• Journal of the Society of Naval Architects of Korea
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• v.30 no.1
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• pp.125-133
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• 1993

Most studies on the vibration analysis of a beam-column with ends elastically restrained and various intermediate constraints have been based on the Euler beam theory, which is inadequate for beam-columns of low slenderness ratios. In this paper, analytical methods for vibration and dynamic sensitivity of a Timoshenko beam-column with ends elastically restrained and various intermediate constraints are presented. Firstly, an exact solution method is shown. Since the exact method requires considerable computational effort, a Rayleigh-Ritz analysis is also investigated. In the latter two kinds of trial functions are examined for comparisions : eigenfunctions of the base system(the system without intermediate constraints) and polynomials having properties corresponding to the eigenfunctions of the base system. The results of some numerical Investigations show that the Rayleigh-Ritz analysis using the characteristic polynomials is competitive with the exact solutions in accuracy, and that it is much more efficient in computations than using the eigenfunctions of the base system, especially in the dynamic sensitivity analysis. In addition, the prediction of the changes of natural frequencies due to the changes of design variables based on the first order sensitivity is in good agreements with that by the ordinary reanalysis as long as the changes of design variables are moderate.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.5 s.335
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• pp.23-30
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• 2005

In the construction of an extension field, there is a connection between the polynomial multiplication method and the degree of polynomial. The existing methods, KO and MSK methods, efficiently reduce the complexity of coefficient-multiplication. However, when we construct the multiplication of an extension field using KO and MSK methods, the polynomials are padded with necessary number of zero coefficients in general. In this paper, we propose basic properties of KO and MSK methods and algorithm that can reduce coefficient-multiplications. The proposed algorithm is more reducible than the original KO and MSK methods. This characteristic makes the employment of this multiplier particularly suitable for applications characterized by specific space constrains, such as those based on smart cards, token hardware, mobile phone or other devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2283-2291
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• 2010

The shrinking generator which is one of clock-controlled generator is a very simple generator with good cryptographic properties. A nonlinear sequence generator based on two 90/150 maximum length cellular automata can generate pseudorandom sequences at each cell of cellular automata whose characteristic polynomials are same. The nonlinear sequence generated by cellular automata has a larger period and a higher linear complexity than shrunken sequence generated by LFSRs. In this paper we analyze shrunken-interleaved sequence based on 90/150 maximum length cellular automata. We show that the sequence generated by nonlinear sequence generator based on cellular automata belongs to the class of interleaved sequence. And we give an effective algorithm for reconstructing unknown bits of output sequence based on intercepted keystream bits.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.889-897
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• 1999

This paper deals with a problem searching a target transfer function to meet the time-domain specifications for feedback system with given plant transfer function. For the Type I system, we first define three forms of transient response to unit step input, which are named by F, M, S-type. These are charaacterized as follows ; F-type has fast initial response and slow approach to the steady sate after reaching at 90% of the steady state value, S-type has slow initial response but fast approach to the steady state, and M-type is denoted by highly smooth response between F-type and S-type. Three prototypes corresponding to each form are proposed, time. For the order $n{\geq}4$, after determining admissible root structures of target characteristic polynomials empirically and expressing such polynomial coefficients by using special parameters ${\gamma}_i$ and $\epsilon$, the optimal prototypes that minimize the integral of the squared of the modified errors(ISME) have been obtained. Since the step responses of these prototypes have almost same wave forms irrespective to the order, the desired settling time or the rise time can be converted into the equibalent time constant $\tau$ and thus it is easy to obtain a target transfer function. It is shown through a design example that the present prototype is very useful for meeting the time-domain specifications and has been compared with different methods with a viewpoint of pertinence.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.563-571
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• 2010

The GPS satellite has three or four atomic clocks that consist of cesiums and rubidiums and the NANU messages can be used to identify the kind of the onboard atomic clock because they classify the clock type on a daily basis. In this study, for long-term analysis of the GPS satellite clock behavior, we extracted satellite clock errors for every PRN from years 2001 through 2009 using the SP3 files that are provided by the IGS. As a result, the cesium clock offsets usually have a linear trend of drifting. On the other hand, rubidium offsets show curvilinear variations in general, even though they cannot be represented as anyone specific polynomial function. For short-term analysis, we extracted satellite clock errors for each PRN for a week-long period using the CLK files that are also provided by the IGS and curve-fitted them with first-order and second-order polynomial functions. In cases of cesium clock errors, they were well-represented by first-order polynomial functions and rubidium clock errors were similar with second-order polynomials. However, some of rubidium clock errors could not be represented as any polynomial fitting function. To analyze the characteristic of GPS satellite by each block and atomic clock, we applied Modified Allan Deviation criterion to the dataset from years 2007 and 2010. We found that the Modified Allan Deviation characteristics changed significantly according the block and atomic clock type.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.