• Journal of Korean Academy of Nursing
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• v.42 no.5
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• pp.719-729
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• 2012

Purpose: This study was done to examine relationships between nurse staffing level and postsurgical patient outcomes using inpatient database from the National Health Insurance. Methods: Records of 111,491 patients who received one of 12 types of surgery between January and December, 2009 were identified and analyzed in this study. Nurse staffing level was measured using adjusted nurse staffing grades from 0 to 7. Patient outcomes were defined as in-hospital mortality, or pneumonia, sepsis, or urinary tract infection after surgery. Logistic regression analyses estimated by Generalized Estimation Model, were used to analyze the association between nurse staffing level and patient outcomes. Results: An inverse relationship was found between nurse staffing and patient mortality. Compared with patients who were cared for in hospitals with the highest nurse staffing (Grades 0-1), increases in the odds of dying were found in those with Grades 6-7 [OR (odds ratio)=2.99, 95% CI (confidence interval)=1.94-4.60], those with Grades 4-5 (OR=1.78, 95% CI=1.24-2.57) and those with Grades 2-3 (OR=1.57, 95% CI=1.25-1.98). Lower nurse staffing level was also associated with higher number of cases in pneumonia and sepsis. Conclusion: Policies for providing adequate nurse staffing is required to enhance quality of care and lead to better perioperative patient outcomes.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.269-275
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• 2013

In this paper, a new modeling method of a magnetic levitation(Maglev) system using extreme learning machine(ELM) is proposed. The linearized methods using Taylor Series expansion has been used for modeling of a Maglev system. However, the numerical method has some drawbacks when dealing with the components with high nonlinearity of a Maglev system. To overcome this problem, we propose a new modeling method of the Maglev system with electro magnetic suspension, which is based on ELM with fast learning time than conventional neural networks. In the proposed method, the initial input weights and hidden biases of the method are usually randomly chosen, and the output weights are analytically determined by using Moore-Penrose generalized inverse. matrix Experimental results show that the proposed method can achieve better performance for modeling of Maglev system than the previous numerical method.

• Ocean and Polar Research
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• v.31 no.2
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• pp.177-187
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• 2009

This study examined the multi-scale variabilities of sea surface temperature (SST) and salinity in the Japan/East Sea (JES) based on statistical analyses of observational data, with a focus on the northwestern part of the sea. The regionality of JES SST variability was estimated for different frequency ranges on semimonthly (11-17 days), monthly to seasonal (30-90 days), quasi-semiannual (157-220 days), and quasi-biennial (1.5-3 years) time scales using cluster analyses of daily gridded SST data for 1996 to 2007 from the Japan Meteorological Agency (JMA). Several significant peaks and regional cores were found in each frequency range of the SST anomaly (SSTA) oscillations. Quasi-semiannual SSTA oscillations with high amplitude were found in the south-southwestern part of the Japan Basin ($41-43^{\circ}N$) and were amplified in the area adjacent to Peter the Great Bay. Oscillations with periods of 79 and 55 days also prevailed over the southwest Japan Basin between the Yamato Rise and the continental slope. A similar method was applied to classify SST and the annual cycle of surface salinity using Generalized Digital Environmental Model (GDEM) gridded data. The Tatarskii Strait and adjacent area showed the most specific annual cycles and variability in salinity on interannual to interdecadal time scales. The most significant inverse relationship between surface salinity in the Tatarskii Strait and southern JES areas was found on the interdecadal time scale. Linkages of sea water salinity in the Tatarskii Strait with Amur River discharge and wind velocity over Amurskii Liman were also revealed.

• Journal of Korean Association for Spatial Structures
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• v.10 no.2
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• pp.87-94
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• 2010

Form-Finding of tensegrity structures by eigenvalue problem is presented, In ardor to maintain the structures stable, "Form-Finding" should be performed. The types of analytical methods are known to solve this phenomenon: One is to use force density method, and the other is to apply so called, generalized inverse method. In this paper, new form finding methods are presented to obtain the self-equilibrium stress of the tensegrity structures. This method is based on the equilibrium equation of the all of the joint and the governing equation is formulated as eigonvalue problem. In order to verify this approach, numerical example(tensegrity structures) are compared with others calculated by previous methods. The solution by present method is shown identical results. Furthermore, the developed process to find the results is more efficient than previous approaches.

• Journal of applied mathematics & informatics
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• v.11 no.1_2
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• pp.305-316
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• 2003

Recently, an iterative algorithm for finding the interior eigenvalues of a definite matrix by CG-type method has been proposed. This method compares to the inverse power method. The given matrices A, and B are assumed to be large and sparse, and SPD( Symmetric Positive Definite) The CG scheme for the optimization of the Rayleigh quotient has been proven a very attractive and promising technique for large sparse eigenproblems for smallest eigenvalue. Also, it is very amenable to parallel computations, like the CG method for the linear systems. A proper choice of the preconditioner significantly improves the convergence of the CG scheme. But for parallel computations we need to find an efficient parallel preconditioner. Our candidates we ILU(0) in the wave-front order, ILU(0) in the multi-coloring order, Point-SSOR(Symmetric Successive Overrelaxation), and Multi-Color Block SSOR preconditioner. Wavefront order is a simple way to increase parallelism in the natural order, and Multi-coloring realizes a parallelism of order(N), where N is the order of the matrix. Another choice is the Multi-Color Block SSOR(Symmetric Successive OverRelaxation) preconditioning. Block SSOR is a symmetric preconditioner which is expected to minimize the interprocessor communication due to the blocking. We implemented the results on the CRAY-T3E with 128 nodes. The MPI (Message Passing Interface) library was adopted for the interprocessor communications. The test problem was drawn from the discretizations of partial differential equations by finite difference methods. The results show that for small number of processors Multi-Color ILU(0) has the best performance, while for large number of processors Multi-Color Block SSOR performs the best.

• Smart Structures and Systems
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• v.17 no.2
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• pp.167-194
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• 2016

This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8371-8376
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• 2014

Background: The use of statistical methods has become an imperative tool in breast cancer survival data analysis. The purpose of this study was to develop the best statistical probability model using the Bayesian method to predict future survival times for the black non-Hispanic female breast cancer patients diagnosed during 1973-2009 in the U.S. Materials and Methods: We used a stratified random sample of black non-Hispanic female breast cancer patient data from the Surveillance Epidemiology and End Results (SEER) database. Survival analysis was performed using Kaplan-Meier and Cox proportional regression methods. Four advanced types of statistical models, Exponentiated Exponential (EE), Beta Generalized Exponential (BGE), Exponentiated Weibull (EW), and Beta Inverse Weibull (BIW) were utilized for data analysis. The statistical model building criteria, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were used to measure the goodness of fit tests. Furthermore, we used the Bayesian approach to obtain the predictive survival inferences from the best-fit data based on the exponentiated Weibull model. Results: We identified the highest number of black non-Hispanic female breast cancer patients in Michigan and the lowest in Hawaii. The mean (SD), of age at diagnosis (years) was 58.3 (14.43). The mean (SD), of survival time (months) for black non-Hispanic females was 66.8 (30.20). Non-Hispanic blacks had a significantly increased risk of death compared to Black Hispanics (Hazard ratio: 1.96, 95%CI: 1.51-2.54). Compared to other statistical probability models, we found that the exponentiated Weibull model better fits for the survival times. By making use of the Bayesian method predictive inferences for future survival times were obtained. Conclusions: These findings will be of great significance in determining appropriate treatment plans and health-care cost allocation. Furthermore, the same approach should contribute to build future predictive models for any health related diseases.

• The Journal of Art Theory & Practice
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• no.7
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• pp.165-188
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• 2009

In the development of linear perspective, Brook Taylor's theory has achieved a special position. With his method described in Linear Perspective(1715) and New Principles of Linear Perspective(1719), the subject of linear perspective became a generalized and abstract theory rather than a practical method for painters. He is known to be the first who used the term 'vanishing point'. Although a similar concept has been used form the early stage of Renaissance linear perspective, he developed a new method of British perspective technique of measure points based on the concept of 'vanishing points'. In the 15th and 16th century linear perspective, pictorial space is considered as independent space detached from the outer world. Albertian method of linear perspective is to construct a pavement on the picture in accordance with the centric point where the centric ray of the visual pyramid strikes the picture plane. Comparison to this traditional method, Taylor established the concent of a vanishing point (and a vanishing line), namely, the point (and the line) where a line (and a plane) through the eye point parallel to the considered line (and the plane) meets the picture plane. In the traditional situation like in Albertian method, the picture plane was assumed to be vertical and the center of the picture usually corresponded with the vanishing point. On the other hand, Taylor emphasized the role of vanishing points, and as a result, his method entered the domain of projective geometry rather than Euclidean geometry. For Taylor's theory was highly abstract and difficult to apply for the practitioners, there appeared many perspective treatises based on his theory in England since 1740s. Joshua Kirby's Dr. Brook Taylor's Method of Perspective Made Easy, Both in Theory and Practice(1754) was one of the most popular treatises among these posterior writings. As a well-known painter of the 18th century English society and perspective professor of the St. Martin's Lane Academy, Kirby tried to bridge the gap between the practice of the artists and the mathematical theory of Taylor. Trying to ease the common readers into Taylor's method, Kirby somehow abbreviated and even omitted several crucial parts of Taylor's ideas, especially concerning to the inverse problems of perspective projection. Taylor's theory and Kirby's handbook reveal us that the development of linear perspective in European society entered a transitional phase in the 18th century. In the European tradition, linear perspective means a representational system to indicated the three-dimensional nature of space and the image of objects on the two-dimensional surface, using the central projection method. However, Taylor and following scholars converted linear perspective as a complete mathematical and abstract theory. Such a development was also due to concern and interest of contemporary artists toward new visions of infinite space and kaleidoscopic phenomena of visual perception.