The selection of the support system is an important design parameter in design and construction of the tunnel using the new Australian tunnel method. It is a common practice to select the support based on the rock mass grade, in which the rock mass is classified into five rock groups. The method is applicable if the characteristics of the rock mass are uniform in the direction of tunnel excavation. However, such case is seldom encountered in practice and not applicable when the properties vary along the longitudinal direction. This study performs comprehensive three dimensional finite difference analyses to investigate the ground deformation pattern for cases in which the rock mass properties change in the direction of the tunnel axis. The numerically calculated displacements at the tunnel crown show that the displacement is highly dependent on the stiffness contrast of the rock masses. The results strongly indicate the need to select the support type $0.5{\sim}1.0D$ before the rock mass boundary. The paper proposes a new guideline for selecting the support type based the results of the analyses.
Kim, Kyoung-Ok;Park, Mi-Jung;Lee, In-Kwang;Park, Kyung-Soon;Shon, Ho-Sun;Kim, Kyung-Ah;Seo, Chang-Jin;Cha, Eun-Jong
Journal of Biomedical Engineering Research
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v.37
no.2
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pp.75-83
/
2016
Nursing staffing is of major interest in hospital management, however, no practical method has been developed. The present study proposed a mathematical model based on the patient classification system for nursing staffing optimization. A few characteristic parameters possibly determined experimentally and/or empirically were introduced followed by systematic calculation of the required number of nurses. An essential concept of the model is the unit work load defined as the amount of nursing work performed on single patient per unit time, where the work load is defined as the number of nursing staffs multiplied by the working hours. The unit work load was considered to vary with the patient classification level as well as the working time during a day, both of which were represented by corresponding parameter values. The number of patients for each class and the number of working hours were multiplied to the unit work load, and added up to obtain the total required work load. As the next step, the averaged number of hours that a nurse could provide per day was formulated considering the degree of nursing practice experience into 3 levels. Finally, the appropriate number of nursing staffs was calculated as the total work load divided by the average working hours per nurse. The present technique has a great advantage that the number of nursing staffs to fulfill the required work load is systematically calculated once the characteristic parameters are appropriately determined, leading to instant and fast evaluation. A practical PC program was also developed to apply the present model to nursing practice.
Poisson's ratio due to multiaxial creep of concrete reported by existing experimental works was controversial. Poisson's ratio calculated from measured strain is very sensitive to small experimental error. This sensitivity make it difficult to find out whether the Poisson's ratio varies with time or remain constant, and whether the Poisson's ratio has different value with stress states or not. A new approach method is needed to resolve the discrepancy and obtain reliable results. This paper presents analytical study on multiaxial creep test results. Microplane model as a new approach method is applied to optimally fitting the test data extracted from experimental studies on multiaxial creep of concrete. Double-power law is used as a model to present volumetric and deviatoric creep evolutions on a microplane. Six parameters representing the volumetric and deviatoric compliance functions are determined from regression analysis and the optimum fits accurately describe the test data. Poisson's ratio is calculated from the optimum fits and its value varies with time. Regression analysis is also performed assuming that Poisson's ratio remains constant with time. Four parameters are determined for this condition, and the error between the optimum fits and the test data is slightly larger than that for six parameter regression results. The constant Poisson's ratio with time is obtained from four parameter analysis results and the constant value can be used in practice without serious error.
The Journal of Korean Academy of Sensory Integration
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v.7
no.2
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pp.77-90
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2009
Objective : The purpose of this study was to provide evidence for the effectiveness of Sensory Integrative Intervention (SII) through a systematic review. Method : The systematic review was executed using MEDLINE/PubMed, PsycINFO, CINAHL, Cochrane Library, OTSeeker. The key words for search was "effects of sensory integration", "sensory integration therapy", and "sensory integration intervention". 11 studies were used for data analysis, and the level of evidence were level I, leve lII and level IV. The substances of review were subject (population), method (intervention type), effect of the intervention, outcome parameter, and outcome measurement. Results : 1. The subjects of SII were autism spectrum disorders (30.7%), pervasive developmental disorder (15.4%) and preterm infants (15.4%). 2. Most frequently used method was the traditional intervention of J. Ayres (36.5%). The outcome parameters of SII were behavioral outcome (40.63%), motor performance outcome (28.13%), sensory-based outcome (25.0%), and academic outcome (6.35%). 3. The effects of SII were improvement of motor performance (66.7%), sensory-based (62.5%), and behavior problems (61.5%). In most studies, however, academic skill such as writing skill was not a positive outcome parameter in terms of effectiveness of SII. Conclusions : The results implied that the sensory integrative intervention is effective on motor performance, sensory-based and behavioral change, but not on the academic skill. It is suggested that the future research need to be done to examine whether and how the effect of sensory integration intervention can be long-lasting and contribute any academic skill and activities of daily living performance.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.15
no.3
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pp.207-221
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2020
This study conducted a meta-analysis on the effects of innovation, risk-taking, and enterprising on entrepreneurship. From 2013 to 2020, 392 papers, which were judged as quantitative research from doctoral and master thesis, and academic journals published in Korea were selected as research subjects. 28 duplicates of thesis and thesis are excluded. A total of 52 papers were finally selected, excluding 312 papers that were insufficient to be used as research data because there were no statistical values such as correlation coefficients. For the 52 selected papers, the homogeneity of the variables was first verified. As a result of the homogeneity test, the innovativeness, risk-taking, initiative, and entrepreneurship education all showed great effects on heterogeneity, and the average effect size was analyzed by random effect model. The average effect size analyzed was 0.38 ~ 0.49, and all four variables showed moderate average effect size. As a result of analyzing the average effect size by forest plot, all showed proper results. From the results of funnel plot analysis of entrepreneurship education, published errors were confirmed asymmetric. Research data on entrepreneurship education shows that it cannot represent the whole. It is a structural equation model with entrepreneurship and entrepreneurial intention as a parameter. Iinnovation and risk-taking have an impact on entrepreneurship by taking entrepreneurship education as a parameter. Initiative had an effect on the entrepreneurial intention a business, regardless of entrepreneurship education. In a number of studies, university entrepreneurship education has had an impact on the entrepreneurial intention. It should be changed to entrepreneurship education that combines theory and practice. Entrepreneurship education should be transformed into continuous and field-oriented education.
Yoon, Chang-Yun;Lee, Misol;Kim, Seung Up;Lim, Hyunsun;Chang, Tae Ik;Kee, Youn Kyung;Han, Seung Gyu;Han, In Mee;Kwon, Young Eun;Park, Kyoung Sook;Lee, Mi Jung;Park, Jung Tak;Han, Seung Hyeok;Ahn, Sang Hoon;Kang, Shin-Wook;Yoo, Tae-Hyun
Kidney Research and Clinical Practice
/
v.36
no.1
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pp.48-57
/
2017
Background: Hepatic steatosis measured with controlled attenuation parameter (CAP) using transient elastography predicts metabolic syndrome in the general population. We investigated whether CAP predicted metabolic syndrome in chronic kidney disease patients. Methods: CAP was measured with transient elastography in 465 predialysis chronic kidney disease patients (mean age, 57.5 years). Results: The median CAP value was 239 (202-274) dB/m. In 195 (41.9%) patients with metabolic syndrome, diabetes mellitus was more prevalent (105 [53.8%] vs. 71 [26.3%], P < 0.001), with significantly increased urine albumin-to-creatinine ratio (184 [38-706] vs. 56 [16-408] mg/g Cr, P = 0.003), high sensitivity C-reactive protein levels (5.4 [1.4-28.2] vs. 1.7 [0.6-9.9] mg/L, P < 0.001), and CAP (248 [210-302] vs. 226 [196-259] dB/m, P < 0.001). In multiple linear regression analysis, CAP was independently related to body mass index (${\beta}=0.742$, P < 0.001), triglyceride levels (${\beta}=2.034$, P < 0.001), estimated glomerular filtration rate (${\beta}=0.316$, P = 0.001), serum albumin (${\beta}=1.386$, P < 0.001), alanine aminotransferase (${\beta}=0.064$, P = 0.029), and total bilirubin (${\beta}=-0.881$, P = 0.009). In multiple logistic regression analysis, increased CAP was independently associated with increased metabolic syndrome risk (per 10 dB/m increase; odds ratio, 1.093; 95% confidence interval, 1.009-1.183; P = 0.029) even after adjusting for multiple confounding factors. Conclusion: Increased CAP measured with transient elastography significantly correlated with and could predict increased metabolic syndrome risk in chronic kidney disease patients.
This study was designed to construct a model that predicts the quality of life of family caregivers with a chronically ill patient. The hypothetical model was developed based on the findings from past studies on quality of life and on the family with a chronically ill patient. Data were collected by self-reported questionnaires from 200 family caregivers in Seoul & Kyung Gi-Do, from May 1 to July 21, 1997. Data were analyzed using descriptive statistics and correlation analysis. The Linear Structural Relationship(LISREL) modeling process was used to find the best fit model which predicts causal relationships among variables. The results are as follows : 1. The overall fit of the hypothetical model to the data was moderate [X$^2$=31.54(df=23, p=.11), GFI=.96, AGFI=.91, RMR=.04]. 2. Paths of the model were modified by considering both its theoretical implication and the statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data expect chi-square value(GFI=.95, AGFI=.91, RMR=.04). 3. Some of predictive factors, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support and fatigue revealed indirect effects on the quality of life of family caregivers with a chronically ill patient. 4. The factors, burden and role satisfaction revealed significant direct effects on the quality of life of family caregivers with a chronically ill patient. 5. All predictive variables of quality of life of family caregivers with a chronically ill patient, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support, fatigue, burden and role satisfaction explained 38.0% of the total variance in the model. In conclusion, the derived model in this study is considered appropriate in explaining and predicting quality of life of family caregivers with a chronically ill patient. Therefore it can effectively be used as a reference model for further studies and suggests direction in nursing practice.
Masonry infill walls are unavoidable parts of any building to create a separation between internal space and external environment. In general, there are some prevalent openings in the infill wall due to functional needs, architectural considerations or aesthetic concerns. In current design practice, the strength and stiffness contribution of infill walls is not considered. However, the presence of infill walls may decisively influence the seismic response of structures subjected to earthquake loads and cause a different behavior from that predicted for a bare frame. Furthermore, partial openings in the masonry infill wall are significant parameter affecting the seismic behavior of infilled frames thereby decreasing the lateral stiffness and strength. The possible effects of openings in the infill wall on seismic behavior of RC frames is analytically studied by means of pushover analysis of several bare, partially and fully infilled frames having different bay and story numbers. The stiffness loss due to partial opening is introduced by the stiffness reduction factors which are developed from finite element analysis of frames considering frame-infill interaction. Pushover curves of frames are plotted and the maximum base shear forces, the yield displacement, the yield base shear force coefficient, the displacement demand, interstory drift ratios and the distribution of story shear forces are determined. The comparison of parameters both in terms of seismic demand and capacity indicates that partial openings decisively influences the nonlinear behavior of RC frames and cause a different behavior from that predicted for a bare frame or fully infilled frame.
To estimate the compressive strength of concrete more realistically, relative large number of data are necessary. However, it is very common in practice that only limited data are available. The purpose of the present paper is therefore to propose a realistic method to estimate the compressive strength of concrete with limited data in actual site. The Bayesian method of statistical analysis has been applied to the problem of the estimation of compressive strength of concrete. The mean compressive strength is considered as the random parameter and a prior distribution is selected to enable updating of the Bayesian distribution of compressive strength of concrete reflecting both existing data and sampling observations. The updating of the Bayesian distribution with increasing data is illustrated in numerical application. It is shown that by combining prior estimation with information from site observation, more precise estimation is possible with relatively small sampling. It is also seen that the contribution of the prior in determining the posterior distribution depends on its sharpness or flatness in relation to the sharpness or flatness of the likelihood function. The present paper allows more realistic determination of concrete strength in site with limited data.
Journal of the Institute of Electronics Engineers of Korea SC
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v.37
no.1
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pp.10-18
/
2000
This paper proposes a fuzzy logic cross-coupled controller using a new contouring modeling for a two-axis servo system. The general decoupled control approach may result in degraded contouring performance due to such factors as mismatch of axial dynamics and axial loop gains. In practice, such systems contain many uncertainties. The cross-coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However, the conventional cross-coupled controllers cannot overcome friction, backlash, and parameter variations. Also since, it is difficult to obtain an accurate mathematical model of multi-axis system, here we investigate a fuzzy logic cross-coupled controller of servo system. In addition, new contouring error vector computation method is presented. The experimental results are presented to illustrate the performance of the proposed algorithm.
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