• Communications of Mathematical Education
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• v.35 no.2
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• pp.153-172
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• 2021

Various competencies such as critical thinking, systems thinking, problem solving competence, communication skill, and data literacy are likely to be required in the 4th industrial revolution. The competency regarding data literacy is one of those competencies. To nurture citizens who will live in the future, it is timely to consider research on teacher education for supporting teachers' development of statistical thinking as well as statistical knowledge. Therefore, in this study we developed and implemented a data analysis project for pre-service teachers to understand their changes in statistical knowledge in addition to their experiences of data-driven decision making process that required them utilizing their statistical thinking. We used a mixed method (i.e., sequential explanatory design) research to analyze the quantitative and qualitative data collected. The findings indicated that pre-service teachers have low knowledge level of their understanding on the relationship between population means and sample means, and estimation of the population mean and its interpretation. When it comes to the data-driven decision making process, we found that the pre-service teachers' experiences varied even when they worked as a small group for the project. We end this paper by presenting implications of the study for the fields of teacher education and statistics education.

• The Korean Journal of Legal Medicine
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• v.41 no.2
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• pp.32-40
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• 2017

In addition to identifying genetic differences between target populations, it is also important to determine the impact of genetic differences with regard to the respective target populations. In recent years, there has been an increasing number of cases where this approach is needed, and thus various statistical methods must be considered. In this study, genetic data from populations of Southeast and Southwest Asia were collected, and several statistical approaches were evaluated on the Y-chromosome short tandem repeat data. In order to develop a more accurate and practical classification model, we applied gradient boosting and ensemble techniques. To infer between the Southeast and Southwest Asian populations, the overall performance of the classification models was better than that of the decision trees and regression models used in the past. In conclusion, this study suggests that additional statistical approaches, such as data mining techniques, could provide more useful interpretations for forensic analyses. These trials are expected to be the basis for further studies extending from target regions to the entire continent of Asia as well as the use of additional genes such as mitochondrial genes.

• Journal of Industrial Convergence
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• v.16 no.4
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• pp.33-46
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• 2018

Personal credit scoring is an effective tool for banks to properly guide decision profitably on granting loans. Recently, many classification algorithms and models are used in personal credit scoring. Personal credit scoring technology is usually divided into statistical method and non-statistical method. Statistical method includes linear regression, discriminate analysis, logistic regression, and decision tree, etc. Non-statistical method includes linear programming, neural network, genetic algorithm and support vector machine, etc. But for the development of the credit scoring model, there is no consistent conclusion to be drawn regarding which method is the best. In this paper, we will compare the performance of the most common scoring techniques such as logistic regression, neural network, and support vector machines using personal credit data of the financial institution in China. Specifically, we build three models respectively, classify the customers and compare analysis results. According to the results, support vector machine has better performance than logistic regression and neural networks.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.103-111
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• 2012

PURPOSES : Effective speed management is necessary for preventing traffic crashes on the road. Speed hump is known as an effective tool for managing speed. Unlike existing studies which are mainly focused on humps for vehicles, this study proposed a novel method to determine design parameters for bicycle speed humps based on a multi-criteria decision making process. METHODS : Three objectives including the effectiveness of speed reduction, bicycle safety, and user's comfortability were incorporated into the proposed evaluation framework for determining design parameters. A multi-criteria value function was also derived and utilized as a part of the proposed method. RESULTS : Extensive simulations and statistical tests show that an integrated bike-box way is identified as the best in terms of operational efficiency and safety. CONCLUSIONS : It is expected that the outcomes of this study can be a valuable precursor for developing design guidelines for bicycle road and facility.

• Architectural research
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• v.7 no.1
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• pp.11-18
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• 2005

In today's building industry the emphasis has been geared more towards construction, thus building maintenance and life cycle have been neglected until now. A direct result of this neglect is the rapid aging of building, which leads to more cost-effective decision making methods for the prolongation of building life span. The following study is conducted in the area of Daegu and Seoul in order to develop the estimation analysis method of the annual operation cost of the Korean high-rise condominiums for the cost-effective decision making support through mathematical and statistical analyses including the present value and standardized measurement corrections. Based on the assumption that the life expectancy of the high rise condominium is 50 years, initial cost is ￦421,212/$m^2$, and a total sum of yearly operation cost during life expectancy is ￦2,154,499//$m^2$), yearly accumulated operation cost is shown as below: $AOC=0.7097t^4-38.803t^3+806.95t^2+11045t-496.52$ ($R^2=0.98$) (Here, AOC = Accumulated Operation Cost, t = given years)

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1272-1275
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• 2002

Watermark detection plays a crucial role in multimedia copyright protection and has traditionally been tackled using correlation-based algorithms. However, correlation-based detection is not actually the best choice, as it does not utilize the distributional characteristics of the image being marked. Accordingly, an efficient watermark detection scheme for DWT coefficients is proposed as optimal for non-additive schemes. Based on the statistical decision theory, the proposed method is derived according to Bayes' decision theory, the Neyman-Pearson criterion, and the distribution of the DWT coefficients, thereby minimizing the missed detection probability subject to a given false alarm probability. The proposed method was tested in the context of robustness, and the results confirmed the superiority of the proposed technique over conventional correlation-based detection method.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.2
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• pp.1-16
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• 1996

The personality types developed by Gustav Jung are frequently used to identify peopl's decision-making style, especially to determine which functions are dominant ones in the perception and the processing of information. In this paper, the Jungian typology is utilized to investigate if there are any systematic relations between an individual's personality type and her/his attitude toward risk. For this purpose, an experiment was conducted where 99 subjects, mostly students, participated in a computer-simulated horse racing game. Each subject's risk-seeking propensity was measured by the winning chance of the selected horse and the amount of stakes. The results of the experiment show that a decision-maker who is extrovert (E) is attitude and intutive(N) in perception of information is more likely to be risk prone than the introvert(I) and sensing(S) type. Feeling(F) function in information processing seems to induce more risk seeking attitude than thinking (T) function, but the statistical significance could not be found from the data, for this statement.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.39-48
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• 2012

This article presents a way of tackling a special class of space optimization problems that arise in a number of practical applications in industry and elsewhere. It presents an elegant solution to a problem that was considered by (Das, 2005) in optimizing storage space in warehouse of a footwear manufacturing company. In (Das, 2005), the problem was formulated as a nonlinear programming problem. In this article, it is shown that the problem can be formulated as a generalized transportation problem which is a special case of generalized network flow problems. Further, an elegant scheme is devised to handle the dynamic situation of warehousing problem which can be easily translated into a decision support system for the warehouse management system. Also, the article points out certain obscurities and gaps in (Das, 2005).

• The Journal of Information Systems
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• v.15 no.1
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• pp.121-144
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• 2006

For constructing the purchasing decision-making model to maximize customer value on the electronic commerce, Means-Ends Network model was used for identifying means and fundamental objectives and their relationships were analyzed by the structural equation. A questionnaire survey of 481 customers in their internet shopping experiences was conducted to extract valid means and fundamental objectives' factors. As a result, 6 means objectives shopping travel, shipping errors, vendor trust, online payment, product choice, and recommender systems and 3 fundamental objectives-shopping convenience, internet ecology, and customer support were founded. Using these 9 factors, structural equation was analyzed 4 times to ensure statistical validities and to establish new interrelationships among them. The results showed that fundamental objectives are affected by the strong relationships within means objectives. This interrelationship with mens and fundamental objectives is interpreted as the purchasing decision-making model to maximize customer value on the electronic commerce in this paper.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.250-251
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• 2021

A subcontract work order is the basis of the construction process and consists of the root and trunk of the construction industry. The construction process through a subcontract work order is an important element of project success, and it is the basic unit of creating profit in the construction industry. Therefore, correct analysis and forecasting of subcontract work orders allow correct estimation of construction cost and profit which is the foundation of corporate decision making. This study has started to provide predictions of subcontractor's bidding-ratio for decision-making. Since the actual project data has been used in this study, the contribution level of the model is highly expected in actual field. The statistical confidential level of adjusted decision coefficient is concluded low because of limited sample numbers. However, its accuracy and confidence level can be increased through increasing sample numbers, considering more variables, and studying of reducing error.