• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.196-202
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• 2013

Basal cell carcinoma (BCC) is the most common skin cancer and its incidence is increasing rapidly. In this paper, we propose a diagnosis method of basal cell carcinoma by Raman spectra of skin tissue using the NMF(non-negative matrix factorization) algorithm. After preprocessing steps, measured Raman spectra is used classification experiments. The weight and the basis can be obtained in a simple matrix operation and a column vector of the matrix decompsed by the NMF. Linear combination of bases and weights, it is possible to approximate the average of Raman spectra. The classification method is to select the class which to minimize the root mean square of the difference of the linear combination and the objective spectrum. According to the experimental results, the proposed method shows the promising results to diagnosis BCC. In addition, it confirmed that the proposed method compared with the previous research result could be effectively applied in the analysis of the Raman spectra.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.141-148
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• 2011

Support vector machines have been extensively studied and utilized in pattern recognition area for years. One of interesting applications of this technique is music/speech classification for a standardized codec such as 3GPP2 selectable mode vocoder. In this paper, we propose a novel approach that improves the speech/music classification of support vector machines. While conventional support vector machine optimization techniques apply during training phase, the proposed technique can be adopted in classification phase. In this regard, the proposed approach can be developed and employed in parallel with conventional optimizations, resulting in synergistic boost in classification performance. We first analyze the impact of kernel width parameter on the classifications made by support vector machines. From this analysis, we observe that we can fine-tune outputs of support vector machines with the kernel width parameter. To make the most of this capability, we identify strong correlation among neighboring input frames, and use this correlation information as a guide to adjusting kernel width parameter. According to the experimental results, the proposed algorithm is found to have potential for improving the performance of support vector machines.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.4
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• pp.549-559
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• 1994

The purpose of this study was to study accumlated residual soils which may be one of the causes for yellowing of worn cloths. Wear and wash tests of white cotton undershirts were repeated at 30 households sellected at random over a period of 60 days. Laundry conditions were similar to home laundry habits in a fact-finding survey, using a powdery heavy duty detergent containing no enzymes or enzymes. The subjects in this study were survey of laundry actual condition, the undershirts from prior to and after the final washing was measured residual soils, $L^*a^*b^*$ value and mellowness index of CIE system. D3ta were analysed by simple correlation analysis of wear and wash cycle, residual soils, whiteness The results obtained were summarized as follows: 1. Using pattern of washing machine, Presoaking was no singinificant differnece in general characteristics of survey respondent. Laundry frequency was significant difference in income level, occupation of housewives whether or not. Use of cold and hot water was significant difference in residence shape. 2. The analyzed consequences of recognition and actual behavior in connection with laundry were found variables each other to have independence or not. 3. Amount of residual sebum soils is using non-enzyme detergent were much more than in using enzyme detergent, increased linearly with increase of the number of wear and wash cycles. 4. Residual protein soils with increase of the number wear and wash cycles less than in laundering more easy than sebum soils. Since accumulated residual sebum soils were much more than residual protein soils. 5. Increase of residual soils was raised mellowness index and diminshed whiteness. yellowness index of residual sebum soils was higher than protein soils. If increase of whiteness will be incresed, amount of residual sebum soils will be decreased sebum soils. Because amount of residual sebum soils much more than protein soils, yellowness index of residual sebum soils was more higher than that of protein soils.

• Journal of Yeungnam Medical Science
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• v.30 no.1
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• pp.10-16
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• 2013

Background: Toll-like receptors (TLRs) are well-known pattern recognition receptors. Among the 13 TLRs, TLR2 is the most known receptor for immune response. It activates mitogen-activated protein kinases (MAPKs), which are counterbalanced by MAPK phosphatases [MKPs or dual-specificity phosphatases (DUSPs)]. However, the regulatory mechanism of DUSPs is still unclear. In this study, the effect of a TLR2 ligand (TLR2L, Pam3CSK4) on DUSP4 expression in Raw264.7 cells was demonstrated. Methods: A Raw264.7 mouse macrophage cell line was cultured in Dulbecco's modified Eagle's medium supplemented with 10% fetal bovine serum and 1% antibiotics (100 U/mL penicillin and 100 g/mL streptomycin) at $37^{\circ}C$ in 5% $CO_2$. TLR2L (Pam3CSK4)-mediated DUSP4 expressions were confirmed with RT-PCR and western blot analysis. In addition, the detection of reactive oxygen species (ROS) was measured with lucigenin assay. Results: Pam3CSK4 induced the expression of DUSP1, 2, 4, 5 and 16. The DUSP4 expression was also increased by TLR4 and 9 agonists (lipopolysaccharide and CpG ODN, respectively). Pam3CSK4 also induced ERK1/2 phosphorylation and ROS production, and the Pam3CSK4-induced DUSP4 expression was decreased by ERK1/2 (U0126) and ROS (DPI) inhibitors. U0126 suppressed the ROS production by Pam3CSK4. Conclusion: Pam3CSK4-mediated DUSP4 expression is regulated by ERK1/2 and ROS. This finding suggests the physiological importance of DUSP4 in TLR2-mediated immune response.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.41-48
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• 2011

In feature selection, the selective evaluation scheme for Ant Colony Optimization(ACO) has recently been proposed, which reduces computational load by excluding unnecessary or less promising candidate solutions from the actual evaluation. Its superiority was supported by experimental results. However the experiment seems to be not statistically sufficient since it used only one dataset. The aim of this paper is to analyze convergence characteristics of the selective evaluation scheme and to make the conclusion more convincing. We chose three datasets related to handwriting, medical, and speech domains from UCI repository whose feature set size ranges from 256 to 617. For each of them, we executed 12 independent runs in order to obtain statistically stable data. Each run was given 72 hours to observe the long-time convergence. Based on analysis of experimental data, we describe a reason for the superiority and where the scheme can be applied.

• Proceedings of the Microbiological Society of Korea Conference
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• 2009.05a
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• pp.78-78
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• 2009

$^1H$ NMR spectroscopy coupled with multivariate statistical analysis was used for the first time to investigate metabolic changes in musts during alcoholic fermentation and wines during ageing. Three Saccharomyces cerevisiae yeast strains (RC-212, KIV-1116 and KUBY-501) were also evaluated for their impacts on the metabolic changes in must and wine. Pattern recognition (PR) methods, including PCA, PLS-DA and OPLS-DA scores plots, showed clear differences for metabolites among musts or wines for each fermentation stage up to 6 months. Metabolites responsible for the differentiation were identified to valine, 2,3-butanediol (2,3-BD), pyruvate, succinate, proline, citrate, glycerol, malate, tartarate, glucose, N-methylnicotinic acid (NMNA), and polyphenol compounds. PCA scores plots showed continuous movements away from days 1 to 8 in all musts for all yeast strains, indicating continuous and active fermentation. During alcoholic fermentation, highest levels of 2,3-BD, succinate and glycerol were found in musts with the KIV-1116 strain, which showed the fastest fermentation or highest fermentative activity of the 3 strains, whereas the KUBY-501 strain showed the slowest fermentative activity. This study highlights the applicability of NMR-based metabolomics for monitoring wine fermentation and evaluating the fermentative characteristics of yeast strains.

• Journal of Gifted/Talented Education
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• v.21 no.1
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• pp.163-174
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• 2011

As the scientific technology has produced complex problems that required value judgment, science-gifted students need the program for enhancing the critical thinking. Therefore, this study analyzed patterns of claims on scientific technology of the science-gifted for the development of argument program. The data were collected by 60 science-gifted students using writing and e-mail. The result showed that 29% of the participants provided only advantageous factors for their claims, whereas only 10% among the participants who provided both sides used pattern of 'rebuttal.' In addition, the students who fell into the patterns of 'alternative suggestion' and 'overly positive expectation on scientific technology' revealed positive recognition on scientific technology. These results highlight the need of argumentation program for science-gifted students that could be guideline for knowledge or argumentation, help awareness of limitation and role of scientific technology and lead to well-balanced judgment between positive effects and negative ones.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.185-192
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• 2016

The purpose of this paper is to examine the relationships among consumer lifestyle, brand attitude, brand attachment, and behavior pattern. Sampling with consumers who experienced eating out in regional catering companies as a population was done and the survey was conducted targeting consumers of catering companies in Gwangju. Therefore, it analyzed the sample by setting hypotheses and research model according to the research objective. First, as for the relationship between lifestyle and brand attitude, the lifestyle as a personal inclination formed a significant relationship with brand attitude the characteristics of which are recognition, convenience, and familiar features regardless of the type of lifestyle. Second, consumer lifestyle in types of reality seeking, value-oriented, and fashion-pursuing formed a significant relationships with brand attachment in order of mention, whereas social oriented type did not form a significant relationship. Third, the relationship between consumer brand attitude and brand loyalty formed a significant relation with the relationship between consumer brand attachment and brand loyalty.

• Journal of Radiation Protection and Research
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• v.42 no.2
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• pp.91-97
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• 2017

Background: A gamma energy identifying algorithm using spectral decomposition combined with smoothing method was suggested to confirm the existence of the artificial radio isotopes. The algorithm is composed by original pattern recognition method and smoothing method to enhance the performance to identify gamma energy of radiation sensors that have low energy resolution. Materials and Methods: The gamma energy identifying algorithm for the compact radiation sensor is a three-step of refinement process. Firstly, the magnitude set is calculated by the original spectral decomposition. Secondly, the magnitude of modeling error in the magnitude set is reduced by the smoothing method. Thirdly, the expected gamma energy is finally decided based on the enhanced magnitude set as a result of the spectral decomposition with the smoothing method. The algorithm was optimized for the designed radiation sensor composed of a CsI (Tl) scintillator and a silicon pin diode. Results and Discussion: The two performance parameters used to estimate the algorithm are the accuracy of expected gamma energy and the number of repeated calculations. The original gamma energy was accurately identified with the single energy of gamma radiation by adapting this modeling error reduction method. Also the average error decreased by half with the multi energies of gamma radiation in comparison to the original spectral decomposition. In addition, the number of repeated calculations also decreased by half even in low fluence conditions under $10^4$ ($/0.09cm^2$ of the scintillator surface). Conclusion: Through the development of this algorithm, we have confirmed the possibility of developing a product that can identify artificial radionuclides nearby using inexpensive radiation sensors that are easy to use by the public. Therefore, it can contribute to reduce the anxiety of the public exposure by determining the presence of artificial radionuclides in the vicinity.

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.77-85
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• 2011

It is believed that the anomalies or diseases of human organs are identified by the analysis of the patterns. This paper proposes a new classification technique for the identification of cancer disease using the proteome patterns obtained from two-dimensional polyacrylamide gel electrophoresis(2-D PAGE). In the new classification method, three different classification methods such as support vector machine(SVM), multi-layer perceptron(MLP) and k-nearest neighbor(k-NN) are extended by multi-boosting method in an array of subclassifiers and the results of each subclassifier are merged by ensemble method. Genetic algorithm was applied to obtain optimal feature set in each subclassifier. We applied our method to empirical data set from cancer research and the method showed the better accuracy and more stable performance than single classifier.