• Journal of Korean Academy of Fundamentals of Nursing
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• v.19 no.4
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• pp.463-473
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• 2012

Purpose: The main purpose of this study was to identify factors affecting medication adherence and to develop an explanatory model for medication adherence in elders with chronic disease. Method: Empirical data were collected from 312 older adults with chronic disease and the data collect period was from August 8 to 31, 2011, and were analyzed using SPSS for Windows 19.0 program and confirmatory factor analysis with the structural equation model (SEM) procedure performed with AMOS 19.0 program. Results: Results of this study showed that perceived self-efficacy was the strongest factor influencing medication adherence, and it affected also outcome expectations positively but impediments were negatively influenced by self-efficacy. Outcome expectations and impediments subsequently acted on medication adherence with the same relationship as self-efficacy. In additional results, self-efficacy and medication adherence were further significantly affected by the factors; social support, medication knowledge, and depression. Conclusion: These results show that nursing interventions to promote medication adherence in this population should focus on self-efficacy promotion including social support, education for delivery of medication knowledge, and reduction in depression.

• Convergence Security Journal
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• v.12 no.6
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• pp.3-10
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• 2012

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, finite failure non-homogeneous Poisson process model, considering learning factor, presented and propose release policies of the life distribution, log linear type model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameters estimation using maximum likelihood estimation of failure time data, make out estimating software optimal release time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.5
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• pp.828-834
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• 1997

The knowledge of material stress-strain behavior is an essential requirement for design and analysis of deformation processes. Empirical stress-strain relationship and constitutive equations describing material behavior during deformation are being widely used, despite suffering some drawbacks in terms of ease of development, accuracy and speed. In the present study, back-propagation neural networks are used to model and predict the flow stresses of a HSLA steel under conditions of constant strain, strain rate and temperature. The performance of the network model is comparedto those of statistical models on rate equations. Well-trained network model provides fast and accurate results, making it superior to statistical models.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.475-485
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• 1995

In this study, statistical analysis of fatigue data which had obtained from respective 24 fatigue crack, was examined for SiC whisker reinforced aluminium 6061 composite alloy (SiC$_{w}$/A16061) and aluminium 6061 alloy. SiC volume fraction in composite alloy is 25%. The analysis results stress intensity factor range and 0.1 mm fatigue crack initiation life for SiC$_{w}$/A16061 composite & A16061 matrix are the log-normal distribution. And regression analysis by linear model, exponential model and multiplicative model were performed to find out the relationship between fatigue crack growth rate(da/dN) and stress intensity for find out the relationship between fatigue crack growth rate(da/dN) and stress intensity factor range(.DELTA.K) in the SiC$_{w}$/A16061 composite and examine the applicability of Paris' equation to SiC$_{w}$A16061 composite. Also computer simulation was performed for fatigue life prediction of SiC$_{w}$/A16061 composite using the statistical results of this study.udy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.496-500
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• 1997

This paper describes an automated system for analyzing the stress intensity factors(SIFs) of three-dimensional (3D) cracks. A geometry model, i.e.a solid containing one or several 3D cracks is defined. Several distributions of local node density are chosen, and then automatically superposed on one another over the geometry model by using the fuzzy knowledge processing. Nodes are generated by the bucketing method, and ten-noded quadratic tetrahedral solid elements are generated by the Delauuay triangulation techniques. The singular elements such that the mid-point nodes near crack fornt are shifted at the quarter-points are automatically placed along the 3D crack front. THe complete finite element (FE) model generated, i.e the mesh with material properties and boundary conditions is given to one of the commercial FE codes, and a stress analysis is performed. The SIFs are calculated using the displacement extrapolation method. To demonstrate practical performance of the present system, a semi- elliptical surface crack in a plate subjected to tension is solved.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.603-613
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• 2008

We often encounter the situation that discrete count data have a large portion of zeros. In this case, it is not appropriate to analyze the data based on standard regression models such as the poisson or negative binomial regression models. In this article, we consider Bayesian analysis for two commonly used models. They are zero-inflated poisson and negative binomial regression models. We use the Bayes factor as a model selection tool and computation is proceeded via Markov chain Monte Carlo methods. Crash count data are analyzed to support theoretical results.

• The Journal of Information Systems
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• v.26 no.3
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• pp.25-46
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• 2017

Purpose The purpose of this study is to analyze the factors for continuous use intention of the simple payment service based on FinTech for Chinese residents in Korea. The Technology Acceptance Model(TAM) and the continuous use model of information system were applied to the AliPay service, which is the most used by Chinese people. Design/methodology/approach In this study, internal factors and external factors for the simple payment service were derived through previous studies and the effects of the users' perspectives on the intention of continuous use were analyzed. As a result, convenience, responsiveness, perceived usefulness, and suitability were supported as factors affecting ongoing intention to use simple payment service. Especially, convenience is a factor affecting the duration of the simple payment service and it is an important factor for the continuous use of the service. Findings As the number of foreigners living or working in Korea is increasing, understanding the perception of the simple payment service and analyzing the factors for the continuous use can be meaningful as a basic research for the market advancement and growth of domestic FinTech companies is.

• Journal of the Korean Society of Costume
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• v.51 no.6
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• pp.117-128
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• 2001

The purposes of this study was to investigate discriminative factors of clothing buying intention on Internet shopping mall. The sample included 435 male(44.8%) and female(55.2% ) adults, and an instrument was developed based on previous studies. The statistical analysis used for this study were factor analysis, 1-test, and LISREL. The results of factor analysis showed that consumers evaluated apparel internet shopping attributes based on perceptional dimensions of internet shopping consisted of clothing quality and value. web service quality and value, and adoption of internet shopping. Each dimension has sub-factors as follows: (1) clothing quality was perceived as 'artistry' 'sociality' and 'practicality'. (2) web interface service quality was perceived as 'visuality', 'advantage', 'response', 'dependability' and 'buying-confidence'. (3) internet shopping adoption was perceived as 'usefulness' and 'convenience'. T-test revealed that consumer's buying intention, re-entry intention, and store attitude were differed concerning all sub-factors including 'usefulness' and 'convenience' in adoption of Internet shopping dimension. As a result of LISREL, clothing buying intention path model was set up as following path. (1) 'artistry', 'sociality' and 'practicality' of clothing quality affected clothing value perception positively. (2) 'visuality', 'advantage', 'response' and 'buying-confidence' of web service quality affected web service value perception positively. (3) clothing and web service value perception affected store attitude positively. (4) store attitude affected clothing buying intention positively. However, Adoption of Internet shopping dimension that was perceived as usefulness and convenience did not affect clothing buying intention path model. Therefore, consumers buying, intention model in internet circumstance could be used nearly the same as real market circumstance.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.6 s.249
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• pp.560-567
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• 2006

Although various conjectures have been proposed to explain abnormal increase in thermal conductivity of nanofluids, the detailed mechanism could not be understood and explained yet. The main reason is primarily due to the lack of knowledge on the most fundamental factor governing the mechanisms such as Brownian motion, liquid layering, phonon transport, surface chemical effects and agglomeration. By applying surface complexation model for the measurement data of hydrodynamic size, zeta potential, and thermal conductivity, we have shown that sulfate charge state is mainly responsible for the increase in the present condition and may be the factor incorporating all the mechanisms as well. Moreover, we propose a new model including concepts of fractal and interfacial layer. The properties such as thickness and thermal conductivity of the layer are estimated from the surface charge states and the concept of electrical double layer. With this, we could demonstrate the pH dependences of the layer properties and eventually of the effective thermal conductivity of the nanofluid.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.5
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• pp.489-495
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• 2009

A novel technique to measuret of viscoelastic properties of polymers is proposed to investigate complex Poisson's ratio as a function of frequency. The forced vibration responses for the samples under the normal and the shear deformation are to be measured with varying load masses. The measured data were used to obtain the viscoelastic properties of the material based on an accurate 2D numerical deformation model of the sample. The 2D model enabled us to exclude data correction by the empirical form factor used in 1D model. Comprehensive measurements of viscoelastic properties of two slightly varied silicone RTV rubber ($Silastic^{(R)}$ S2) compositions were performed. Standard composition (90% PDMS polymer + 10% catalyst) and modified composition (92.5% polymer + 7.5% catalyst) were tested in temperature range from $30^{\circ}C$ to $70^{\circ}C$. Shear modulus, modulus of elasticity, loss factor, and both the real and the imaginary parts of the Poisson's ratio were determined for frequencies from 50 to 400Hz in the linear deformation regime (at relative deformations $10^{-4}{\sim}10^{-3}$).