• Health Policy and Management
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• v.14 no.1
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• pp.89-120
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• 2004

The purpose of this empirical study is to test hypotheses in order to identify the cost drivers that drive indirect costs in general hospitals in Korea. In various cases' studies, it has been suggested that overhead costs are driven by volume and complexity variables, how they are structurally related and how the cost impacts of these variables can be A unique feature of the research is the treatment of complexity as an endogenous variable. It is hypothesized that level of hospital complexity in terms of the number of services provided(i.e., “breath" complexity) and the intensity of individual estimated in practice. overhead services(ie., “depth" complexity) are simultaneous determined with the level of costs needed to support the complexity. Data used in this study were obtained from the Database of Korean Health Industry Development Institute, Health Insurance Review Agency and analyzed using simultaneous equation model, path model. The results found those volume and complexity variables are all statistically signi-ficance drivers of general hospital overhead costs. This study has documented that the level of service complexity is a significant determinant of hospital overhead costs, caution should be exercised in interpreting this as supportive of the cost accounting procedures associated with ABC. with ABC.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.4
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• pp.89-97
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• 2003

Using inference models developed for estimation of the parameters necessary to implement the Runoff Block of the Stormwater Management Model (SWMM), a number of alternative inference scenarios were developed to assess the influence of inference model complexity and structure on the calibration of the catchment modelling system. These inference models varied from the assumption of a spatially invariant value (catchment average) to spatially variable with each subcatchment having its own unique values. Fur-thermore, the influence of different measures of deviation between the recorded information and simulation predictions were considered. The results of these investigations indicate that the model performance is more influenced by model structure than complexity, and control parameter values are very much dependent on objective function selected as this factor was the most influential for both the initial estimates and the final results.

• Journal of computational fluids engineering
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• v.11 no.3 s.34
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• pp.1-7
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• 2006

Euler and Navier-Stokes flow analyses for helicopter rotor in hover were performed as low and high fidelity analysis models respectively for the future multidisciplinary design optimization(MDO). These design-oriented analyses possess several attributes such as variable complexity, sensitivity-computation capability and modularity which analysis models involved in MDO are recommended to provide with. To realize PC-based analyses for both fidelity models, reduction of flow domain was made by appling farfield boundary condition based on 3-dimensional point sink with simple momentum theory and also periodic boundary condition in the azimuthal direction. Correlations of thrust, torque and their sensitivities between low and high complexity models were tried to evaluate the applicability of these analysis models in MDO process. It was found that the low-fidelity Euler analysis model predicted inaccurate sensitivity derivatives at relatively high angle of attack.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.29-36
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• 2016

Tensairity girder is a light weight inflatable fabric structural concept which can be used in road emergency transportation. It uses low pressure air to stabilize compression elements against buckling. With the purpose of obtaining the comprehensive target of minimum deflection and weight under ultimate load, the cross-section and the inner pressure of tensairity girder was optimized in this paper. The Variable Complexity Modeling (VCM) method was used in this paper combining the Kriging approximate method with the Finite Element Analysis (FEA) method, which was implemented by ABAQUS. In the Kriging method, the sample points of the surrogate model were outlined by Design of Experiment (DOE) technique based on Optimal Latin Hypercube. The optimization framework was constructed in iSIGHT with a global optimization method, Multi-Island Genetic Algorithm (MIGA), followed by a local optimization method, Sequential Quadratic Program (SQP). The result of the optimization gives a prominent conceptual design of the tensairity girder, which approves the solution architecture of VCM is feasible and efficient. Furthermore, a useful trend of sensitivity between optimization variables and responses was performed to guide future design. It was proved that the inner pressure is the key parameter to balance the maximum Von Mises stress and deflection on tensairity girder, and the parameters of cross section impact the mass of tensairity girder obviously.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.181-195
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• 2006

In recent years, increasing attention has been paid on how to manage a successful relationships between the receiver and provider of the Information Systems(IS) outsourcing services. This study explores the sources of influence for successful outsourcing relationships. Based on the Jaworski's control combination model for marketing, we (1) propose a management combination model of outsourcing relationships where trust is introduced as an intervening variable and outsourcing compleyity as a moderating variable, (2) test this model using a sample of 94 outsourcing projects in 36 organizations that have outsourced there IS functions to external service providers. The results indicated several significant findings. First, the deployment of management mechanism such as contract mechanism and trust building has a significant effect on the outsourcing success through trust only. Second, complexity of outsourcing activities has a moderating effect on relationship management combinations.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.93-98
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• 2009

In this paper, we propose a new VSS-NLMS algorithm through a simple modification of the conventional NLMS algorithm, which leads to a low complexity algorithm with enhanced performance. The step size of the proposed algorithm becomes smaller as the error signal is getting orthogonal to the input vector. We also show that the proposed algorithm is an approximated normalized version of the KZ-algorithm and requires less computation than the KZ-algorithm. We carried out a performance comparison of the proposed algorithm with the conventional NLMS and other VSS algorithms using an adaptive channel equalization model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.

• Computers and Concrete
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• v.6 no.3
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• pp.203-223
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• 2009

Regression analysis (RA) can establish an explicit formula to predict the strength of High-Performance Concrete (HPC); however, the accuracy of the formula is poor. Back-Propagation Networks (BPNs) can establish a highly accurate model to predict the strength of HPC, but cannot generate an explicit formula. Genetic Operation Trees (GOTs) can establish an explicit formula to predict the strength of HPC that achieves a level of accuracy in between the two aforementioned approaches. Although GOT can produce an explicit formula but the formula is often too complicated so that unable to explain the substantial meaning of the formula. This study developed a Backward Pruning Technique (BPT) to simplify the complexity of GOT formula by replacing each variable of the tip node of operation tree with the median of the variable in the training dataset belonging to the node, and then pruning the node with the most accurate test dataset. Such pruning reduces formula complexity while maintaining the accuracy. 404 experimental datasets were used to compare accuracy and complexity of three model building techniques, RA, BPN and GOT. Results show that the pruned GOT can generate simple and accurate formula for predicting the strength of HPC.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1604-1613
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• 2018

The paper presents the equivalent circuit of an induction machine (IM) model which includes fundamental stray load and iron losses. The corresponding equivalent resistances are introduced and modeled as variable with respect to the stator frequency and flux. Their computation does not require any tests apart from those imposed by international standards, nor does it involve IM constructional details. In addition, by the convenient positioning of these resistances within the proposed equivalent circuit, the order of the conventional IM model is preserved, thus restraining the inevitable increase of the computational complexity. In this way, a compromise is achieved between the complexity of the analyzed phenomena on the one hand and the model's practicability on the other. The proposed model has been experimentally verified using four IMs of different efficiency class and rotor cage material, all rated 1.5 kW. Besides enabling a quantitative insight into the impact of the stray load and iron losses on the operation of mains-supplied and vector-controlled IMs, the proposed model offers an opportunity to develop advanced vector control algorithms since vector control is based on the fundamental harmonic component of IM variables.

• Korea Trade Review
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• v.47 no.5
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• pp.21-37
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• 2022

Baltic Dry Index (BDI) is difficult to forecast because of the high volatility and complexity. To improve the BDI forecasting ability, this study apply Bayesian variable selection method with a large number of predictors. Our estimation results based on the BDI and all predictors from January 2000 to September 2021 indicate that the out-of-sample prediction ability of the ADL model with the variable selection is superior to that of the AR model in terms of point and density forecasting. We also find that critical predictors for the BDI change over forecasts horizon. The lagged BDI are being selected as an key predictor at all forecasts horizon, but commodity price, the clarksea index, and interest rates have additional information to predict BDI at mid-term horizon. This implies that time variations of predictors should be considered to predict the BDI.

• ETRI Journal
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• v.16 no.3
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• pp.27-41
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• 1994

This paper provides a performance study of multistage interconnection networks in packet switching environment. In comparison to earlier work, the model is more extensive - it includes several parameters such as multiple-packet messages, variable buffer size, and wait delay at a source. The model is also uniformly applied to several representative networks and thus provides a basis for fair comparison as well as selection of optimal values for parameters. The complexity of the model required use of simulation. However, a partial analytical model is provided to measure the congestion in a network.