• Journal of the Korean Society of Safety
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• v.17 no.1
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• pp.94-98
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• 2002

This study aimed to search for the fundamental accident causes using a categorical analysis, a kind of statistical methods. As the analysis methods, correlation analysis, independence test and logistic regression analysis were used. And the SPSS package, a general-purpose mathematical library, was used to obtain statistical characteristics. As the result of this study, the accident causes associated with factor of 'lost working days' were factors such as 'employed periods', 'sex', 'type of accident', 'month'. In case of applying independence test method, the most important cause was the factor of 'month'. In case that logistic regression analysis method was applied, the cause contributed to the increase structure'. 'less than 6 month'. On the basis of these results, the plan for accident prevention and the proper investment for accident prevention expenditure could be carried out in each workshop.

• IE interfaces
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• v.12 no.4
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• pp.551-556
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• 1999

In this paper, we compare the performance of three data mining classification algorithms(neural network, decision tree, logistic regression) in consideration of various characteristics of categorical input and output data. $2^{4-1}$. 3 fractional factorial design is used to simulate the comparison situation where factors used are (1) the categorical ratio of input variables, (2) the complexity of functional relationship between the output and input variables, (3) the size of randomness in the relationship, (4) the categorical ratio of an output variable, and (5) the classification algorithm. Experimental study results indicate the following: decision tree performs better than the others when the relationship between output and input variables is simple while logistic regression is better when the other way is around; and neural network appears a better choice than the others when the randomness in the relationship is relatively large. We also use Taguchi design to improve the practicality of our study results by letting the relationship between the output and input variables as a noise factor. As a result, the classification accuracy of neural network and decision tree turns out to be higher than that of logistic regression, when the categorical proportion of the output variable is even.

• Architectural research
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• v.16 no.2
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• pp.75-80
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• 2014

Risks, uncertainties, and associated cost overruns are critical problems for construction projects. Cost contingency is an important funding source for these unforeseen events and is included in the base estimate to help perform financially successful projects. In order to predict more accurate contingency, many empirical models using regression analysis and artificial neural network method have been proposed and showed its viability to minimize prediction errors. However, categorical factors on contingency cannot have been treated and thus considered in these empirical models since those models are able to treat only numerical factors. This paper identified potential factors on contingency in transportation construction projects and evaluated categorical factors using the one-way ANOVA statistical method. Among factors including project work type, delivery method type, contract agreement type, bid award type, letting type, and geographical location, two factors of project work type and contract agreement type were found to be statistically important on allocating cost contingency.

• IE interfaces
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• v.14 no.1
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• pp.79-83
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• 2001

In this paper, we propose a simple method to reduce categorical variables into smaller, but significant numbers, and also demonstrate how the proposed method can be applied to the problem of reduction that empirical research often faces in the course of data processing. For the purpose, we introduce a concept of pseudo-correlation coefficient to make it possible to use factor analysis (FA) as a tool for reducing variables. The main idea of the concept is to deal with the measures of association of categorical variables in the sense of the concept of Pearson's correlation coefficient in order to meet the input requirement of FA. Upon examination of existing measures that could play as pseudo-correlation coefficients, Cramer's V coefficient is selected for the best result among them. To show the detailed procedure of the proposed method, a specific demonstration with the data from 329 R&D projects conducted in 18 private laboratories in electric and electronics industry is presented.

• The Journal of the Acoustical Society of Korea
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• v.29 no.5
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• pp.325-331
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• 2010

Categorical perception has been noted as characteristic properties of linguistic stimuli. In this study, Korean monosyllabic minimal pairs (consonant-vowel-consonant, CVC) were analyzed to understand perception boundaries between clinically confusing words. An efficient scheme has been developed to systematically synthesize temporal transition waveforms (11 steps) from one word to the target word for the pairs of /gom/-/gong/, /non/-/noon/, and /don/-/non/. The corresponding slopes, widths, and non-dominant factors of perception boundaries were analyzed for the total of 40 young normal subjects (20 males and 20 females). Results showed that there were relative pattern differences among confusing monosyllabic minimal pairs under categorical perception. For instance, the vowel difference within CVC pairs led to the lowest boundary performance in this experiment set. Data also indicated the potential application of the overall procedure for evaluating auditory functions and assisting rehabilitation programs.

• Language and Information
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• v.19 no.1
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• pp.1-18
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• 2015

Korean marks case for subjects and objects, but it is well known that case-markers can be dropped in certain contexts. Kwon and Zribi-Hertz (2008) establishes the phenomenon of Korean case drop on a single factor of f(ocus)-structure visibility and claims that both subject and object case drop can fall under a single linguistic generalization of information structure. However, the supporting data is not empirically substantiated and the tenability of the f-structure analysis is still under question. In this paper, an experiment was conducted to show that the specific claims of Kwon and Zribi-Hertz's analysis that places exclusive importance on information structure cannot be adequately supported by empirical evidence. In addition, the present study examines H. Lee's (2006a, 2006c) multi-factor analysis of object case drop and investigates whether this approach can subsume both subject and object case drop under a unified analysis. The present findings indicate that the multi-factor analysis that involves the interaction of independent factors (Focus, Animacy, and Definiteness) is also compatible with subject case drop, and that judgments on case drop are not categorical but form gradient statistical preferences.

• Journal of the Korean Society for Railway
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• v.11 no.3
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• pp.216-224
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• 2008

In general, based on criteria of subway law, radius 500m from subway station is defined as SIA(Subway Station Influence Area). Therefore, in this paper, selection models of SIA are developed to identify appropriate SIA for recently developed 4 new towns based based on CART analysis. As a result, following outputs are obtained; (1) walking distance from subway station is the most influential factor to define SIA (2) SIAs vary with new towns (i.e., bundang city: 856m, ilsan sanbon city 508m, pyungchon city 495m), and (3) walking distance from subway station is influential to land price of SIA. In addition, bundang and pyungchon new town are more affected in land price and walking distance. Therefore, it is desirable for current definition of SIA (radius 500m from subway station) to reflect characteristics of land use and walking distance in the new towns.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.831-844
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• 2008

Since cooperatives consist of many distinct members in the management environment and characteristics, it is necessary to make similar cooperatives into a few groups for the effective risk management of cooperatives' mutuality bank. This paper is a priori research for suggesting a guidance for effective risk management of cooperatives with different management strategy. For such purpose, we propose a way to group the members of cooperative's mutuality bank. The 30 continuous variables which is relative to cooperatives' management status are considered and six factors are extracted from those variables through factor analysis with empirical consideration to avoid wrong grouping and to enhance the practical interpretation. Based on extracted six factors and additional 3 categorical variables, six representative groups are derived by the two step clustering analysis. These findings are useful to execute a discriminatory risk management and other management strategy for a mutuality bank and others.

• Korean Linguistics
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• v.81
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• pp.267-297
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• 2018

Vowel raising in Korean has been primarily treated as a phonological, categorical change. This study aims to show how the Korean connective suffix {-go} is realized in various environments, and propose a principle of vowel raising based on both acoustic and perceptual data. To that end, we used a corpus of spoken Korean to analyze the types of syntactic constructions, the realization of prosodic boundaries (IP and PP), and the types of boundary tone associated with {-go}. It was found that the vowel tends to be raised most frequently in utterance-final position, while in utterance-medial position the vowel was raised more when the syntactic and prosodic distance between {-go} and the following constituent was smaller. The results for boundary tone also showed a correlation between vowel raising and the discourse function of the boundary tone. In conclusion, we propose that vowel raising is not simply an optional phenomenon, but rather a type of phonetic reduction related to the comprehension of the following constituent.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.93-100
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• 2013

This paper analyzes determinants of tourist consumption in the case of 2013 Gangneung Dano Festival, based on the multiple regression model. We set 12 determinants of consumption such as income as explanatory variables and consumption expenditure as a dependent variable. Also Five kinds of categorical consumptions are estimated. Main results are the followings. First, income is the most important factor and shows positive effect in tourist consumption. Second, age and metropolitan area influence consumption positively. Third number of participating day and length of stay also influence consumption positively. Fourth, number of accompanying person shows negative effect on consumption. Fifth, male, married person, and lodge with own expense influence consumption positively. Finally, categorical consumption has its specific determinants distinct from common factors This paper can be applied to invent and implement efficient strategies for development in regional economies and tour industries.