• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.19-29
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• 2015

The purpose of this study is to suggest the grid search method for selecting an optimal decision tree model. It chooses optimal values for the maximum depth of tree and the minimum number of observations that must exist in a node in order for a split to be attempted. Therefore, the grid search method guarantees building a decision tree model that shows more precise and stable classifying performance. Through empirical analysis using data of job satisfaction of workplace reserve force commanders, we show that the grid search method helps us generate an optimal decision tree model that gives us hints for the improvement direction of labor conditions of Korean workplace reserve force commanders.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.3
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• pp.347-355
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• 2001

A heat transfer analysis in a ventilation chamber of Plasma Display Panel(PDP) has been conducted. The process requirement is to precisely follow prescribed temperature trajectory while maintaining temperature uniformity for each panel. Firstly, experiment in a test chamber has been carried out and the results are compared with the unsteady 3D numerical data. Reasonable agreement was found, which suggested that the employed numerical model had its credibility in actual PDP ventilation processes. On this ground, a tact-type heating/cooling system was analyzed. The panel temperature in the 40$^{\circ}C$ tact-type system was more uniform than that in the 80$^{\circ}C$ one. For improving the uniformity of panel temperature, relocation of ventilation head to the rear part and inlet flow control are required. Comparison of full simulation of a cart and simplified simulation of one panel indicates the optimized panel pitch can also be predicted.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.111-126
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• 2021

A Kano model was used to classify the quality attributes of the service robot function for actual deployment that can support and replace bank employees. Quality attributes for a total of 6 dimensions and 23 service elements were divided into bank employees and customer groups, and service priorities were derived after comparative analysis. The Decision tree model was used to supplement the excessive simplification of quality attributes by the modest number of Kano models and to classify and predict by segment market. Of the 23 services, 16 were classified into the same attributes in both groups. 6 services classified as combination attributes used a Decision tree to identify differences in perception of quality attributes among groups. In terms of basic financial services and professional financial services, it was confirmed that bank employees feel financial service robots more attractive than ordinary customers. In the design of IT convergence service, we propose a methodology for deriving quality attributes by combining a Kano model for classifying quality attributes of two groups and a Decision tree for forecasting subdivision markets.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.693-701
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• 2012

Recently, the number of students who get double majors has tended to increase in many universities. As results, many problems occur because immoderate inflow of double-major students is concentrated in a specific popular department. In this paper, we study the characteristic of inflow and outflow of double majors using social network analysis and decision tree analysis. According to the results, SAT score affected the inflow of double majors the most. Additionally, department category, course evaluation score, employment rate also affected the inflow of double majors in the order named. On the other hand, department category affected the outflow of double majors the most. Additionally, SAT score, employment rate, course evaluation score also affected the outflow of double majors in the order named.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.55-61
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• 2024

In response to the COVID-19 pandemic, the logistics industry in Korea has rapidly been expanding, with offline demand concentrating on online platforms owing to the development of digital infrastructure. This has increased the workload of courier drivers considerably, along with labor intensity. A delivery driver died recently from overwork due to the continuous increase in delivery volume, which raises social concerns. Delivery drivers work long hours, (over 12 hours) and are greatly affected by weather conditions, such as snow, rain, heat waves, and cold waves. In addition, they lack a fixed workplace; perform atypical work handling workpieces of various sizes, weights, and shapes; and spend a large amount of time driving as part of their work. This work involves a high level of tension and requires attention and concentration. Despite the frequency of industrial accidents in the courier industry, studies on safety and health to quantitatively analyze and systematize the work of courier workers are very scarce. Therefore, to define the work process necessary for investigating the harmful factors in delivery service and the work analysis, this study conducted interviews and on-site surveys to analyze the unit work of the delivery service by targeting delivery workers. In other words, a framework of unit work for work analysis was presented to enable research and analysis by considering the aforementioned characteristics of the courier industry. The process was broadly divided into work, transport, storage, delay, and inspection. Work was divided into loading, sorting, unloading, and door subcategories, and transportation was divided into vehicle, cart, and walking subcategories as well as 10 small processes. Moreover, 22 unit works were again drawn by conducting field surveys and interviews. The risk of unit work derived from this study was ergonomically evaluated, and the ergonomic analysis revealed that uploading and transportation were the most dangerous. The results of this study could be used as basic data for preventing industrial accidents among courier workers, whose work has increased with the logistics volume and the development of the logistics industry.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.624-634
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• 2016

Nuclear criticality safety analyses (NCSAs) considering burnup credit were performed for the GBC-32 cask. The used nuclear fuel assemblies (UNFAs) discharged from Hanbit Nuclear Power Plant Unit 3 Cycle 6 were loaded into the cask. Their axial burnup distributions and average discharge burnups were evaluated using the DeCART and Multi-purpose Analyzer for Static and Transient Effects of Reactors (MASTER) codes, and NCSAs were performed using SCALE 6.1/STandardized Analysis of Reactivity for Burnup Credit using SCALE (STARBUCS) and Monte Carlo N-Particle transport code, version 6 (MCNP 6). The axial burnup distributions were determined for 20 UNFAs with various initial enrichments and burnups, which were applied to the criticality analysis for the cask system. The UNFAs for 20- and 30-year cooling times were assumed to be stored in the cask. The criticality analyses indicated that $k_{eff}$ values for UNFAs with nonuniform axial burnup distributions were larger than those with a uniform distribution, that is, the end effects were positive but much smaller than those with the reference distribution. The axial burnup distributions for 20 UNFAs had shapes that were more symmetrical with a less steep gradient in the upper region than the reference ones of the United States Department of Energy. These differences in the axial burnup distributions resulted in a significant reduction in end effects compared with the reference.

• Journal of Engineering Education Research
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• v.13 no.4
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• pp.51-59
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• 2010

In order to manage the lectures efficiently in the university and improve the educational outcome, the process is needed that make diagnosis of the present educational outcome of each classes on a lecture and find factors of educational outcome. In most studies for finding the factors of the efficient lecture, statistical methods such as association analysis, regression analysis are used usually, and recently decision tree analysis is employed, too. The decision tree analysis have the merits that is easy to understand a result model, and to be easy to apply for the decision making, but have the weaknesses that is not strong for characteristic of input data such as multicollinearity. This paper indicates the weaknesses of decision tree analysis, and suggests the experimental solution using multiple decision tree algorithm to supplement these problems. The experimental result shows that the suggested method is more effective in finding the reliable factors of the educational outcome.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• Investigative Magnetic Resonance Imaging
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• v.26 no.1
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• pp.20-31
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• 2022

Purpose: To assess conventional MRI features associated with residual soft-tissue sarcomas following unplanned excision (UPE), and to compare the diagnostic performance of conventional MRI only with that of MRI including diffusion-weighted imaging (DWI) for residual tumors after UPE. Materials and Methods: We included 103 consecutive patients who had received UPE of a soft-tissue sarcoma with wide excision of the tumor bed between December 2013 and December 2019 and who also underwent conventional MRI and DWI in this retrospective study. The presence of focal enhancement, soft-tissue edema, fascial enhancement, fluid collections, and hematoma on MRI including DWI was reviewed by two musculoskeletal radiologists. We used classification and regression tree (CART) analysis to identify the most significant MRI features. We compared the diagnostic performances of conventional MRI and added DWI using the McNemar test. Results: Residual tumors were present in 69 (66.9%) of 103 patients, whereas no tumors were found in 34 (33.1%) patients. CART showed focal enhancement to be the most significant predictor of residual tumors and correctly predicted residual tumors in 81.6% (84/103) and 78.6% (81/103) of patients for Reader 1 and Reader 2, respectively. Compared with conventional MRI only, the addition of DWI for Reader 1 improved specificity (32.8% vs. 56%, 33.3% vs. 63.0%, P < 0.05), decreased sensitivity (96.8% vs. 84.1%, 98.7% vs. 76.7%, P < 0.05), without a difference in diagnostic accuracy (76.7% vs. 74.8%, 72.9% vs. 71.4%) in total and in subgroups. For Reader 2, diagnostic performance was not significantly different between the sets of MRI (P > 0.05). Conclusion: After UPE of a soft-tissue sarcoma, the presence or absence of a focal enhancement was the most significant MRI finding predicting residual tumors. MRI provided good diagnostic accuracy for detecting residual tumors, and the addition of DWI to conventional MRI may increase specificity.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.3
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• pp.59-76
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• 2008

Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.