• The Korean Journal of Food And Nutrition
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• v.29 no.3
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• pp.371-381
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• 2016

The present study investigated the effects of processing parameters such as time (10, 20, 30, 40 min), pressure (25, 50, 75, 100 MPa), and the salinity of brine (0~10%(w/v)) on jacopever (Sebastes schlegeli Hilgendorf) in order to establish optimization of the three factors using a high hydrostatic pressure (HHP) machine. To do so, it analyzed the quality characteristics of volatile basic nitrogen (VBN), trimethylamine (TMA), total bacterial counts, dynamic viscoelasticities, and differential scanning calorimetry (DSC) properties. First, when the time increased to 40 mins, by 10 min intervals, the total bacterial counts in HHP groups under $25^{\circ}C$, 100 MPa, and 4%(w/v) brine were significantly decreased except for the first 10 min in comparison to the control group. In regards to DSC properties, the onset temperature ($T_O$) of the first endothermal curve was significantly reduced. Second, when the pressure level increased up to 100 MPa by 25 MPa increments, the total bacterial counts in the HHP samples significantly decreased for 20 min at 50 MPa or higher. As the pressure increased, G', G" and the slope of tan ${\delta}$ decreased (except for 50 MPa). Third, in regards to the salinities of brine, when the HHP processing was treated at 100 MPa, $25^{\circ}C$ for 20 min, the total bacterial counts of all the HHP groups significantly decreased in comparison to those of the control group. A significant difference was found in the enthalpy of the second endothermic curve in the 6~10%(w/v) (except 7%(w/v)) HHP groups. Therefore, the salinity of the immersion water under the HHP condition was appropriate when it was lower than 6%(w/v). The present study demonstrated that the optimum parameter condition according to/under the condition of the microbial inhibition and economic effects using an HHP would be the reaction time for 20 min, reaction pressure at 100 MPa, and the salinity of 4%(w/v) brine.

• Journal of Distribution Research
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• v.5 no.2
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• pp.49-68
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• 2001

In this chapter, we summarize the results on the optimal location selection and present limitation and direction of research. In order to reach the objective, this study selected and tested the interaction model which obtains the value of co-ordinates on location selection through the optimization technique. This study used the original variables in the model, but the results indicated that there is difference in reality. In order to overcome this difference, this study peformed market survey and found the new variables (first data such as price, quality and assortment of goods, and the second data such as aggregate area, and area of shop, and the number of cars in the parking lot). Then this study determined an optimal variable by empirical analysis which compares an actual value of market share in 1988 with the market share yielded in the model. However, this study found the market share in each variables does not reflect a reality due to an assumption of λ-value in the model. In order to improve this, this study performed a sensitivity analysis which adds the λ value from 1.0 to 2.9 marginally. The analyzed result indicated the highest significance with the market share ratio in 1998 at λ of 1.0. Applying the weighted value to a variable from each of the first data and second data yielded the results that more variables from the first data coincided with the realistic rank on sales. Although this study have some limits and improvements, if a marketer uses this extended model, more significant results will be produced.

• Progress in Medical Physics
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• v.18 no.1
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• pp.35-41
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• 2007

In this work practical considerations of a pulsed arterial spin labeling MRI are presented to reliable multi-slice perfusion measurements In the human brain. Three parameters were considered in this study. First, In order to improve slice profile and Inversion efficiency of a labeling pulse a high power Inversion pulse of adiabatic hyperbolic secant was designed. A $900^{\circ}$ rotation of the flip angle was provided to make a good slice profile and excellent Inversion efficiency. Second, to minimize contributions of a residual magnetization be4ween Interleaved scans of control and labeling we tested three different conditions which were applied 1) only saturation pulses, 2) only spotter gradients, and 3) combinations of saturation pulses and spotter gradients Applications of bo4h saturation pulses and spoiler gradients minimized the residual magnetization. Finally, to find a minimum gap between a tagged plane and an imaging plane we tested signal changes of the subtracted image between control and labeled Images with varying the gap. The optimum gap was about 20mm. In conclusion, In order to obtain high quality of perfusion Images In human brain It Is Important to use optimum parameters. Before routinely using In clinical studios, we recommend to make optimizations of sequence parameters.

• Applied Biological Chemistry
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• v.42 no.1
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• pp.58-62
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• 1999

Method to access qualities of brown sauce and optimize its cooking conditions was studied by sensory evaluation and response surface methodology. Cooks of an hotel, sauce experts, were selected as sensory panelists, and the brown sauce cooking conditions practically used in an hotel were adopted to prepare sauce samples for the sensory test. The cooking conditions were designed with two factors, i.e., one factor of roux contents with three levels and the other factor of cooking times with three levels, which were known as most important in sauce cooking. Sensory acceptance evaluation with intensity 7 grades was applied for several sauce attributes such as color, flavour, viscosity, taste and overall. Ability of each panel to perceive the differences between the brown sauces prepared under different cooking conditions was judged, and only data of the 9 panelists proved as reliable among the 12 panelists were reflected. The acceptances by different cooking conditions were found to be in the order of 11 > 9 > 13% roux contents and 8 > 9 > 7 hr cooking times. Response surface methodology was treated with second-order model on the sensory data and the optimum cooking conditions with the highest acceptances were $10.3{\sim}10.8%$ roux content and 8 hr cooking time.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.5
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• pp.92-103
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• 2015

Box-Wilson experimental design method, known as central composite design, is the design of any information-gathering exercises where variation is present. This method was devised to gather as much data as possible in spite of the low design cost. This method was employed to model the effect of mixing factors on several performances of 60 MPa high strength self compacting concrete and to numerically calculate the optimal mix proportion. The nonlinear relations between factors and responses of HSSCC were approximated in the form of second order polynomial equation. In order to characterize five performances like compressive strength, passing ability, segregation resistance, manufacturing cost and density depending on five factors like water-binder ratio, cement content, fine aggregate percentage, fly ash content and superplasticizer content, the experiments were made at the total 52 experimental points composed of 32 factorial points, 10 axial points and 10 center points. The study results showed that Box-Wilson experimental design was really effective in designing the experiments and analyzing the relation between factor and response.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.73-84
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• 1993

In this research, configuration design optimization of plane truss structure has been tested by using decomposition technique. In the first level, the problem of transferring the nonlinear programming problem to linear programming problem has been effectively solved and the number of the structural analysis necessary for doing the sensitivity analysis can be decreased by developing stress constraint into member stress approximation according to the design space approach which has been proved to be efficient to the sensitivity analysis. And the weight function has been adopted as cost function in order to minimize structures. For the design constraint, allowable stress, buckling stress, displacement constraint under multi-condition and upper and lower constraints of the design variable are considered. In the second level, the nodal point coordinates of the truss structure are used as coordinating variable and the objective function has been taken as the weight function. By treating the nodal point coordinates as design variable, unconstrained optimal design problems are easy to solve. The decomposition method which optimize the section areas in the first level and optimize configuration variables in the second level was applied to the plane truss structures. The numerical comparisons with results which are obtained from numerical test for several truss structures with various shapes and any design criteria show that convergence rate is very fast regardless of constraint types and configuration of truss structures. And the optimal configuration of the truss structures obtained in this study is almost the identical one from other results. The total weight couldbe decreased by 5.4% - 15.4% when optimal configuration was accomplished, though there is some difference.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• KSBB Journal
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• v.23 no.6
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• pp.463-469
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• 2008

During the last decade, monacolin-K biosynthesized by fermentation of red yeast rice (Monascus strains) was proved to have an efficient cholesterol lowering capability, leading to rapid increase in the market demand for the functional red yeast rice. In this study, the production medium composition and components were optimized on a shake flask scale for monacolin-K production by Monascus pilosus (KCCM 60160). The effect of three different soybean flours on the monacolin-K production were studied in order to replace the nitrogen sources of basic production medium (yeast extract, malt extract and beef extract). Among the several experiments, the production medium with dietary soybean flour to replace a half of yeast extract was very good for monacolin-K production. Plackett-Burman experimental design was used to determine the key factors which are critical to produce the biological products in the fermentation. According to the result of Plackett-Burman experimental design, a second order response surface design was applied using yeast extract, beef extract and $(NH_4)_2SO_4$ as factors. Applying this model, the optimum concentration of the three variables was obtained. The maximum monacolin-K production (369.6 mg/L) predicted by model agrees well with the experimental value (418 mg/L) obtained from the experimental verification at the optimal medium. The yield of monacolin-K was increased by 67% as compared to that obtained with basic production medium in shake flasks.

• Journal of Hydrogen and New Energy
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• v.22 no.3
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• pp.326-332
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• 2011

The authors examined the effects of operating parameters on the $H_2$ production by dark fermentation of the wastewater generated from food waste recycling facilities, in short "food waste wastewater (FWW)". Central composite design based response surface methodology was applied to analyze the effect of initial pH (5.5-8.5) and substrate concentration (2-20 g Carbo. COD/L) on $H_2$ production. The experiment was conducted under mesophilic ($35^{\circ}C$) condition and a heat-treated ($90^{\circ}C$ for 20min)anaerobic digester sludge was used as a seeding source. Although there was a little difference in carbohydrate removal, $H_2$ yield was largely affected by the experimental conditions, from 0.38 to 1.77 mol $H_2$/mol $hexose_{added}$. By applying regression analysis, $H_2$ yield was well fitted based on the coded value to a second order polynomial equation (p = 0.0243): Y = $1.78-0.17X_1+0.30X_2+0.37X_1X_2-0.29X_1{^2}-0.35X_2{^2}$, where $X_1$, $X_2$, and Y are pH, substrate concentration (g Carbo. COD/L), and hydrogen yield (mol $H_2$/mol $hexose_{added}$), respectively. The 2-D response surface clearly showed a high inter-dependency between initial pH and substrate concentration, and the role of these two factors was to control the pH during fermentation. According to the statistical optimization, the optimum condition of initial pH and substrate concentration were 7.0 and 13.4 g Carbo. COD/L, respectively, under which predicted $H_2$ yield was 1.84 mol $H_2$/mol $hexose_{added}$. Microbial analysis using 16S rRNA PCR-DGGE showed that $Clostridium$ sp. such as $Clostridium$ $perfringens$, $Clostridium$ $sticklandii$, and $Clostridium$ $bifermentans$ were main $H_2$-producers.

• Cartoon and Animation Studies
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• s.37
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• pp.143-158
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• 2014

In the modeling processes of 3D computer animation, methods to build optimal work conditions to realize real forms for more efficient works have been advanced. Digital sculpting software, published in 1999, ZBrush has been positioned as an essential factor in character model work requiring of realistic descriptions through different manufacturing methods from previous modeling work processes and easy shape realization. Their functional areas are expanding. So, in this production case paper, as a method to product more optimized animation character models, the efficiency of production method linking digital sculpting software (Z-Brush) and animation production software (Maya) was deliberated and its consequences and implications are suggested. To this end, first the technical features of polygon modeling and Retopology were reviewed. Second, based on it, the efficiency of animation character modeling work processes through step linking ZBrush and Maya suggested in this paper was analyzed. Third, based on the features drawn before, in order to prove the hypothesis on modeling optimization method suggested in this paper, the production process of character Dumvee from a short animation film, 'Cula & Mina' was analyzed as an example. Through this study, it was found that technical approach easiness and high level of completion could be realized through two software linked work processes. This study is considered to be a reference for optimizing production process of related industries or modeling-related classes by deliberating different modeling process linked systems.