• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.183-203
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• 1993

One of the most difficult and time-consuming stages in the development of the knowledge-based system is a knowledge acquisition. A splitting algorithm is developed to infer a rule-tree which can be converted to a rule-typed knowledge. A market segmentation may be performed in order to establish market strategy suitable to each market segment. As the sales data of a product market is probabilistic and noisy, it becomes necessary to prune the rule-tree-at an acceptable level while generating a rule-tree. A splitting algorithm is developed using the pruning measure based on a total amount of information gain and the measure of existing algorithms. A user can easily adjust the size of the resulting rule-tree according to his(her) preferences and problem domains. The algorithm is applied to a market segmentation problem of a medium-large computer market. The algorithm is illustrated step by step with a sales data of a computer market and is analyzed.

• Journal of the Korea Safety Management & Science
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• v.14 no.2
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• pp.237-243
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• 2012

The more the satisfied customers increases in customer satisfaction survey, the more the company has difficultly in improving the customer satisfaction. In addition, the effectiveness of practical application of customer satisfaction survey decreases due to its constitution limitation on its data analysis. To overcome these problems, it is necessary to develop a new method to identify the strategy meanings and find the dissatisfied factors of satisfied customers using the satisfied customers reclassification. This study focuses on the satisfied customer segmentation using Latent Class Analysis. The case study shows that the satisfied customers are divided into three subgroups using Latent Class Analysis and we draw meaning results such as satisfaction and dissatisfaction factors through analyzing each group. This study is expected to play the role as the groundwork for the revitalization of customer satisfaction survey.

• Journal of The Korean Digital Architecture Interior Association
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• v.8 no.1
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• pp.39-47
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• 2008

This study aims to provide the guidelines for planning and operating convention centers. A case study is utilized with the units of analysis, including Seoul COEX, Busan BEXCO, Daegu EXCO, Jeju ICCJEJU, Ilsan KINTEX, Gwangju KDJ Center, and Changwon CECO. The findings related to the operation of convention centers in Korea are summarized as follows: the interation of similar conventions; an increase in size; globalization; and specialization. With a view of marketing, this study concludes as follows: (1) initial categorization of target markets is needed due mainly to the founding purposes and the site characteristics of the convention centers in question while utilizing market segmentation strategies; (2) a specific target market should be selected and focused on it; and (3) the development strategy of an image and servicescape is demanded to devised in plan.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.345-346
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• 2009

The segmentation of vessel including portal vein, hepatic vein and artery, from Computed Tomography (CT) images plays an important role in the therapeutic strategies for hepatic diseases. Representing segmented vessels in three dimensional spaces is extremely useful for doctors to plan liver surgery. In this paper, proposed method is focused on smoothing technique of segmented 3D liver vessels, which derived from 3D region growing approach. A pixel expand algorithm has been developed first to avoid vessel lose and disconnection cased by the next smoothing technique. And then a binary volume filtering technique has been implemented and applied to make the segmented binary vessel volume qualitatively smoother. This strategy uses an iterative relaxation process to extract isosurfaces from binary volumes while retaining anatomical structure and important features in the volume. Hard and irregular place in volume image has been eliminated as shown in the result part, which also demonstrated that proposed method is a suitable smoothing solution for post processing of fine vessel segmentation.

• Culinary science and hospitality research
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• v.3
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• pp.57-81
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• 1997

Recently foodservice industry marketing environment changes rapidly and the qualitic change of demand is accelerated from high growth phase to low growth on industrial environment. To actively competely with the foreign brands that runs with the developed management skills and enough fund, the domestic should classify the customers first and develop the menu. To introduce the modern management technique to pursue the management utility by establishing the market segmentation forcusing the target market and discriminating strategy of menu and service. The method of this study is focused on the changes of foodservice industrial environment and alternatives.

• Health Policy and Management
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• v.13 no.4
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• pp.84-98
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• 2003

This research objective is to determine the optimal price break points for n­block tariff, because comparing non­linear pricing with uniform pricing on the basis of profit, n­block tariff outperforms two­part tariff, all unit discount price schedule, and uniform pricing. Although the merits of non­linear pricing are well documented, the attempt to practice the non-linear pricing in medical service sector has been relatively rare. The determination of the parameters under n­block tariff is the interesting decision making agenda for marketers. Under n­block tariff, the marketers should decide the optimal price break points and the optimal marginal price for each price zone. The results can be summarized as follows: The researchers found that mixture model can be the feasible methodology for determining the optimal number of n­block tariff and identifying the optimal segmentation criteria. We demonstrate the feasibility and the superiority of the mixture model by applying it to the database of medical examination. The results appear that the number of patients per month can be the optimal segmentation variable. And 6­block tariff is the optimal price break for this medical service.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.637-644
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• 2006

Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.

• Smart Structures and Systems
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• v.29 no.1
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• pp.221-235
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• 2022

Manual inspection of steel box girders on long span bridges is time-consuming and labor-intensive. The quality of inspection relies on the subjective judgements of the inspectors. This study proposes an automated approach to detect and segment cracks in high-resolution images. An end-to-end cascaded framework is proposed to first detect the existence of cracks using a deep convolutional neural network (CNN) and then segment the crack using a modified U-Net encoder-decoder architecture. A Naïve Bayes data fusion scheme is proposed to reduce the false positives and false negatives effectively. To generate the binary crack mask, first, the original images are divided into 448 × 448 overlapping image patches where these image patches are classified as cracks versus non-cracks using a deep CNN. Next, a modified U-Net is trained from scratch using only the crack patches for segmentation. A customized loss function that consists of binary cross entropy loss and the Dice loss is introduced to enhance the segmentation performance. Additionally, a Naïve Bayes fusion strategy is employed to integrate the crack score maps from different overlapping crack patches and to decide whether a pixel is crack or not. Comprehensive experiments have demonstrated that the proposed approach achieves an 81.71% mean intersection over union (mIoU) score across 5 different training/test splits, which is 7.29% higher than the baseline reference implemented with the original U-Net.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.79-87
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• 2010

This paper is proposed that implemental model of customer relationship management system for oriental hospital is designed by customer segmentation using personal information and medical record of outpatients in existing integrated medical information system database. Proposed model can be practical model at once, because it can construct by partial modification of existing medical information system without additional information technology and infrastructure. And, if we use the proper variable and method of customer segmentation according to marketing strategy, it can be flexible customer relationship management system not only improvement of customer satisfaction but also various marketing supports.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.496-500
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• 2015

International construction projects are inherently more risky than domestic projects with multi-dimensional uncertainties that require complementary risk management at both the country and project levels. However, despite a growing need for systematic country evaluations, most studies have focused on project-level decisions and lack country-based approaches for firms in the construction industry. Accordingly, this study suggests data-driven approaches for evaluating countries using two quantitative models. The first is a two-stage country segmentation model that not only screens negative countries based on country attractiveness (macro-segmentation) but also identifies promising countries based on the level of past project performance in a given country (micro-segmentation). The second is a multi-criteria country segmentation model that combines a firm's business objective with the country evaluation process based on Kraljic's matrix and fuzzy preference relations (FPR). These models utilize not only secondary data from internationally reputable institutions but also performance data on Korean firms from 1990 to 2014 to evaluate 29 countries. The proposed approaches enable firms to enhance their decision-making capacity for evaluating and selecting countries at the early stage of corporate strategy development.