• Journal of Microbiology and Biotechnology
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• v.12 no.3
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• pp.449-456
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• 2002

The objective of this study was to optimize medium composition of initial pH, tryptone, glucose, yeast extract, and mineral mixture for production of bacteriocin by Lactobacillus acidophilus ATCC 4356, using response surface methodology. A response surface approach including new statistical and plotting methods was employed for design and analysis of the experiment. An interiorly augmented central composite design was used as an experimental design. A normal-distribution log-link generalized linear model based on a subset fourth-order polynomial ($R^2$=0.94, Mean Error Deviance=0.0065) was used as an analysis model. This model was statistically superior to the full second-order polynomial-based generalized linear model ($R^2$=0.80, Mean Error Deviance=0.0140). Nonlinear programming determined the optimum composition of the medium as initial pH 6.35, typtone $1.21\%$, glucose $0.9\%$, yeast extract $0.65\%$, and mineral mixture $1.17\%$. A validation experiment confirmed that the optimized medium was comparable to the MRS medium in bacteriocin production, having the advantage of economy and practicality.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.413-415
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• 2001

In this paper, Polynomial Neural Networks(PNN) is proposed to overcome some problems, such as the conflict between overfitting and good generation, and low reliability and to control nonlinearity and unknown parameter of complex system. PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be generated according to the system environments. The performances depend on two factors, number of inputs and order of polynomials in each node directly. In most cases these factors are decided by the trial and error of designer so optimization is needed in deciding procedure of the factors. Evolutionary algorithm is applied to decide the factors in PNN. The study is illustrated with the aid of representative time series data for gas furnace process used widely for performance comparison, and shows the designed PNN architecture with evolutionary algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1060-1069
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• 2016

In this paper, we introduce the fingerprint recognition system based on Radial Basis Function Neural Network(RBFNN). Fingerprints are classified as four types(Whole, Arch, Right roof, Left roof). The preprocessing methods such as fast fourier transform, normalization, calculation of ridge's direction, filtering with gabor filter, binarization and rotation algorithm, are used in order to extract the features on fingerprint images and then those features are considered as the inputs of the network. RBFNN uses Fuzzy C-Means(FCM) clustering in the hidden layer and polynomial functions such as linear, quadratic, and modified quadratic are defined as connection weights of the network. Particle Swarm Optimization (PSO) algorithm optimizes a number of essential parameters needed to improve the accuracy of RBFNN. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. The performance evaluation of the proposed fingerprint recognition system is illustrated with the use of fingerprint data sets that are collected through Anguli program.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.537-539
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• 2007

Telemetry processing system requires minimum bit transition level in data streams to maintain a bit synchronization while receiving telemetry signal. PN code has a capability of providing the bit transition and is widely used in the packet communication of CCSDS. CCSDS PN code that generator polynomial is $h(x)=x^{8}+x^{7}+x^{5}+x^{3}+1$, and the random bit sequence that is generated from this polynomial is repeated with the cycle of 255 bits. As the resolution of satellite image increases, the size and transmission rate of data increases. To process of huge and bulky size of satellite image, the speed of CCSDS PN Processing is very important. This paper introduces the way of improving the CCSDS PN Processing speed through processing 128 bits at one time using the feature of cyclic structure that repeats after first 255 bytes by grouping the random bit sequence with 1 byte and Intel Streaming SIMD Extensions 2. And this paper includes the comparison data of processing speed between SSE2-applied implementation and not-applied implementation, in addition, the measured value of speed improvement.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.50-59
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• 2010

In this paper, two kind of free-form progressive addition lenses (PALs) were designed with Zernike polynomial surface and anatomically accurate finite presbyopic schematic eyes which have aspheric cornea, aspheric GRIN crystalline lens, aspheric retina, and Gaussian apodization factor. Geometrical and diffraction MTFs were used for the optimization process in sequence. 5th orders of Zernike polynomials were used for the evaluation of progression zones of the two examples. The target MTF was set as 0.22 at 100 lp/mm which satisfies the standard visual resolution. These examples were fabricated with a CNC diamond turning machine controlled by slow tool servo (STS). After polishing process, the wavefront aberrations were measured with a laser interferometer on the ten test points across the progression zones and then compared with three current commercially available PALs on the optical performance. Astigmatic aberrations of the examples are very lower than the three selected PALs and have more increased stabilized progressive intermediate zones and near zones. It is expected to give better clear and comfortable distance, intermediate and near visions than other conventional PALs and to improve the adaptability of presbyopic patients to PALs.

• Journal of the Korea Society of Computer and Information
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• v.20 no.11
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• pp.69-75
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• 2015

This paper suggests heuristic polynomial time algorithm for crew scheduling problem that is a kind of optimization problems. This problem has been solved by linear programming, set cover problem, set partition problem, column generation, etc. But the optimal solution has not been obtained by these methods. This paper sorts transit costs $c_{ij}$ to ascending order, and the task i and j crew paths are merged in case of the sum of operation time ${\Sigma}o$ is less than day working time T. As a result, we can be obtain the minimum number of crews $_{min}K$ and minimum transit cost $z=_{min}c_{ij}$. For the transit cost of specific number of crews $K(K>_{min}K)$, we delete the maximum $c_{ij}$ as much as the number of $K-_{min}K$, and to partition a crew path. For the 5 benchmark data, this algorithm can be gets less transit cost than state-of-the-art algorithms, and gets the minimum number of crews.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.437-444
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• 2007

The objective of this paper is to accommodate the existing motion-capture-based animation to small memories and low computing powers of mobile embedded systems. To use efficiently memories, we propose a paradigm in which a motion capture database is compressed on a PC and so-compressed motion capture database is decompressed little by little on mobile embedded systems and the decompressed data are eliminated right after used. As a compression method for this paradigm we propose an approach that compresses captured motion rendering parameters using a polynomial function fitting method. To enhance its performance we also propose an optimization method for the degree of the polynomial fitting function. Using so-obtained compression method we demonstrate motion-capture-based animation on commercial mobile embedded systems.

• Journal of Environmental Science International
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• v.30 no.5
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• pp.399-406
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• 2021

The dissolution of ionized gas in dielectric barrier plasma, similar to the principle of ozone generation, is a major performance-affecting factor. In this study, the plasma gas dissolving performance of a gas mixing-circulation plasma process was evaluated using an experimental design methodology. The plasma reaction is a function of four parameters [electric current (X₁), gas flow rate (X₂), liquid flow rate (X₃) and reaction time (X₄)] modeled by the Box-Behnken design. RNO (N, N-Dimethyl-4-nitrosoaniline), an indictor of OH radical formation, was evaluated using a quadratic response surface model. The model prediction equation derived for RNO degradation was shown as a second-order polynomial. By pooling the terms with poor explanatory power as error terms and performing ANOVA, results showed high significance, with an adjusted R² value of 0.9386; this indicate that the model adequately satisfies the polynomial fit. For the RNO degradation, the measured value and the predicted values by the model equation agreed relatively well. The optimum current, gas flow rate, liquid flow rate and reaction time were obtained for the highest desirability for RNO degradation at 0.21 A, 2.65 L/min, 0.75 L/min and 6.5 min, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.151-156
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• 2023

This paper deals with the optimization problem that decides the number of advertising for any media among various medium to maximize the perception quality index of new product meets the given budget and over the minimum reached people constraints. For this problem, there is only in used the mathematical approach as linear programming (LP) software package and has been unknown the polynomial time algorithm. In this paper we suggest the heuristic algorithm with O(nlog n)time complexity to solve the optimal solution for this problem. This paper suggests the evaluation index to select the media most economically-efficient way and decides the media and the number of advertisement. While we utilize Excel, the proposed algorithm can be get the same optimal solution as LP for experimental data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.1
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• pp.39-47
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• 2005

In this paper, a method of station keeping strategy using relative orbital motion and numerical optimization technique is presented for geostationary spacecraft. Relative position vector with respect to an ideal geostationary orbit is generated using high precision orbit propagation, and compressed in terms of polynomial and trigonometric function. Then this relative orbit model is combined with optimization scheme to propose a very efficient and flexible method of station keeping planning. Proper selection of objective and constraint functions for optimization can yield a variety of station keeping methods improved over the classical ones. Results from the nonlinear simulation have been shown to support such concept.