• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.449-457
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• 2017

In this paper, we analyze the security and performance of the Quantis Quantum random number generator in terms of cryptography through experiments. The Quantis' post-processing is designed to output full-entropy via bit-matrix-vector multiplication based on mathematical background, and we used the min-entropy estimating test of NIST SP 800-90B so as to verify whether the output is full-entropy. Quantis minimizes the effect on the random bit rate by using an optimization technique for bit-matrix-vector multiplication, and compared the performance to conditioning functions of NIST SP 800-90B by measuring the random bit rate. Also, we have distinguished what is in Quantis' post-processing to the standard model of NIST in USA and BSI in Germany, and in case of applying Quantis to cryptographic systems in accordance with the CMVP standard, it is recommended to use the output of Quantis as the seed of the approved DRBG.

• Journal of Microbiology and Biotechnology
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• v.22 no.2
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• pp.199-206
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• 2012

Naturally immobilized tannase (tannin acyl hydrolase, E.C. 3.1.1.20) has many advantages, as it avoids the expensive and laborious operation of isolation, purification, and immobilization, plus it is highly stable in adverse pH and temperature. However, in the case of cell-associated enzymes, since the enzyme is associated with the biomass, separation of the pure biomass is necessary. However, tannic acid, a known inducer of tannase, forms insoluble complexes with media proteins, making it difficult to separate pure biomass. Therefore, this study optimizes the production of cell-associated tannase using a "protein-tannin complex" free media. An exploratory study was first conducted in shake-flasks to select the inducer, carbon source, and nitrogen sources. As a result it was found that gallic acid induces tannase synthesis, a tryptose broth gives higher biomass, and lactose supplementation is beneficial. The medium was then optimized using response surface methodology based on the full factorial central composite design in a 3 l bioreactor. A $2^3$ factorial design augmented by 7 axial points (${\alpha}$ = 1.682) and 2 replicates at the center point was implemented in 17 experiments. A mathematical model was also developed to show the effect of each medium component and their interactions on the production of cell-associated tannase. The validity of the proposed model was verified, and the optimized medium was shown to produce maximum cell-associated tannase activity of 9.65 U/l, which is 93.8% higher than the activity in the basal medium, after 12 h at pH 5.0, $30^{\circ}C$. The optimum medium consists of 38 g/l lactose, 50 g/l tryptose, and 2.8 g/l gallic acid.

• Journal of Biosystems Engineering
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• v.34 no.2
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• pp.95-105
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• 2009

A method was proposed which employed control of the drop location of fertilizer particles on a spinner disc to optimize the spread pattern uniformity. The system contained an optical sensor as a feedback mechanism, which measured discharge velocity and location, as well as particle diameters to predict a spread pattern of a single disc. Simulations showed that the feed gate adaptation algorithm produced high quality patterns for any given application rate in the dual disc spreader. The performance of the feed gate control method was assessed using data collected from a Sulky spinner disc spreader. The results showed that it was always possible to find a spread pattern with an acceptable CV lower than 15%, even though the spread pattern was obtained from a rudimentary flat disc with straight radial vanes. A mathematical optimization method was used to find the initial parameter settings for a specially designed experimental spreading arrangement, which included the feed gate control system, for a given flow rate and swath width. Several experiments were carried out to investigate the relationship between the gate opening and flow rate, disc speed and particle velocity, as well as disc speed and predicted landing location of fertilizer particles. All relationships found were highly linear ($r^2$ > 0.96), which showed that the time-of-flight sensor was well suited as a feedback sensor in the rate and uniformity controlled spreading system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1772-1781
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• 2017

In this study, the design methodology for alleviating the overfitting problem of Polynomial Neural Networks(PNN) is realized with the aid of two kinds techniques such as L2 regularization and Sum of Squared Coefficients (SSC). The PNN is widely used as a kind of mathematical modeling methods such as the identification of linear system by input/output data and the regression analysis modeling method for prediction problem. PNN is an algorithm that obtains preferred network structure by generating consecutive layers as well as nodes by using a multivariate polynomial subexpression. It has much fewer nodes and more flexible adaptability than existing neural network algorithms. However, such algorithms lead to overfitting problems due to noise sensitivity as well as excessive trainning while generation of successive network layers. To alleviate such overfitting problem and also effectively design its ensuing deep network structure, two techniques are introduced. That is we use the two techniques of both SSC(Sum of Squared Coefficients) and $L_2$ regularization for consecutive generation of each layer's nodes as well as each layer in order to construct the deep PNN structure. The technique of $L_2$ regularization is used for the minimum coefficient estimation by adding penalty term to cost function. $L_2$ regularization is a kind of representative methods of reducing the influence of noise by flattening the solution space and also lessening coefficient size. The technique for the SSC is implemented for the minimization of Sum of Squared Coefficients of polynomial instead of using the square of errors. In the sequel, the overfitting problem of the deep PNN structure is stabilized by the proposed method. This study leads to the possibility of deep network structure design as well as big data processing and also the superiority of the network performance through experiments is shown.

• Journal of Welding and Joining
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• v.30 no.4
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• pp.31-37
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• 2012

In recent years, a demand for precision-welding is increasing in wide industrial fields for getting a high quality welded structures. Although laser welding is commonly used for precision-welding, gas tungsten arc (GTA) welding is also attempted as a precision-welding due to the cost benefit. However, welding heat causes an uneven temperature distribution leading to welding deformation. Since it causes geometric errors and degrades product quality, welding distortion recently rises as an important issue in the field of automobile parts. To control welding deformation, it is needed to design in shapes that can maximize stiffness against deformation during welding; control the welding sequence; minimize heat input; and weld allowing reverse deformation; etc. Thus it is necessary to find the one, among such approaches, that can minimize the deformation range by mathematical analysis and understand how effective it would be when it is actually used in industrial fields. This study performs analyses by numerical calculations and experiments for the De-Tent Lever, one of transmission part that requires precision the most among automobile parts, as the subject of experiment. Decrease in welding deformation is required for this part, since there is currently a trouble in guaranteeing precision due to angular deformation by welding between boss and plate. Finally the ways to minimize welding deformation has been suggested in this study through analyses on it.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.799-802
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• 2008

General behaviors based on hydraulic characteristics of natural streams and channels have been recently analyzed and developed via various numerical models. However in the states of natural hydraulics, an experimental research must be performed simultaneously with the mathematical analysis due to effects of hydraulic properties such as meander, sediment, and so on. In this study based on 2-D advection-dispersion equation, flow and tracer experiments were performed in the S-curved meandering laboratory channel with a rectangular cross-section. The channel was equipped with instrument carriages which was equipped with an auto-traversing system to be used with velocity measuring sensors throughout the depth and breadth of the flow field. To measure concentration distribution of the salt solution was adjusted to that of the flume water by adding methanol and a red dye (KMnO4) was added to aid the visualization of the tracer cloud, the tracer was instantaneously injected into the flow as a full-depth vertical line source by the instantaneous injector and the initial concentration of the tracer was 100,000 mg/l. The secondary current as well as the primary flow pattern was analyzed to investigate the flow distribution in the meandering channels. The velocity distribution of the primary flow for all cases skewed toward the inner bank at the first bend, and was almost symmetric at the crossovers, and then shifted toward the inner bank again at the next alternating bend. Thus, one can clearly notice that the maximum velocity occurs taking the shortest course along the channel, irrespective of the flow conditions. The result of the tracer tests shows that pollutant clouds are spreading following the maximum velocity lines in each cases with various mixing patterns like superposition, separation, and stagnation of pollutant clouds. Flow characteristics in each cases performed in this study can be compared with tracer dispersion characteristics with using evaluation of longitudinal and transverse dispersion coefficients(LDC, TDC). As expected, LDC and TDC in meandering parts have been evaluated with increasing distribution and straight parts have effected to evaluate minimum of LDC and TDC due to symmetric flow patterns and attenuations of secondary flow.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.77-84
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• 2002

An cluster system used consist of large number of running servers, one has the problem that does the low availability occured by the high chance of the server failures and it is difficult to provide occuring software aging. In this paper, running cluster web servers consists of n primary servers and k backup servers, based on the operational parameters such as number of running primary servers, number of backup severs, rejuvenation period, rejuvenation time, failure rate of sewers, repair rate of servers, unstable rate of servers. We calculate to evaluate the rejuvenation policy such steady-state probabilities, downtime, availability, and downtime cost. We validate the solutions of mathematical model by experiments based on various operation parameters and find that the software rejuvenation method can be adopted as prventive fault tolerant technique for stability of system. The failure rate and unstable rate of the servers are essential factors for decision making of the rejuvenation policies.

• Metals and materials international
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• v.24 no.6
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• pp.1193-1201
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• 2018

Dilatometry is a useful technique to obtain experimental data concerning transformation. In this paper, a dilation conversional model was established to calculate carbides fraction in AISI H13 hot-work tool steel based on the measured length changes. After carbides precipitation, the alloy contents in the matrix changed. In the usual models, the content of carbon atoms after precipitation is considered as the only element that affects the lattice constant and the content of the alloy elements such as Cr, Mo, Mn, V are often ignored. In the model introduced in this paper, the alloying elements (Cr, Mo, Mn, V) changes caused by carbides precipitation are incorporated. The carbides were identified using scanning electron microscope and transmission electron microscope. The relationship between lattice constant of carbides and temperature are measured by high-temperature X-ray diffraction. The results indicate that the carbides observed in all specimens cooled at different rates are V-rich MC and Cr-rich $M_{23}C_6$, and most of them are V-rich MC, only very few are Cr-rich $M_{23}C_6$. The model including the effects of substitutional alloying elements shows a good improvement on carbides fraction predictions. In addition, lower cooling rate advances the carbides precipitation for AISI H13 specimens. The results between experiments and mathematical model agree well.

• Geomechanics and Engineering
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• v.17 no.1
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• pp.31-45
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• 2019

In this study the spatial variability of soils is substantiated physically and numerically by using random field theory. Heterogeneous samples are fabricated by combining nine homogeneous soil clusters that are assumed to be elements of an adopted random field. Homogeneous soils are prepared by mixing different percentages of kaolin and bentonite at water contents equivalent to their respective liquid limits. Comprehensive characteristic laboratory tests were carried out before embarking on direct shear experiments to deduce the basic correlations and properties of nine homogeneous soil clusters that serve to reconstitute the heterogeneous samples. The tests consist of Atterberg limits, and Oedometric and unconfined compression tests. The undrained shear strength of nine soil clusters were measured by the unconfined compression test data, and then correlations were made between the water content and the strength and stiffness of soil samples with different consistency limits. The direct shear strength of heterogeneous samples of different stochastic properties was then evaluated by physical and numerical modelling using FISH code programming in finite difference software of $FLAC^{3D}$. The results of the experimental and stochastic numerical analyses were then compared. The deviation of numerical simulations from direct shear load-displacement profiles taken from different sources were discussed, potential sources of error was introduced and elaborated. This study was primarily to explain the mathematical and physical procedures of sample preparation in stochastic soil mechanics. It can be extended to different problems and applications in geotechnical engineering discipline to take in to account the variability of strength and deformation parameters.