Electronics
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• 제18권5호
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• pp.1489-1500
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• 2018

Partial shading analysis of large-scale photovoltaic (PV) arrays has recently become a theoretically and numerically challenging issue, and it is necessary for PV system designers. The main contributions of this study are the following: 1) A PSIM-based macro-model was employed because it is remarkably fast, has high precision, and has no convergence issues. 2) Three types of equivalent macro-models were developed for the transformation of a small PV sub-array with uniform irradiance to a new macro-model. 3) On the basis of the proposed new macro-model, a tearing method was established, which can divide a large-scale PV array into several small sub-arrays to significantly improve the efficiency improvement of a simulation. 4) Three platforms, namely, PSIM, PSpice, and MATLAB, were applied to evaluate the proposed tearing method. The proposed models and methods were validated, and the value of this research was highlighted using an actual large-scale PV array with 2420 PV modules. Numerical simulation demonstrated that the tearing method can remarkably improve the simulation efficiency by approximately thousands of times, and the method obtained a precision of nearly 6.5%. It can provide a useful tool to design the optimal configuration of a PV array with a given shading pattern as much as possible.

• 대한기계학회논문집A
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• 제33권11호
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• pp.1202-1208
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• 2009

An inverse finite element (FE) model parameter estimation algorithm can be used to characterize mechanical properties of biological tissues. Using this algorithm, we can consider the influence of material nonlinearity, contact mechanics, complex boundary conditions, and geometrical constraints in the modeling. In this study, biomechanical experiments on macro and micro samples are conducted and characterized with the developed algorithm. Macro scale experiments were performed to measure the force response of porcine livers against mechanical loadings using one-dimensional indentation device. The force response of the human liver cancer cells was also measured by the atomic force microscope (AFM). The mechanical behavior of porcine livers (macro) and human liver cancer cells (micro) were characterized with the algorithm via hyperelastic and linear viscoelastic models. The developed models are suitable for computing accurate reaction force on tools and deformation of biomechanical tissues.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.671-674
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• 2005

The series parasitic resistances ($R_s$, $R_g$, $R_d$, $R_{sub}$) of BSIM3v3 RF MOSFET macro model were directly extracted from measured S-parameters in the GHz region by using simple 2-port parameter equations. Also, overlap capacitance and junction capacitance parameters were extracted by tuning $S_{11}$, $S_{12}$, and $S_{22}$ respectively while DC-parameters and all parasitic resistances are fixed at previously extracted values. These data are verified to be accurate by observing good correspondence between modeled and measured S-parameters up to 10GHz.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.675-678
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• 2005

An improved BSIM3v3 RF Macro model with RC parallel substrate circuit has been developed to simulate RF characteristics of the output admittance in MOSFET accurately. This improved model shows better agreements with measured $Y_{22}-parameter$ up to 10 GHz than conventional one with a single substrate resistance, verifying the accuracy of the improved one.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2011년 춘계학술대회논문집
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• pp.286-290
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• 2011

This paper introduces the optimum macro-siting of a potential site for an offshore wind farm around Jeju Island using the RDAPS sea wind model. The statistical model was developed by analyzing the sea wind data from RDAPS model, and the meso-scale digital wind map was prepared. To develop the high resolution spatial calibration model, Artificial Neural Network(ANN) models were used to construct the wind and bathymetric maps. Accuracy and consistency of wind/bathymetric spatial calibration models were obtained using analysis of variance. The optimization problem was defined to maximize the energy density satisfying the criteria of maximum water depth and maximum distance from the coastline. The candidate site was selected through Genetic Algorithm(GA). From the results, it is possible to predict roughly a candidate site location for the installation of the offshore wind jam, and to evaluate the wind resources of the proposed site.