• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.8
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• pp.534-540
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• 2008

In this paper, the optimal bang-bang control problem of an air-conditioning system with slab thermal storage was formulated by gradient method. Furthermore, the numeric solution obtained by gradient method algorithm was compared with the analytic solution obtained on the basis of maximum principle. The control variable is changed uncontinuously at the start time of thermal storage operation in an analytic solution. On the other hand, it is showed as a continuous solution in a numeric solution. The numeric solution reproduces the analytic solution when a tolerance for convergence is applied severely. It is conceivable that gradient method is effective in the analysis of the optimal bang-bang control of the large-scale system like an air-conditioning system with slab thermal storage.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1289-1302
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• 2019

In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.3
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• pp.41-48
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• 2004

Finite field multiplication and division are important arithmetic operation in error-correcting codes and cryptosystems. The elements of the finite field GF($2^m$) are represented by bases with a primitive polynomial of degree m over GF(2). We can be easily realized for multiplication or computing multiplicative inverse in GF($2^m$) based on a normal basis representation. The number of product terms of logic function determines a complexity of the Messay-Omura multiplier. A normal basis exists for every finite field. It is not easy to find the optimal normal element for a given primitive polynomial. In this paper, the generating method of normal basis is investigated. The normal bases whose product terms are less than other bases for multiplication in GF($2^m$) are found. For each primitive polynomial, a list of normal elements and number of product terms are presented.

• Food Science and Preservation
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• v.17 no.1
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• pp.91-99
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• 2010

Extraction and bleaching of citric acid- and pepsin-soluble collagens (ASC and PSC, respectively) from shark (Isurus oxyrinchus) skin and muscle were investigated. The optimal sodium hydroxide concentration for extraction was 0.3 M and the optimal treatment time for removal of foreign material was 9 h. The optimal sodium hypochlorite level for bleaching of shark skin was 0.48% (w/v), and sodium hypochlorite was a better bleaching agent than acetone, hydrogen peroxide (10%, v/v), sodium sulfite (0.48%, w/v), sodium thiosulfate (0.48%, w/v), or sodium metabisulfite (0.48%, w/v). Optimal citric acid concentration and extraction time for ASC were 0.3 M and 72 h, respectively, whereas optimal conditions for extraction of PSC were treatment with 0.1 M citric acid containing 0.1% (w/v) pepsin for 24 h. Protein contents in ASSC (acid-soluble shark skin collagen), ASMC (acid-soluble shark meat collagen), PSSC (pepsin-soluble shark skin collagen), and PSMC (pepsin-soluble shark meat collagen) were 88.66%, 83.09%, 90.33%, and 84.81% (on a dry weight basis), respectively, similar to that of commercial marine collagen (88.86%). Net collagen contents of ASSC, ASMC, PSSC, and PSMC, calculated from hydroxyproline levels, were 70.31%, 25.70%, 83.09%, and 32.94%, respectively. The yields of freeze-dried ASSC, ASMC, PSSC,and PSMC were 57.22%, 53.85%, 23.28%, and 20.61%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3142-3150
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• 2013

Present research deals with an optimal design of the C-type frame of a desktop pressing machine to minimize its deformation which plays an important role in accuracy of the machine. Deformation pattern of the frame is analyzed by the finite element method. Design parameters are defined for the frame to derive an optimal design. Displacement and weight sensitivities of the parameters are analyzed using the method of the parametric study. On the basis of the response curves for the parameters, optimal designs of the frame are proposed. Effectiveness of the optimal design is verified by analyses in the viewpoint of the deformation and weight of the frame. Deformation of the optimized frame without increase of the weight is 87.5 % of the original frame.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.11
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• pp.886-897
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• 1990

This paper is proposed new optimal PWM scheme is based on a defined linear relationship between the successive pulsewidths of the PWM pattern. The calculation of the pulsewidths in the new PWM scheme is caried out without referring to the equations of CW and MW. With this scheme the PWM pattern for microprocessor controlled inverters can be composed easily by obtaining the optimal increment in sucessive pulsiwidths of the pattern. Furthmore, the harmonic level at the output of PWM inverter are always very low because this PWM pattern is selected on the basis of minimum THD. Theis scheme is applied to 1(Hp), three phase induction motor, and compared with conventional regular PWM scheme. The results of calculations and experiments show that new optimal PWM scheme could provide an effective generalized approach for minimization of harmonics in the VSI-PWM inverter.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2074-2079
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• 2018

Global state space's optimal policy is used for offline controller in the form of table by using Dynamic Programming. If an optimal policy table has a large amount of control data, it is difficult to use the system in a low capacity system. To resolve these problem, controller using the compressed optimal policy table is proposed in this paper. A DCT is used for compression method and the cosine function is used as a basis. The size of cosine function decreased as the frequency increased. In other words, an essential information which is used for restoration is concentrated in the low frequency band and a value of small size that belong to a high frequency band could be discarded by quantization because high frequency's information doesn't have a big effect on restoration. Therefore, memory could be largely reduced by removing the information. The compressed output is stored in memory of embedded system in offline and optimal control input which correspond to state of plant is computed by interpolation with Inverse DCT in online. To verify the performance of the proposed controller, computer simulation was accomplished with a one link inverted pendulum.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.135-142
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• 2012

In this paper, we proposed a new architecture called radial basis function-based polynomial neural networks classifier that consists of heterogeneous neural networks such as radial basis function neural networks and polynomial neural networks. The underlying architecture of the proposed model equals to polynomial neural networks(PNNs) while polynomial neurons in PNNs are composed of Fuzzy-c means-based radial basis function neural networks(FCM-based RBFNNs) instead of the conventional polynomial function. We consider PNNs to find the optimal local models and use RBFNNs to cover the high dimensionality problems. Also, in the hidden layer of RBFNNs, FCM algorithm is used to produce some clusters based on the similarity of given dataset. The proposed model depends on some parameters such as the number of input variables in PNNs, the number of clusters and fuzzification coefficient in FCM and polynomial type in RBFNNs. A multiobjective particle swarm optimization using crowding distance (MoPSO-CD) is exploited in order to carry out both structural and parametric optimization of the proposed networks. MoPSO is introduced for not only the performance of model but also complexity and interpretability. The usefulness of the proposed model as a classifier is evaluated with the aid of some benchmark datasets such as iris and liver.

• The KSFM Journal of Fluid Machinery
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• v.12 no.3
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• pp.7-12
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• 2009

In this paper, shape optimization based on three-dimensional flow analysis has been performed for impeller design of centrifugal compressor. To evaluate the objective function of an isentropic efficiency, Reynolds-averaged Navier-Stokes equations are solved with SST (Shear Stress Transport) turbulence model. The governing equations are discretized by finite volume approximations. The optimization techniques based on the radial basis neural network method are used for the optimization. Latin hypercube sampling as design of experiments is used to generate thirty design points within design space. Sequential quadratic programming is used to search the optimal point based on the radial basis neural network model. Four geometrical variables concerning impeller shape are selected as design variables. The results show that the isentropic efficiency is enhanced effectively from the shape optimization by the radial basis neural network method.

• Journal of Communications and Networks
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• v.12 no.6
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• pp.600-604
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• 2010

A method of width adaptation in the radial basis function network (RBFN) using stochastic gradient (SG) algorithm is introduced. Using Taylor's expansion of error signal and differentiating the error with respect to the step-size, the optimal time-varying step-size of the width in RBFN is derived. The proposed approach to adjusting widths in RBFN achieves superior learning speed and the steady-state mean square error (MSE) performance in nonlinear channel environment. The proposed method has shown enhanced steady-state MSE performance by more than 3 dB in both nonlinear channel environments. The results confirm that controlling over step-size of the width in RBFN by the proposed algorithm can be an effective approach to enhancement of convergence speed and the steady-state value of MSE.