• International Journal of Fluid Machinery and Systems
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• v.8 no.2
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• pp.63-72
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• 2015

Water hammer phenomena are important issues for the design and the operation of hydro power plants. Especially, if several reversible pump-turbines are coupled hydraulically there may be strong unit interactions. The precise prediction of all relevant transients is challenging. Regarding a recent pump-storage project, dynamic measurements motivate an improved turbine modeling approach making use of a Thoma number dependency. The proposed method is validated for several transient scenarios and turns out to improve correlation between measurement and simulation results significantly. Starting from simple scenarios, this allows better prediction of more complex transients. By applying a fully automated simulation procedure broad operating ranges of the highly nonlinear system can be covered providing a consistent insight into the plant dynamics. This finally allows the optimization of the closing strategy and hence the overall power plant performance.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.211-214
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• 2007

With the recent development of spatial information technology, the relative importance of satellite image contents has increased to about 62%, the techniques related to satellite images have improved, and their demand is gradually increasing. Accordingly, a standard processing method for the whole process of collection from satellites to distribution of satellite images is required in many countries for efficient distribution of images and improvement of their utilization. This study presents the processor standardization technique for the preprocessing of satellite images including geometric correction, orthorectification, color adjustment, interpolation for DEM (Digital Elevation Model) production, rearrangement, and image data management, which will standardize the subjective, complex process and improve their utilization by making it easy for general users to use them

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.559-570
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• 2008

This paper proposes an improved particle swarm optimization named PSO with Controllable Random Exploration Velocity (PSO-CREV) behaving an additional exploration behavior. Different from other improvements on PSO, the updating principle of PSO-CREV is constructed in terms of stochastic approximation diagram. Hence a stochastic velocity independent on cognitive and social components of PSO can be added to the updating principle, so that particles have strong exploration ability than those of conventional PSO. The conditions and main behaviors of PSO-CREV are described. Two properties in terms of "divergence before convergence" and "controllable exploration behavior" are presented, which promote the performance of PSO-CREV. An experimental method based on a complex test function is proposed by which the proper parameters of PSO-CREV used in practice are figured out, which guarantees the high exploration ability, as well as the convergence rate is concerned. The benchmarks and applications on FCRNN training verify the improvements brought by PSO-CREV.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.106-113
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• 2018

Although deep learning methods of convolutional neural networks (CNNs) and long-/short-term memory (LSTM) are widely used for text categorization, they still have certain shortcomings. CNNs require that the text retain some order, that the pooling lengths be identical, and that collateral analysis is impossible; In case of LSTM, it requires the unidirectional operation and the inputs/outputs are very complex. Against these problems, we thus improved these traditional deep learning methods in the following ways: We created collateral CNNs accepting disorder and variable-length pooling, and we removed the input/output gates when creating bidirectional LSTMs. We have used four benchmark datasets for topic and sentiment classification using the new methods that we propose. The best results were obtained by combining LTSM regional embeddings with data convolution. Our method is better than all previous methods (including deep learning methods) in terms of topic and sentiment classification.

• Natural Product Sciences
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• v.19 no.2
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• pp.173-178
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• 2013

The protective effect of SAPP, an extract from a novel herbal complex, on acute liver injury was investigated using mouse animal model in this study. The content of total phenol in SAPP was increased at dose dependent manner. Consistent with the content of total phenol, SAPP showed the significant anti-oxidative effects on 1, 1-diphenyl-2-picrylhydrazyl (DPPH) method. Acute liver injury was induced by D-galactosamine (D-GalN) in mouse. Treatment with SAPP significantly reduced the level of alanine transaminase (ALT) and aspartate transaminase (AST) in serum. Histological observation revealed that whereas D-GalN treated mouse showed vacuolization of hepatocytes, sinusoidal dilation and congestion, loss of cell boundaries and ballooning degeneration, loss of architecture and cell necrosis, treatment with SAPP improved D-GalN-induced liver injury. These results suggest that SAPP shows protective effects against D-GalN-induced hepatotoxicity in vivo acute mouse model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.97-100
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• 2013

In this paper, we propose a detection method of the character rather than cursive, containing many components of the vertical and horizontal direction in complex background image. The characters have many dense corners but the background has few sparse corners. So we use harris corner detector and cluster the corners by using the position of the detected corners for detecting character regions. To merge or filter character regions, we analysis a histogram of gray image of character regions. In each improved region, we compare histograms of R, G, B channels to detect characters.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.84-90
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• 2014

This paper presents the results of three-dimensional face point cloud smoothing based on a modified anisotropic diffusion method. The focus of this research was to obtain a 3D face point cloud with a smooth texture and number of vertices equal to the number of vertices input during the smoothing process. Different from other methods, such as using a template D face model, modified anisotropic diffusion only uses basic concepts of convolution and filtering which do not require a complex process. In this research, we used 6D point cloud face data where the first 3D point cloud contained data pertaining to noisy x-, y-, and z-coordinate information, and the other 3D point cloud contained data regarding the red, green, and blue pixel layers as an input system. We used vertex selection to modify the original anisotropic diffusion. The results show that our method has improved performance relative to the original anisotropic diffusion method.

• Proceedings of the Korean Reliability Society Conference
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• 2001.06a
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• pp.455-462
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• 2001

We propose a new method to evaluate the network reliability which greatly reduces the intermediate steps toward calculations of maximum capacity flow by excluding unnecessary simple paths contained in the set of failure simple paths. By using signed simple paths and signed flow, we show that our method is more efficient than that of Lee and Park (2001a) in the number of generated composite paths and in the procedure for obtaining minimal success composite paths. Numerical examples are given to illustrate the use and the efficiency of the method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.2
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• pp.55-68
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• 2008

One of well known and much studied nonlinear matrix equations is the matrix polynomial which has the form $P(X)=A_0X^m+A_1X^{m-1}+{\cdots}+A_m$, where $A_0$, $A_1$, ${\cdots}$, $A_m$ and X are $n{\times}n$ complex matrices. Newton's method was introduced a useful tool for solving the equation P(X)=0. Here, we suggest an improved approach to solve each Newton step and consider how to incorporate line searches into Newton's method for solving the matrix polynomial. Finally, we give some numerical experiment to show that line searches reduce the number of iterations for convergence.

• Proceedings of the KIEE Conference
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• 1998.11c
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• pp.1033-1036
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• 1998

In this research project, two aspects of small signal stability are studied: improvement in Hessenberg method to compute the dominant electromechanical oscillation modes and siting FACTS devices to damp the low frequency oscillation. Fourier transform of transient stability simulation results identifies the frequencies of the dominant oscillation modes accurately. Inverse transformation of the state matrix with complex shift equal to the angular speed determined by Fourier transform enhances the ability of Hessenberg method to compute the dominant modes with good selectivity and small size of Hessenberg matrix. Any specified convergence tolerance is achieved using the iterative scheme of Hessenberg method. Siting FACTS devices such as SVC, STACOM, TCSC, TCPR and UPFC has been studied using the eigen-sensitivity theory of augmented matrix. Application results of the improved Hessenberg method and eigen-sensitivity to New England 10-machine 39-bus and KEPCO systems are presented.