• Journal of Astronomy and Space Sciences
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• v.28 no.2
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• pp.123-132
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• 2011

It is generally believed that the occurrence of a magnetic storm depends upon the solar wind conditions, particularly the southward interplanetary magnetic field (IMF) component. To understand the relationship between solar wind parameters and magnetic storms, variations in magnetic field polarity and solar wind parameters during magnetic storms are examined. A total of 156 storms during the period of 1997~2003 are used. According to the interplanetary driver, magnetic storms are divided into three types, which are coronal mass ejection (CME)-driven storms, co-rotating interaction region (CIR)-driven storms, and complicated type storms. Complicated types were not included in this study. For this purpose, the manner in which the direction change of IMF $B_y$ and $B_z$ components (in geocentric solar magnetospheric coordinate system coordinate) during the main phase is related with the development of the storm is examined. The time-integrated solar wind parameters are compared with the time-integrated disturbance storm time (Dst) index during the main phase of each magnetic storm. The time lag with the storm size is also investigated. Some results are worth noting: CME-driven storms, under steady conditions of $B_z$ < 0, represent more than half of the storms in number. That is, it is found that the average number of storms for negative sign of IMF $B_z$ (T1~T4) is high, at 56.4%, 53.0%, and 63.7% in each storm category, respectively. However, for the CIR-driven storms, the percentage of moderate storms is only 29.2%, while the number of intense storms is more than half (60.0%) under the $B_z$ < 0 condition. It is found that the correlation is highest between the time-integrated IMF $B_z$ and the time-integrated Dst index for the CME-driven storms. On the other hand, for the CIR-driven storms, a high correlation is found, with the correlation coefficient being 0.93, between time-integrated Dst index and time-integrated solar wind speed, while a low correlation, 0.51, is found between timeintegrated $B_z$ and time-integrated Dst index. The relationship between storm size and time lag in terms of hours from $B_z$ minimum to Dst minimum values is investigated. For the CME-driven storms, time lag of 26% of moderate storms is one hour, whereas time lag of 33% of moderate storms is two hours for the CIR-driven storms. The average values of solar wind parameters for the CME and CIR-driven storms are also examined. The average values of ${\mid}Dst_{min}{\mid}$ and ${\mid}B_{zmin}{\mid}$ for the CME-driven storms are higher than those of CIR-driven storms, while the average value of temperature is lower.

• Journal of Korean Academy of Nursing
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• v.41 no.4
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• pp.500-509
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• 2011

Purpose: Time-driven activity-based costing was applied to analyze the nursing activity cost and efficiency of a medical unit. Methods: Data were collected at a medical unit of a general hospital. Nursing activities were measured using a nursing activities inventory and classified as 6 domains using Easley-Storfjell Instrument. Descriptive statistics were used to identify general characteristics of the unit, nursing activities and activity time, and stochastic frontier model was adopted to estimate true activity time. Results: The average efficiency of the medical unit using theoretical resource capacity was 77%, however the efficiency using practical resource capacity was 96%. According to these results, the portion of non-added value time was estimated 23% and 4% each. The sums of total nursing activity costs were estimated 109,860,977 won in traditional activity-based costing and 84,427,126 won in time-driven activity-based costing. The difference in the two cost calculating methods was 25,433,851 won. Conclusion: These results indicate that the time-driven activity-based costing provides useful and more realistic information about the efficiency of unit operation compared to traditional activity-based costing. So time-driven activity-based costing is recommended as a performance evaluation framework for nursing departments based on cost management.

• Wind and Structures
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• v.39 no.2
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• pp.125-140
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• 2024

The simulation of non-stationary wind velocity is particularly crucial for the wind resistant design of slender structures. Recently, some data-driven simulation methods have received much attention due to their straightforwardness. However, as the number of simulation points increases, it will face efficiency issues. Under such a background, in this paper, a time-varying coherence matrix decomposition method based on Diagonal Proper Orthogonal Decomposition (DPOD) interpolation is proposed for the data-driven simulation of non-stationary wind velocity based on S-transform (ST). Its core idea is to use coherence matrix decomposition instead of the decomposition of the measured time-frequency power spectrum matrix based on ST. The decomposition result of the time-varying coherence matrix is relatively smooth, so DPOD interpolation can be introduced to accelerate its decomposition, and the DPOD interpolation technology is extended to the simulation based on measured wind velocity. The numerical experiment has shown that the reconstruction results of coherence matrix interpolation are consistent with the target values, and the interpolation calculation efficiency is higher than that of the coherence matrix time-frequency interpolation method and the coherence matrix POD interpolation method. Compared to existing data-driven simulation methods, it addresses the efficiency issue in simulations where the number of Cholesky decompositions increases with the increase of simulation points, significantly enhancing the efficiency of simulating multivariate non-stationary wind velocities. Meanwhile, the simulation data preserved the time-frequency characteristics of the measured wind velocity well.

• Journal of the Korean Society of Combustion
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• v.22 no.3
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• pp.23-28
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• 2017

The fuel and oxidizer mixing process in the shock tube driven section is simulated numerically. The boundary condition is set based on an shock tube experimental condition. The objective is to predict the gas mixing time for experiments. In the experiment, the amount of fuel to be injected is determined in advance. Then, according to duration of fuel injection, 5 cases with the same fuel mass but different fuel mass flow rate are simulated. After fuel is injected into the driven section, the fuel and air will be mixed with each other through convection and diffusion processes. The mixing time is predicted numerically for experiments.

• Journal of Ocean Engineering and Technology
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• v.18 no.5
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• pp.22-28
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• 2004

This study constructed a 3D real-time numerical model that predicts the water quality and movement characteristics of the inner bay, considering the characteristics of the wind-driven current and density current in estuaries, generated by the river discharge from the Hyeong-san river and oceanic water of the Eastern sea. The numerical model successfully calculated the seawater circulation current of Yeong-il Bay, using the input conditions oj the real-time tidal current, river discharge, and weather conditions during March 2001. This study also observed the wind-driven current and density current in estuaries that are effected by the seawater circulation pattern of the inner bay. We investigated and analyzed each impact factor, and its relationship to the water quality of Yeong-il bay.

• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.1-11
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• 2003

This paper is introduced about Design driven testing, for real time system, based on use case approaches, We focuses on a part of an extended use case approach for real time software development, which partitions design schema into layered design component architecture of functional components called "design component", We developed a use case action matrix to contain a collection of related scenarios each describing a specific variant of an executable sequence of use case action units, which reflected the behavioral properties of the real time system design, in this paper, we attempt to apply real time system with design driven testing with test plan metrics which is introduced which produces an ordering of this scenario set to enhance productivity and both promote and capitalize on test case reusability of existing scenarios.scenarios.

• Journal of the Korean Society of Combustion
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• v.21 no.4
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• pp.16-22
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• 2016

Pressure and temperature variations in a shock tube have been studied numerically by changing the diameter ratio of a driven part to a driver part. There are five cases where the adopted diameter ratios are 40%, 50%, 60%, 80%, and 100% respectively. The diameter of the driver part remains unchanged meanwhile the shock tube driven part diameter increases from 40% to 100% of the driver part. In the 100% ratio case, the driver part and driven parts have the same diameter of 66.9 mm. As the diameter ratio decreases, the pressure in the shock tube and available test time are increased.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.6
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• pp.849-861
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• 1995

In this paper, a new trace driven simulation algorithm is proposed to evaluate the bus traffic and the miss ration of the various sector cache memories, which have various sub-block sizes and block sizes and associativities and number of sets, with a single pass through an address trace. Trace-driven simulaton is usually used as a method for performance evaluation of sector cache memories, but it spends a lot of simulation time for simulating the diverse cache configurations with a long address trace. The proposed algorithm shortens the simulation time by evaluating the performance of the various sector cache configurations. which have various sub-block sizes and block sizes and associativities and number of sets , with a single pass through an address trace. Our simulation results show that the run times of the proposed simulation algorithm can be considerably reduced than those of existing simulation algorithms, when the proposed algorithm is miplemented in C language and the address traces obtained from the various sample programs are used as a input of trace-driven simulation.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1418-1432
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• 1996

In addition t improved availability, replication of data can enhance performance of distributed real-time transaction processing system by allowing transactions initiated at multiple node to be processed concurrently. To satisfy both the consistency and real-time constraints, it is necessary to integrate concurrency control and atomic commitment protocols with time-driven scheduling methods. blocking caused by existing concurrency control protocols is incompatible with time-driven scheduling because they cannot schedule transactions to meet given deadlines. To maintain consistency of replicated data and to provide a high degree of schedulability and predictability , the proposed time-driven scheduling methods integrate optimistic concurrency control protocols that minimize the duration of blocking and produce the serialization by reflecting the priority transactions. The atomicity of transactions is maintained to ensure successful commitment in distributed environment. Specific time-driven scheduling techniqueare discussed, together with an analysis of the performance of this scheduling.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.1-12
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• 1996

We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.