• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.161-165
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• 2010

In the present study, process optimization for thermal-sprayed STS316 coating has been performed using $L_9(3^4)$ orthogonal array and analysis of variance (ANOVA). STS316 coatings were fabricated by flame spray process on steel substrate, and the hardness test and microstructure observation of the coatings were studied. The results of hardness test were analyzed by ANOVA. The ANOVA results showed that the spray distance had the greatest effect on hardness of the coating, on the other hands, the effects of oxygen gas flow and spray distance were ignorable. From these results, the optimal combination of the flame spray parameters could be derived, and confirmation experiment was carried out to verify these derived results. The calculated hardness of the coatings by ANOVA was found to approximately close to that of confirmation experimental result. Thus, it was considered that design of experiments using orthogonal array and ANOVA was effective for process optimization of thermal-sprayed STS316 coating.

• Journal of Power System Engineering
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• v.13 no.5
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• pp.89-94
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• 2009

In this work, the optimal process has been designed by $L_9(3^4)$ orthogonal array and analysis of variance(ANOVA) for thermal-sprayed Ni-based hard coating. Ni-based hard coatings were fabricated by flame spray process on steel substrate. Then, the hardness test and observation of microstructure of the coatings were performed. The results of hardness test were analyzed by ANOVA. The ANOVA results demonstrated that the acetylene gas flow had the greatest effect on hardness of the coatings. The oxygen gas flow was found to have a neglecting effect. From these results, the optimal combination of the flame spray parameters could be predicted. The calculated hardness of the coatings by ANOVA was found to lie close to that of confirmation experimental result. Thus, it was considered that design of experiments design using orthogonal array and ANOVA was useful to determine optimal process of thermal-sprayed Ni-based hard coating.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.46-53
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• 2009

To find the working condition is one of the important factors in precision machining. In this study, we analyzed maximum working temperature by infra-red camera and surface roughness in side wall end milling using design of experiment (DOE): RSM(response surface methodology), ANOM(analysis of means) and ANOVA(analysis of variance) by table of orthogonal array. ANOM and ANOVA are well adapted to select sensitivity of design variables for maximum working temperature and surface roughness. The effective design variables and their levels should be determined using ANOM, ANOVA. RSM is presented 2nd order approximation polynomial of maximum working temperature and surface roughness is composed with design variables. Therefore, it is expected that the proposed procedure using design of experiment : table of orthogonal array, ANOM, ANOVA and RSM can be easily utilized to solve the problem of working condition.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.398-406
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• 2009

This study intends to provide support for tourism industry to establish marketing strategies for selling the travel products on which it should focus on more by examining the difference on selection of travel product attributes by tourism action. This research utilized cluster analysis and ANOVA. The cluster analysis identified four cluster: logical tourism, weak conspicious tourism, value tourism, conspicuous and value tourism. ANOVA analysis showed that four cluster were different in terms of tourism action such as transportation accommodation facilities, tourist attractions, shopping and meals except for travel service, entertainment.

• Journal of the Ergonomics Society of Korea
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• v.33 no.6
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• pp.515-532
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• 2014

Objective: The purpose of this study is to define consumers' affection on the interior design of commercial cars in terms of its design factors: color, embossing and gloss as independent factors. Background: Existing affective studies related to interior of vehicle focus on just sedans. However, there is no affective study about the interior of commercial cars. In addition, it is hard to change levels to which manufactures want. Method: Representative design factors were drawn using ANOVA and SNK analysis and definitive affective vocabularies were drawn using factor analysis. Furthermore, the results of 3D experiment were analyzed using ANOVA and LSD analysis. 3D images for the experiment were made using 3D max program. The experiment revealed that consumers discerned the differences in levels of each design factor and affective vocabulary. Results: The ANOVA revealed that beige color "A" type and non-gloss were the most preferred design in terms of the affective vocabularies and total preference. Conclusion: The result of the experiment may help manufactures to design the interior of commercial cars in the near future. Furthermore, the ANOVA result of affective vocabularies evaluation is expected to suggest a meaningful guideline. Application: The study results may be utilized as a guideline for interior design of commercial cars.

• Journal of Environmental Science International
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• v.16 no.11
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• pp.1209-1218
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• 2007

Advertisement signboards on the buildings have functionally a visual value as factor of urban and building design. But it is not easy to find any reasonable principles and regulations, how well the signboards deliver the information of stores to the customers, and how they contribute the visual amenity from the sight of urban landscape. Under this context, this study tries to analyze the information delivery power of signboards in relation to the visual cognition. The analysis method is the Two-Way ANOVA (Analysis of Variance) evaluation with factors, such as scale, amount and arrangement of signboards. The scale of letters or figures at Signboards is specified in 3 different sizes such as big, medium and small. The amount is classified into 5 grades from 100% to 20% installation. And the arrangement is divided into orderly and disorderly installation. As the results of the Two-Way ANOVA, the identical scale of signboards is much better for the awareness. And the orderly arrangement shows also the same result. Above all, including these two results, the 80% of installation showed the biggest different result of awareness.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.97-115
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• 2001

cDNA microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. Many statistical analysis tools become widely applicable to the analysis of cDNA microarray data. In this talk, we consider a two-way ANOVA model to differentiate genes that have high variability and ones that do not. Using this model, we detect genes that have different gene expression profiles among experimental groups. The two-way ANOVA model is illustrated using cDNA microarrays of 3,800 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

• Journal of Power System Engineering
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• v.15 no.5
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• pp.72-76
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• 2011

In this work, the parameter optimization for thermal-sprayed Al/SiC composites have been designed by $L_9(3^4)$ orthogonal array and analysis of variance(ANOVA). Al/SiC composites were fabricated by flame spray process on steel substrate. The hardness of composites were measured using micro-vickers hardness tester, and these results were analyzed by ANOVA. The ANOVA results showed that the oxygen gas flow, powder feed rate and spray distance affect on the hardness of the Al/SiC composites. From the ANOVA results, the optimal combination of the flame spray parameters could be extracted. It was considered that experimental design using orthogonal array and ANOVA was efficient to determine optimal parameter of thermal-sprayed Al/SiC composites.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.835-841
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• 2018

In this study, we analyzed public health data analysis using the hadoop-based spack in the cloud environment using the data of the Community Health Survey from 2012 to 2014, and the factors affecting the quality of life and quality of life. In the proposed paper, we constructed a cloud manager for parallel processing support using Hadoop - based Spack for open medical big data analysis. And we analyzed the factors affecting the "quality of life" of the individual among open medical big data quickly without restriction of hardware. The effects of public health data on health - related quality of life were classified into personal characteristics and community characteristics. And multiple-level regression analysis (ANOVA, t-test). As a result of the experiment, the factors affecting the quality of life were 73.8 points for men and 70.0 points for women, indicating that men had higher health - related quality of life than women.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.667-675
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• 2001

The usefulness of analysis of variance(ANOVA) estimates of variance components is impaired by the frequent occurrence of negative values. The probability of such an occurrence is therefore of interest. In this paper, we investigate a variety of reasons for negative estimates under one way random effects model. It can be shown, through simulation, that this probability increases when the number of treatments is too small for fixed total observations, unbalancedness of data is severe, ratio of variance components is too small, and data may contain many outliers.