• Journal of Industrial Convergence
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• v.1 no.2
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• pp.125-140
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• 2003

This study examined testing condition when consumers have a strong ordinal preference and in a absence of established ordinal for a given attribute, how adding common features to two brands in a given product category affects brand choice. Research findings presented in this study are generally consistent with the preference confirmation view of choice. The data provides support for the proposition that (1) the effect of common features is moderated by the relative importance of brand attributes(Hypothesis 1) and (2) in the presence of primary attribute adding common features increases the likelihood of choosing the brand with the best value on this attribute(Hypotheses 2).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.287-293
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• 2009

The aim of this paper is to analyze resettlement cost and decision factors of resettlement since Redevelopment Promotion Projects. Range of resettlement cost was averagely increased 204% by using actual data. Consequently, the research is operated for aboriginal people in these areas by a questionnaire. The questionnaire ask a payment range of the resettlement cost with 4 stages; 150% and less, 180% and less, 200% and less, excess of 200%. Research scope is consist of Seo-kumsa, Civil Park, Chung-mu and Young-do. These areas are redevelopment of Busan metropolitan city. Resettlement is come under the influence of the resettlement cost and many factors by each specific character. In many alternatives for resettlement, understanding the reason why aboriginal peoples select a certain alternative and if we actualize the proper alternative, aboriginal peoples' resettlement ratio will be increased. Moreover it ask housing characteristic, housing life pattern for understanding aboriginal peoples' characteristic. Also data analysis model is ordinal logistic model'. In analysis result, resettlement cost is 150% of aboriginal assets. and significance parameter is sex, job, income, region, affection, attachment, housing possession type, size and others have influence on aboriginal peoples' resettlement.

• Journal of Korean Academy of Nursing
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• v.44 no.5
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• pp.542-551
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• 2014

Purpose: This study was done to examine the incidence of oral mucositis in hematopoietic stem cell transplantation patients and to identify factors influencing oral mucositis and patient outcomes according to severity. Methods: In this retrospective study, data were collected from electronic medical records of 222 patients who had received hematopoietic stem cell transplantation. Oral mucositis was evaluated using WHO's assessment scale. Data were analyzed using Chi-square test, Fisher exact test, Spearman's correlation, Ordinal logistic regression, ANOVA and Kruskal-Wallis test. Results: A total of 69.8% of the patients evaluated developed oral mucositis (grade II and over). As a results of ordinal regression, factors influencing oral mucositis severity were found to be diagnosis, type of transplantation, oxygen inhalation and the number of antiemetics administration before transplantation. The severity of oral mucositis was found to increase the days of hospitalization, days of TPN administration, days of using antibiotics and the number and dosage of analgesics. Conclusion: The results would help predict severity of oral mucositis in hematopoietic stem cell transplantation patients and suggest that provision of appropriate nursing assessment and oral care would improve patient outcomes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2129-2147
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• 2019

This paper introduces an adaptive face recognition method based on a Novel Incremental Kernel Nonparametric Discriminant Analysis (IKNDA) that is able to learn through time. More precisely, the IKNDA has the advantage of incrementally reducing data dimension, in a discriminative manner, as new samples are added asynchronously. Thus, it handles dynamic and large data in a better way. In order to perform face recognition effectively, we combine the Gabor features and the ordinal measures to extract the facial features that are coded across local parts, as visual primitives. The variegated ordinal measures are extraught from Gabor filtering responses. Then, the histogram of these primitives, across a variety of facial zones, is intermingled to procure a feature vector. This latter's dimension is slimmed down using PCA. Finally, the latter is treated as a facial vector input for the advanced IKNDA. A comparative evaluation of the IKNDA is performed for face recognition, besides, for other classification endeavors, in a decontextualized evaluation schemes. In such a scheme, we compare the IKNDA model to some relevant state-of-the-art incremental and batch discriminant models. Experimental results show that the IKNDA outperforms these discriminant models and is better tool to improve face recognition performance.

• Journal of Distribution Science
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• v.20 no.10
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• pp.11-17
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• 2022

Purpose: This research aims to find the link between public service Distribution and individual job performance in the provincial municipality. Research design, data, and methodology: This is a quantitative approach study with a non-experimental and correlational design. The sample consisted of 140 employees appointed and hired by the provincial municipality of Huaraz. For data collection, Two questionnaires with an ordinal Likert-type scale and the Rho Spearman correlation coefficient were used to assess the link between the research variables., For Analysis: two questionnaires with an ordinal Likert-type scale and the Rho Spearman correlation coefficient were used to determine the connection between the research variables. Results: It was determined that both variables have a high degree of correlation (0.725), indicating a direct and significant relationship between the Distribution of public service and skill performance in the provincial municipality (0.614). Conclusion: Finally, this allows us to conclude that the institutional context is essential; that is, there is a significant correlation between the PSM and contextual performance in the provincial municipality of Huaraz, which has a Rho Spearman value of 0.723.

• Journal of Agricultural Extension & Community Development
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• v.30 no.3
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• pp.157-170
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• 2023

This study aims to identify factors that affect the quality of life of rural residents. Data were collected from 4,000 rural residents living in rural areas. Raw data was procured from the 'Survey on Rural Well-being in 2022 in Rural Development Administration'. The main results of the ordinal logit regression analysis are as follows. First, in the case of non-farm households, female, immigrants, more educated, more healthy are more likely to be highly perceived quality of life. In the case of full-time farm households, more healthy are more likely to be highly perceived quality of life. In the case of part-time farm households, younger, married, more healthy are more likely to be highly perceived quality of life. Second, for all rural housholds(non-farmers, full-time farmers, and part-time farmers), local amenities and safety also had positive impact on perception of quality of life.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.139-146
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• 1996

The estimation technique of psychophysical magnitude Is useful tool which measures to subjective feeling or opinion of human. This paper Introduces properties of the measured data, scales(nominal. ordinal. Interval. and ratio scale). and right analyzing methods of the measured data.

• Proceedings of the ESK Conference
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• 1993.10a
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• pp.133-144
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• 1993

Psychophysical data, in general, belong to one of the four scale categories : Nominal, Ordinal, Interval, and Ratio Scale. This paper introduces properties of the four scale categories and describes some psychophysical scales that attempt to measure subjective feeling or opinion of human. In addition, guidelines of analyzing and interpreting measured data are suggested. Some examples of analyzing and interpreting paychophysical data inappropriately are presented especially with category scales which have been used most widely in measuring subjective information.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.85-94
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• 2013

As the financial market becomes larger, the loss increases due to the failure of the credit risk managements from the poor management of the customer information or poor decision-making. Thus, the credit risk management also becomes more important and it is essential to develop a credit scoring model, which is a fundamental tool used to minimize the credit risk. Credit scoring models have been studied and developed only for binary target variables. In this paper, we consider other types of target variables such as ordinal multinomial data or longitudinal binary data and suggest credit scoring models. We then apply our developed models to real data and random data, and investigate their performance through Kolmogorov-Smirnov statistic.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.373-380
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• 2016

Even though Likert type data is ordinal scale, many researchers who regard Likert type data as interval scale adapt as parametric methods. In this research, simulations have been used to find out a proper analysis of Likert type data. The locations and response distributions of five point Likert type data samples having diverse distribution have been evaluated. In estimating samples' locations, we considered parametric method and non-parametric method, which are t-test and Mann-Whitney test respectively. In addition, to test response distribution, we employed Chi-squared test and Kolmogorov-Smirnov test. In this study, we assessed the performance of the four aforementioned methods by comparing Type I error ratio and statistical power.