• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.11-17
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• 2016

In this paper, we propose a method of correcting depth image by the plane modeling and then improving the coding performance. We model a plane by using the least squares method to the horizontal and vertical directions including the target pixel, and then determine that the predicted plane is suitable from the estimate error. After that, we correct the target pixel by the plane mode. The proposed method can correct not only the depth image composed the plane but also the complex depth image. From the simulation result that measures the entropy power, which can estimate the coding performance, we can see that the coding performance by the proposed method is improved up to 80.2%.

• The Journal of Society for e-Business Studies
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• v.14 no.3
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• pp.15-37
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• 2009

This study presents a new retrieval system developed to consider various preferential requirements for buyers in the real estate market. The paper analyses essential factors affecting the price of real estate and then a set of factors are classified by region-related factor and individual-related factor. After endowing the buyer's selected factors with weights in the retrieval system, the optimal solutions have been drawn by comparing with the others through an entropy measure of Multi-attribute Decision Making. This retrieval system is applied to the Busan real estate market to estimate the solutions of retrieval. Evaluation results indicate that the retrieval system can provide useful information to analyse the price determination factors of real estate, as well as to save the searching cost of the buyers.

• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.9-15
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• 2013

In this study, texture feature analysis (TFA) algorithm to automatic recognition of liver disease suggests by utilizing computed tomography (CT), by applying the algorithm computer-aided diagnosis (CAD) of hepatocellular carcinoma (HCC) design. Proposed the performance of each algorithm was to comparison and evaluation. In the HCC image, set up region of analysis (ROA, window size was $40{\times}40$ pixels) and by calculating the figures for TFA algorithm of the six parameters (average gray level, average contrast, measure of smoothness, skewness, measure of uniformity, entropy) HCC recognition rate were calculated. As a result, TFA was found to be significant as a measure of HCC recognition rate. Measure of uniformity was the most recognition. Average contrast, measure of smoothness, and skewness were relatively high, and average gray level, entropy showed a relatively low recognition rate of the parameters. In this regard, showed high recognition algorithms (a maximum of 97.14%, a minimum of 82.86%) use the determining HCC imaging lesions and assist early diagnosis of clinic. If this use to therapy, the diagnostic efficiency of clinical early diagnosis better than before. Later, after add the effective and quantitative analysis, criteria research for generalized of disease recognition is needed to be considered.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.193-202
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• 2005

Due to the importance of SCM(Supply Chain management) in business logistics. many studies related to the SCM performance measurement have been conducted. However, previous SCM performance measurement models have not reflected both ways, operational efficiency and response for market shift. The aim of this research is to suggest a dynamic model to measure SCM performance both with operational efficiency and response for market shift, based on previous SCOR model. To achieve this aim, we developed a cognitive map-based model described eleven KPIs (Key Performance Indicators) with different weight values. And, to measure response level for market shift, we used the concept of entropy-elasticities. Finally, through some actual cases, merits that have no previous models were shown.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4893-4901
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• 2013

In order for a machine, especially used in the defense industry, to consistently operate during its life-time, lots of study has been done in machine design as well as machine maintenance. However, the realistic study is necessary in management and operation of a military support facility, where spare parts are stored and retrieved. In this paper, efficient arrangement of spare parts are proposed to acquire increased in efficiency and decreased in cost for operation management of the military support facility. First, spare parts is assorted by MTBF(Mean Time Between Failure) and divided in to three groups A/B/C as an alternative arrangement. Each defined alternatives will go under simulations and RULA(Rapid Upper Limb Assessment), which is posture classification scheme evaluation attributes, to find working time and posture difficulty and lastly by entropy measurement to be selected. This research proposes the efficient spare parts arrangement in military support facility to minimize working time and posture difficulty. By taking system and human engineering approach together into consideration, it will lead to show a specific value.