• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.193-207
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• 2001

When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

• IE interfaces
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• v.20 no.1
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• pp.41-48
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• 2007

The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

• Journal of Drive and Control
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• v.20 no.3
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• pp.9-14
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• 2023

In this paper, the selection of a reliable accelerated life test code for a 2-ton forklift was accomplished by choosing the driving resistance coefficient failure-free test time based on a 10,000-hour B₁₀ life. The overall life and average equivalent load of the vehicle were then calculated based on actual driving test conditions using the selected driving resistance coefficient. The gear train's accelerated life test code was selected by adjusting the equivalent load to a torque and rotation speed that did not exceed 125%(about 75HP) of the vehicle rated power. The safety of the test standards was validated by conducting an actual accelerated life test utilizing the proposed test method in this study and comparing the test result with the corresponding theoretical value. It is anticipated that the reliability of the accelerated life test in this paper will be enhanced, by incorporating actual driving performance data collected directly from the forklift and adjusting the conditions used in developing the accelerated life test code.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.15-25
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• 2002

This paper considers supplier selection process for e-business & ISO 9001 quality management system environments. Determining suitable suppliers in the electronic commerce has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In this paper, a Quality Estimated Supplier Selection (QESS) model is proposed to deal with the supplier selection problems in the e-business(Business to Business: B to B). In the supplier selection, quality management factors will be considered for the first time, and then price, and delivery etc. In the first level, we deal with the quality management factors such as quality management audit, product test, engineering man-power, capability index and training time etc., based on the five point scale. In the second level, a QESS model determines the final solution by considering factors such as price, production lead-time and delivery time.

• Journal of Korea Trade
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• v.26 no.3
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• pp.102-116
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• 2022

Purpose - This paper empirically investigates the relationship between firm productivity and importing intermediate inputs in the Korean manufacturing sector. Design/methodology - This paper tests the two related hypotheses on the relationship between importing and productivity for a sample of Korean manufacturing firms. We test the self-selection hypothesis by comparing pre-entry levels of productivity between importers and non-importers. We test the learning-by-importing hypothesis by employing propensity score matching with differencein-differences approach. Findings - Future importers are more productive than future non-importers years before they start to import, which supports the self-selection hypothesis. In contrast, there is no strong evidence for learning-by-importing. Originality/value - This paper is the first study to explore the relationship between importing and firm-level productivity for Korean firms. The results have an important implication on trade policies to lower or raise trade barriers in imported inputs.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.5-8
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• 2003

This paper presents a methodology to be able to select an appropriate RP system that suits the end use of a part. Evaluation factors used in process selection include major attributes such as accuracy, roughness, strength, elongation, part cost and build time that greatly affect the performance of RP systems. Crisp values such as accuracy and surface roughness are obtained with a new test part developed. The test part is designed with conjoint analysis to reflect users' preference. The part cost and build time that have approximate ranges due to cost and many variable parameters are presented by linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application is selected by using the modified TOPSIS(Technique of Order Preference by Similarity to Ideal Solution) method. It uses crisp data as well as linguistic variables, and each weight on the alternatives is assigned by using pair-wise comparison matrix. The ranking order helps the decision making of the selection of RP systems.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.11-18
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• 2004

It is making researches in questions selection method for examination in web-based education system. Most questions made for these remote examinations use methods of making questions using fixed questions or randomly using item pools or automatically using degree of difficulty. This paper proposes a new examination questions selection algorithm in web-based education system for engineer test. Generally, Engineer test is characterized by adequate examination questions selection for degree of difficulty and equally between all units. Therefore this algorithm selected examination questions equally well as regards degree of difficulty and distribution between all units. This algorithm providers more effective education examination method as compared with previous algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1521-1524
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• 2003

In this paper, we propose a "Distance Correlation Selection operator (DCS)" as a new selection operator. For Genetic Algorithm (GA), many improvements have been proposed. The MGG (Minimal Generation Gap) model proposed by Satoh et.al. shows good performance. The MGG model has all advantages of conventional models and the ability of avoiding the premature convergence and suppressing the evolutionary stagnation. The proposed method is an extension of selection operator in the original MGG model. Generally, GA has two types of selection operators, one is "selection for reproduction", and the other is "selection for survival"; the former is for crossover and the latter is the individuals which survive to the next generation. The proposed method is an extension of the former. The proposed method utilizes distance information between individuals. From this extension, the proposed method aims to expand a search area and improve ability to search solution. The performance of the proposed method is examined with several standard test functions. The experimental results show good performance better than the original MGG model.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.901-904
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• 2005

Testing of mixed-signal circuit has become a difficult task for test engineers and efficient test solution to these problems are needed. In this paper a new specification-based mixed-signal test method called TSS(Time Slot Specification) using high performance current sensors and a novel test point selection technique without heavy computational overhead are proposed. External output and power nodes are used for test points and accessed by the current sensors in the ATE.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.130-138
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• 2023

The selection of the correct examination variables for diagnosing heart disease provides many benefits, including faster diagnosis and lower cost of examination. The selection of inspection variables can be performed by referring to the data of previous examination results so that future investigations can be carried out by referring to these selected variables. This paper proposes a model for selecting examination variables using an Artificial Bee Swarm Optimization method by considering the variables of accuracy and cost of inspection. The proposed feature selection model was evaluated using the performance parameters of accuracy, area under curve (AUC), number of variables, and inspection cost. The test results show that the proposed model can produce 24 examination variables and provide 95.16% accuracy and 97.61% AUC. These results indicate a significant decrease in the number of inspection variables and inspection costs while maintaining performance in the excellent category.