• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.229-236
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• 2005

This paper is contribute to Inverse continuous wavelets transform(ICWT) which permits to determine real 'time-scale' plan. The application of ICWT is not yet represented because of the numerical difficulty. If the signal can be reconstructed stably by ICWT, the multi scale filter bank system which composed by analysis and synthesis process can be designed. In this work, we represent the ICWT which leads to nearly perfect reconstruction of signal and the multi-scale filter bank system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.3
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• pp.419-427
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• 2013

The catalytic converters for automobile exhaust systems are manufactured by inserting a mat-wrapped substrate into a stainless steel can. A residual pressure that is too high will initiate a fracture in the substrate. In contrast, a residual pressure that is too low will fail to hold the substrate in the acceleration or deceleration phase. Both the process capability and mat pressure on the substrate are predicted while considering the effect of the statistical variation in the dimensions of the parts. The validity of the solutions is then confirmed. A program using EXCEL combines a finite element analysis and process capability analysis in one program.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.6
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• pp.498-503
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• 2012

Independent component analysis (ICA) technique based on statistical independency of the signals is known as suitable to identify the source signals by measuring and separating mixed signals through transfer paths and has successfully applied in the field of medical care, communications and so forth. In this study, the ICA technique is introduced for the identification of excitation sources from measured vibration signals of structures, which can be done by evaluating negentropy of centered and whitened vibration signals and correlation of separated signals. To validate the method, numerical analyses are carried out for a plate and a cylinder structure. The results show that the method can be applied efficiently to source identification of complex structures. Nevertheless, additional studies would be required to complement problems of occasional inaccuracy.

• Journal of IKEEE
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• v.22 no.4
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• pp.1109-1114
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• 2018

Electroencephalogram (EEG) is a tool used to study brain activity caused by external stimuli. In this process, artifacts are mixed and it is easy to distort the signal, so post-processing is necessary to remove it. Independent Component Analysis (ICA) is a widely used method for removing artifact. This method has a disadvantage in that it has excellent performance but some loss of brain wave information. In this paper, we propose a method to reduce EEG information loss by restricting the filter coverage using eye blink information obtained from Eyetracker. We then compared the results of the proposed method with the conventional method using quantization methods such as Signal to Noise Ratio (SNR) and Spectral Coherence (SC).

• Applied Biological Chemistry
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• v.48 no.4
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• pp.352-357
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• 2005

The optimization of extraction conditions of phytoestrogen from pomegranate by hot water was conducted by analyzing the extraction characteristics. The purpose of this study was effective utilization of bioactive components of pomegranate, and the analyzing was performed with response surface methodology (RSM). This study established 10 sections based on the central composite design with the independent variables of extraction temperature (60, 70, 80, 90, $100^{\circ}C$) and extraction time (1, 2, 3, 4, 5 hr) to predict the optimal conditions for extraction of the effective components. The dependent variables were measured for extracted materials, those were, the major components such as chlorogenic acid, kaempferol, $17-{\alpha}-estradiol\;and\;17-{\beta}-estradiol$ content, and regression analysis was performed by SAS program, and optimal conditions for each characteristics were predicted, and the characteristics of extraction were analyzed by response surface methodology. It was found that chlorogenic acid, kaempferol, and $17-{\alpha}-estradiol$ content were greatly affected by extraction temperature. However, $17-{\beta}-estradiol$ content was affected significantly by extraction time. Regression formulas for each variable were elicited from this study, and the chlorogenic acid, kaempferol, $17-{\alpha}-estradiol\;and\;17-{\beta}-estradiol$ content depending on response surface methodology factor were superimposed. It was shown that optimal temperature and extraction time were $98{\sim}100^{\circ}C\;and\;3{\sim}5$ hrs, respectively.

• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Journal of Life Science
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• v.18 no.4
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• pp.556-564
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• 2008

Response surface methodology was used to monitor the optimization of fermentation conditions for red ginseng wine. A central composite design was applied to investigate the effects of independent variables, fermentation temperature ($X_1$), fermentation time ($X_2$) and initial pH ($X_3$) on dependent variables, physicochemical characteristics and effective ingredients. Alcohol and total sugar content were significantly affected both by fermentation temperature and time. Crude saponin content was greatly affected by fermentation time, and pH was significantly affected by initial pH. Fermentation time and initial pH had a greater effect on ginsenoside content than fermentation temperature. Ginsenoside content increased along with fermentation time and initial pH. We elicited a regression formula for each variable, and superimposed the total optimum points of fermentation conditions for physicochemical characteristics and the effective constituents. The predicted values at the optimum fermentation conditions were at $21{\sim}27^{\circ}C$ for $15{\sim}20$ day in initial pH $4.6{\sim}5.2$.

• Applied Chemistry for Engineering
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• v.32 no.2
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• pp.168-173
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• 2021

In this study, we measured total flavonoids after extracting the total flavonoids from lemongrass which is known to have a high content of antioxidant ingredients when using microwave energy. Also, optimal extraction conditions of active ingredients using central composite design-response surface methodology (CCD-RSM) were presented. Both ultrapure water and alcohol were used as extraction solvents and the volume ratio of ethanol/ultrapure water, microwave irradiation time, and microwave irradiation power were set as independence variables. And the extraction yield and total flavonoids were measured. The optimal extraction conditions using CCD-RSM were the volume ratio of ethanol/ultrapure water = 56.3 vol.%, the microwave irradiation time = 6.1 min, and the microwave irradiation power = 574.6 W. We could also obtain expected results of yield = 17.2 wt.% and total flavonoids = 44.7 ㎍ QE/mL dw under the optimum conditions. The comprehensive satisfaction degree of this formula was 0.8562. The P-value was calculated for the yield of 0.037 and the total flavonoids content of 0.002. The average error from actual experiments established for the verification of conclusions was lower than 2.5%. Therefore, a high favorable level could be obtained when the CCD-RSM was applied to the optimization of extraction process.

• Journal of dental hygiene science
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• v.10 no.3
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• pp.147-153
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• 2010

The purpose of this study was to investigate the correlation between food intake pattern body component bone mineral density(BMD) and dental caries experience of college women and we wanted to determine the correlation of these factors with dental caries experience. Research was conducted to offer basic data to develope a nutritional program for the future prevention from oral disease. The subjects in this study were 132 college women who participated in the food intake survey and who's body component and BMD was measured. The statistical analysis was done by using the SPSS 15.0 program. The results of this study were as follows; 1. The food intake pattern was not directly correlated with DMFT index. 2. The body component was not directly correlated with DMFT index. 3. The SOS, BQI was directly correlated with DMFT index(p<0.05). 4. T-score of BMD had the greatest influence on DMFT index(p<0.05). Above results indicated that bone mineral density are related with the incidence of dental caries experience and further research is necessary to develop a nutritional and health promotional program in order to prevent oral illness.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.227-235
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• 2018

The aim of this study is to predict the sensitivity of motion sickness (MS) using pattern of cardinal gaze position (CGP) before experiencing the virtual reality (VR) content. Twenty volunteers of both genders (8 females, mean age $28.42{\pm}3.17$) participated in this experiment. They was required to measure the pattern of CGP for 5 minute, and then watched VR content for 15 minute. After watching VR content, subjective experience for MS reported from participants using by 'Simulator Sickness Questionnaire (SSQ)'. Statistical significance between CGP and SSQ score were confirmed using Pearson correlation analysis and independent t-test, and prediction model was extracted from multiple regression model. PCPA & PCPR indicators from CGP revealed significantly difference and strong or moderate positive correlation with SSQ score. Extracted prediction model was tested using correlation coefficient and mean error, SSQ score between subjective rating and prediction model showed strong positive correlation and low difference.