• Journal of Hydrogen and New Energy
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• v.27 no.1
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• pp.121-126
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• 2016

Hydraulic performance of a micro-bubble pump has been analyzed by numerical simulation and experimental measurements. Flow recirculation apparatus between the pump inlet and outlet reserviors has been adopted to measure pump performance according to flow conditions sequentially. To analyze three-dimensional flow field in the micro-bubble pump, general analysis code, CFX, is employed. SST turbulence model is employed to estimate the eddy viscosity and compared the pump performance to k-${\varepsilon}$ model. Unstructured grids are used to represent a composite grid system including blade, casing and inlet casing. It is found that the numerical model used in the present study is effective to evaluate the pump performance. From the numerical simulation, low velocity region due to pressure loss is decreased where pump efficiency has maximum value. Detailed flow field inside the micro-bubble pump is also analyzed and compared.

• Earthquakes and Structures
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• v.13 no.4
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• pp.397-407
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• 2017

With the growing demand for metallic dampers in engineering practice, it is urgent to establish a reasonable approach to evaluating the mechanical performance of metallic dampers under seismic excitations. This paper introduces an effective method for parameter identification of the modified Bouc-Wen model and its application to evaluating the fatigue performance of metallic dampers (MDs). The modified Bouc-Wen model which eliminates the redundant parameter is used to describe the hysteresis behavior of MDs. Relations between the parameters of the modified Bouc-Wen model and the mechanical performance parameters of MDs are studied first. A modified Genetic Algorithm using real-integer hybrid coding with relative fitness as well as adaptive crossover and mutation rates (called RFAGA) is then proposed to identify the parameters of the modified Bouc-Wen model. A reliable approach to evaluating the fatigue performance of the MDs with respect to the Chinese Code for Seismic Design of Buildings (GB 50011-2010) is finally proposed based on the research results. Experimental data are employed to demonstrate the process and verify the effectiveness of the proposed approach. It is shown that the RFAGA is able to converge quickly in the identification process, and the simulation curves based on the identification results fit well with the experimental hysteresis curves. Furthermore, the proposed approach is shown to be a useful tool for evaluating the fatigue performance of MDs with respect to the Chinese Code for Seismic Design of Buildings (GB 50011-2010).

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.11
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• pp.25-39
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• 1992

Due to the data processing development by the computer, the early warning system recently has made a remarkable evolution in its functions and performance as a component of the communication and control system which is also supported by the computer communication and intelligence system. In this paper it is presented that a integrated data processing system is designed to integrate the information sent from the various radar systems which constitute an early warning system. The suggested system model of this paper is devided into two types of structures, the centralized model and the distributed model, according to the data processing algorithm. We apply the queueing theory to analyse the performance of the designed models and the OPNET system kernel to make the analysing program with C language. From the analysis of the queueing components by applying the analysis programs to the designed systems, we got the tendancies and characteristics of both models, that is, a fast data processing performance of the distributed model and a stable data processing capability of the centralized model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.711-725
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• 2013

A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

• International Journal of Quality Innovation
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• v.10 no.2
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• pp.77-96
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• 2009

Industry competition environment is not being meaning of internal and external distinction. This may be phenomenon of globalization progress. In this time, we wish to examine present level in our enterprise and also analyze cause relation between 7 category of China Excellence Performance model which is modified Malcolm Baldridge Model and compare with China enterprise by using the same questionnaire with China. It is right opportunity to obtain information by comparing China enterprise with the Korea. This questionnaire composition and contents used as it is questionnaire contents that enforce in 2007 in China CAQ. The survey on Korea enterprises' is 509 by KSA in 2008, China is surveyed 1679 by CAQ in 2007. In Korea 'leadership', 'strategy planning', 'customer and market', 'measurement, analysis and improvement' 'resources management' and 'process management' stronger than China, but in China 'performance results' is stronger than Korea.

• Korean Management Science Review
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• v.27 no.3
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• pp.87-98
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• 2010

In this paper, we drew upon IMP group's Interaction model to investigate the contributing impact of Inter-organizational system (IOS) on performance through enhancing inter-organizational relationship. While most extant literature studied the contribution of IOS from transaction efficiency perspective, the relational aspect of IOS contribution on the supply chain was addressed only by a few researches. As such, we intended to fill this gap of the IOS research stream. The conceptual model was developed, with reference to process theory, to analyze how the relational perspective could be applicable to IOS impact on performance. With the 129 sample data collected at the firm level,structural equation model using the LISREL was employed to validate the proposed research model. The empirical results supported the hypotheses such as the extent of IOS usage positively influences the interaction between the firms, which thereby enhances the extent of inter-firm partnership and performance. The results help better understanding the strategic use of IOS from relationship perspective.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.235-245
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• 2011

Early criticality prediction models that determine whether a design entity is fault-prone or not are becoming more and more important as software development projects are getting larger. Effective predictions can reduce the system development cost and improve software quality by identifying trouble-spots at early phases and proper allocation of effort and resources. Many prediction models have been proposed using statistical and machine learning methods. This paper builds a prediction model using Support Vector Machine(SVM) which is one of the most popular modern classification methods and compares its prediction performance with a well-known prediction model, BackPropagation neural network Model(BPM). SVM is known to generalize well even in high dimensional spaces under small training data conditions. In prediction performance evaluation experiments, dimensionality reduction techniques for data set are not used because the dimension of input data is too small. Experimental results show that the prediction performance of SVM model is slightly better than that of BPM and polynomial kernel function achieves better performance than other SVM kernel functions.

• ETRI Journal
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• v.29 no.4
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• pp.489-496
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• 2007

As pervasive computing is widely adopted and reliable networks are becoming more easily accessible, there is a rapidly growing need to develop a mechanism to analyze and evaluate the performance of ubiquitous environments. This paper presents an information processing model which characterizes a ubiquitous environment where a variety of pieces of information need to be exchanged among devices within a system. The proposed model not only provides analytical tools to evaluate the performance of devices, but also makes it possible to identify key factors in designing a ubiquitous environment. For illustrative purposes, a test bed is constructed and the performance of the system is assessed based on the proposed model.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1009-1012
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• 1999

An analytical performance model that can predict the performance of a superscalar processor employing multiple branch prediction is introduced. The model is based on the conditional independence probability and the basic block size of instructions, with the degree of multiple branch prediction, the fetch rate, and the window size of a superscalar architecture. Trace driven simulation is performed for the subset of SPEC integer benchmarks, and the measured IPCs are compared with the results derived from the model. As the result, our analytic model could predict the performance of the superscalar processor using multiple branch prediction within 6.6 percent on the average.