• International Journal of CAD/CAM
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• v.8 no.1
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• pp.37-40
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• 2009

Based on the study of Digital Elevation Simplification Model and fractal theory, this paper put forward a new method to simulate complex terrain. That use simplified DEM data to construct terrain frame based on the quad tree at first, and then use fractal to generate the details of every node of the tree. In the process of construction, the LOD theory is used to simplify the terrain and get its typical data. According to the change of view position and direction, the paper gives a new way to judge the visibility of the surface patch. Experimental results show that this algorithm is simple, efficient and supports the real time dynamic simulation of terrain model.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.580-588
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• 1999

The reuse of software components from existing software system enhances productivity and reliability, decreases the cost of production in software development. The extraction of software components with high reusability from existing software system is very important in software reuse. The reuse of a class is classified into white-box reuse to reuse with modification and black-box reuse to reuse without modification. A class has the property of procedural language and object-oriented language. Therefore, it must measure reusability in consideration of two properties. In black-box reuse, independence of class is important quality. It can quantify through information hiding, coupling between objects, cohesion, etc. In white-box reuse, modification is the best important quality. It can quality through class complexity, coupling, cohesion, documentation, etc. We propose a new model for measurement of class reusability and the measure criteria in object-oriented program. A class that is measured by proposed model can judge whether the reuse with modification has the advantage or the reuse without modification has the advantage.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.245-250
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• 2001

Nowadays, there has been extreme competition due to market reduction in the domestic construction industry. In this situation, Korean construction companies are focused in the area of planning development housing project, which should maximize profit for a project. The most important step in this project is the business planning stage which judge whether it could come true or not. Each company has its own planning process model, but there hasn't been any standard model for the business planning process. To solve this problem in Korean construction companies, this study identifies the existing business planning process in the domestic construction companies finds out its problems, and suggests solutions for thorn. And Finally a business planning process model is proposed for success in development housing projects.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.132-135
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• 2022

Recently, with the development of IoT communication technology, products and services that detect and inform the surrounding environment under the name of smart plugs are being developed. In particular, in order to prepare for fire or gas leakage accidents, products that automatically close and warn when abnormal symptoms occur are used. Most of them use methods of collecting, analyzing, and processing information through networks. However, there is a disadvantage that it cannot be used when the network is temporarily in a failed state. In this paper, sensor information was analyzed using deep learning, and a model that can predict abnormal symptoms was learned in advance and applied to MCU. The performance of each model was evaluated by developing firmware that can judge and process on its own regardless of network and applying a predictive model to the MCU after 3 to 120 seconds.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.415-419
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• 2013

To mitigate forest fire damage, it is needed to concentrate suppression resources on the fire having a high probability to become large in the initial stage. The objective of this study is to develop the large fire judgement model which can estimate large fire possibility index between the fire size and the related factors such as weather, terrain, and fuel. The results of logistic regression equation indicated that temperature, wind speed, continuous drought days, slope variance, forest area were related to the large fire possibility positively but elevation has negative relationship. This model may help decision-making about size of suppression resources, local residents evacuation and suppression priority.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.3 s.43
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• pp.223-232
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• 1992

The ultimate purpose of this study is to build a model on clothing satisfaction which extends the consumer satisfaction model by unifying the exportation antecedents. In the literature study, it is proposed to clarify the concepts on the clothing satisfaction, and to investigate the present paradigms of the consumer satisfaction. It is widely accepted by the clothing researchers that the clothing satisfaction is a comparative process in which the evaluation criteria are used to judge the clothing product and to access the disconfirmation. In the Disconfirmation paradigm, the role of the expectation is very important. We propose to classify the expectation into the expective expectation and the normative expectation. The normative expectation applies when the investment cost and effort are considered. The expectation is shown to be affected by the expectation antecedents of the product characteris-tics, the situation characteristics, and the consumer characteristics. We investigate in detail those clothing satisfaction determinants and their measurement methods. Then, we build a clothing satisfaction model by the disconfirmation paradigm which is composed of the expectation antecedents, the expectation (expective expectation, normative expectation), the perceived clothing product performance, and the disconfirmation.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1643-1656
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• 2010

It is necessary to develop a system to judge inferiority of goods to minimize the loss at small factories in which produces various kinds of goods with small amounts. That system can be developed based on HTM theory. HTM is a model to apply the operation principles of the neocortex in human brain to the machine learning. We have to build the trained HTM network to use the HTM-based machine learning system. It requires the knowledge for the HTM theory. This paper presents the design and implementation of the training system to support the development of HTM networks which recognize the molding parts to judge its badness. This training system allows field technicians to train the HTM network with high accuracy without the knowledge of the HTM theory. It also can be applied to any kind of the HTM-based judging systems for molding parts.

• The Journal of Korean Association of Computer Education
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• v.17 no.4
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• pp.45-57
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• 2014

Many studies on algorithm judging system which verifies the correctness and the time efficiency of your program have been underway recently, most of which are on an online judging system focused on programming contests. However this study is mainly about development and application of the judging system based on client-server. Especially, we designed to promote metacognition and motivation which are emphasized in CRESST model, and implemented the total system that consists of the problem, data set, validation program, and user service environments. We applied our system to elementary, middle, and high school students, and We noticed a significant difference of average score between the experimental and control group in posttest and concluded that the teaching method using our system gave the bigger positive effects on programming learning.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.5
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• pp.197-205
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• 2011

Since Intelligent Transport Systems(ITS) is a complex project combining technology and system of transportation, information and communication and civil engineer, it needs a specialized management activities. However, it is difficult to judge who has responsibility for a shoddy and fault construction since the role between project management and supervision is very ambiguous. The aim of this study is propose an efficient project management and supervision for ITS reflecting the characteristics of ITS. Therefore, we suggest a statistical models using nonlinear regression model to prepare the project management and supervision compensation criteria, hence, we choose the realistic and validation statistical model.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.9
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• pp.1225-1228
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• 2006

A total of 1,367 first lactation records of daughters of 81 sires, having 5 or more progeny were used to evaluate sires by 3 different methods viz., least squares (LS), best linear unbiased prediction (BLUP) and derivative free restricted maximum likelihood (DFREML) method. The highest and lowest overall average breeding value of sires for first lactation 305 days or less milk yield was obtained by BLUP (1,520.72 kg) and LS method (1,502.22 kg), respectively. The accuracy, efficiency and stability of different sire evaluation methods were compared to judge their effectiveness. The error variance of DFREML method was lowest ($191,112kg^2$) and its coefficient of determination of fitting the model was highest (33.39%) revealing that this method of sire evaluation was most efficient and accurate as compared to other methods. However, the BLUP method was most stable amongst all the methods having coefficient of variation (%) very near to unadjusted data (18.72% versus 19.89%). The higher rank correlations (0.7979 to 0.9568) between different sire evaluation methods indicated that there was higher degree of similarity of ranking sires by different methods ranging from about 80 to 96 percent. However, the DFREML method seemed to be the most effective sire evaluation method as compared to other methods for the present set of data.