• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.91-91
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• 1989

Neural Network(NN) is known to be suitable for forecasting corporate bankruptcy because of discriminant capability. Bandkruptcy prediction on NN by now has mostly been studied based on financial indices at specific point of time. However, the financial profile of corporates fluctuates within a certain range with the elapse of time. Besides, we need a lot of data of different bankrupt types in order to apply NN for better bankruptcy prediction. Therefore, We have decided to focus on textile and clothing industries for bankruptcy prediction with limited data. One part of the collected data was used for training and calibration, and the other was used for verification. The model makes a learning with extended data from financial indices at specific point of time. The trained model has been tested and we could get a high hitting ratio relatively.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.4
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• pp.54-65
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• 2000

The purpose of this paper is to examine the concept, general framework, planning process of bioregion, and bioregional impacts on landscape planning of future and to discuss the application possibility of landscape planning. Bioregionalism is defined in the course of following: knowing the land, learning the lore, developing the potential, liberating the self. Bioregional paradigm was composed of policy system insisted on diversity and decentralization based on region and community, sustainable economy structure focused on conservation and stability, and society structure through cooperation with common consciousness in the community. A general bioregional framework was organized to be able to achieve a sustainable future with interaction for humans being, other living things, and important earth life system. Bioregional mapping should be able to explain three important aspects about how localised and sustainable cultures would exist: to define the external boundaries, to describe forces of energy, and give a hint for th productive capability. In conclusion, according to the result of reviewing the total environmental planning, bioregional paradigm, examples of projects, technique of bioregional mapping, and actions of Nongovernmental Organizations(NGOs). this study is helpful to show an applicability of bioregional planning theory in Korea

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.360-376
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• 2020

Many heuristic attribute reduction algorithms have been proposed to find a single reduct that functions as the entire set of original attributes without loss of classification capability; however, the proposed reducts are not always perfect for these multiclass datasets. In this study, based on a probabilistic rough set model, we propose the class-oriented attribute reduction (COAR) algorithm, which separately finds a reduct for each target class. Thus, there is a strong dependence between a reduct and its target class. Consequently, we propose a type of ensemble constructed on a group of classifiers based on class-oriented reducts with a customized weighted majority voting strategy. We evaluated the performance of our proposed algorithm based on five real multiclass datasets. Experimental results confirm the superiority of the proposed method in terms of four general evaluation metrics.

• Journal of Engineering Education Research
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• v.14 no.6
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• pp.51-59
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• 2011

The authors have developed a reading & writing textbook for engineering students to improve their communication capability, and also analyzed the outcomes that the students accomplished through the Engineering Reading and Writing class. The reading & writing textbook has been organized to be used as a guidebook with which the engineering students can practically solve the problems that they would face continuously after they finish their regular curriculum and when they are employed. The questionnaire survey analysis has been performed in order to evaluate the textbook contents, lecturing, and learning outcomes for the lecturers and students finished the engineering reading and writing classes. Desirable evaluation has been resulted in the broad areas: subject extraction from the readings, logical understanding, summarizing, practical writing, writing principle, etc.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.260-266
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• 1996

In this paper, we presents neural network identification and control of highly complicated nonlinear Left Ventricular Assist Device(LVAD) system with a pneumatically driven mock circulation system. Generally the LVAD system need to compensate nonlinearities. Hence, it is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with Neural Network Identification. Once the NNI has learned the dynamic model of LVAD system, the other network, called Neural Network Controller(NNC), is designed for control of a LVAD system. The ability and effectiveness of identifying and controlling a LVAD system using the proposed algorithm will be demonstrated by computer simulation.

• Research in Mathematical Education
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• v.15 no.1
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• pp.15-30
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• 2011

We study to design educational Logo-based microworld environment equipped with 3D construction capability, 3D manipulation, and web-based communication. Extending the turtle metaphor of 2D Logo, we design simple and intuitive symbolic representation system that can create several turtle objects and operations. We also present various mathematization activities applying the turtle objects and suggest the way to make good use of them in mathematics education. In our microworld environment, the symbolic representations constructing the turtle objects can be used for web-based collaborative learning, communication, and assessments.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.53-68
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• 2013

Purpose: The paper presents research that examine relationship difference education quality, satisfaction, loyalty in university education sector. Specifically, the effects of difference education quality on student satisfaction and loyalty in the context of education quality are examined. Methods: A model of difference education quality effect on student satisfaction and loyalty is introduced and tested in the university using student perceptions of provider. Questionnaire was developed, and data was collected and analyzed for this study with SEM(Structural Equation Modeling). Results: The results are as follows: Education capability, BNIE(Business Newspaper In Education) are significantly influenced on student satisfaction. In addition, student satisfaction is significantly influence on external customer satisfaction, professor image. Professor image is significantly influence on student loyalty. Conclusion: Upon learning of student need and want, professor can focus on development of difference education quality based on student need and want.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3992-4005
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• 2018

In our current information-based society in which knowledge is a fundamental asset to production, the capability to utilize information and produce knowledge with the use of information technology (IT) has become essential to learning. Massive Open Online Courses (MOOCs) have recently been introduced in light of such changes and are recognized as an alternative to open education. MOOCs' capabilities are being acknowledged in lifelong education in terms of reeducation and knowledge sharing, and also in terms of improving teaching quality, and improving university students' levels of creativity and integrated thinking by supporting high-level content and teaching. Therefore, this study presents an extended research model that combines information system (IS) continuance and task-technology fit models. Our study researches previous literature, revealing factors of continuous use after accepting MOOCs from the learner's perspective, and analyzes the model empirically. The ideal environment for MOOCs learners is evaluated, and a strategic approach to the successful settlement and diffusion of MOOCs is presented based on this study's findings.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.251-258
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• 2005

Automatic document classification may differ significantly according to the characteristics of documents that are subject to classification, as well as classifier's performance. This research identifies e-mail document's characteristics to apply a three-step preprocessing algorithm that can minimize e-mail document's atypical characteristics. In the first 5go, uncertain based sampling algorithm that used Mean Absolute Deviation(MAD), is used to address the question of selection learning document for the rule generation at the time of classification. In the subsequent stage, Weighted vlaue assigning method by attribute is applied to increase the discriminating capability of the terms that appear on the title on the e-mail document characteristic level. in the third and last stage, accuracy level during classification by each category is increased by using Naive Bayesian Presumptive Algorithm's Dynamic Threshold. And, we implemented an E-Mail Recommendtion System using a three-step preprocessing algorithm the enable users for direct and optimal classification with the recommendation of the applicable category when a mail arrives.