• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.111-119
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• 2014

The cloud environment need resource management method that to enable the big data issue and data analysis technology. Existing resource management uses the limited calculation method, therefore concentrated the resource bias problem. To solve this problem, the resource management requires the learning-based scheduling using resource history information. In this paper, we proposes the ART (Adaptive Resonance Theory)-based adaptive resource management. Our proposed method assigns the job to the suitable method with the resource monitoring and history management in cloud computing environment. The proposed method utilizes the unsupervised learning method. Our goal is to improve the data processing and service stability with the adaptive resource management. The propose method allow the systematic management, and utilize the available resource efficiently.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.115-123
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• 2017

The purpose of this research provides analyzes the learning attitude types by Chinese students in Korea. For this purpose, we have adopted of the practical research methodology and quantitative research methodology, which can objectively determine the individual's ideas and behavior of the "Q methodology". To this end, This research is targeted at Chinese students in the students' learning attitude implemented by 4 types and analyzes questionnaires of each type. The analysis results are categorized as the type of learning environment is not satisfied; positively cooperate with the learning process and the environment; the lack of learning motivation; and paradoxical learning state. As a result of this discussion, Chinese students should have clear motivation to learn new things; improve their korean language ability; and need to know their clear learning methods. Nowadays, more and more Chinese students are choosing study abroad. Therefore, the learning attitudes and learning abilities as two of the most important of focus from society.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.125-141
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• 2010

The aim of this paper is to develop a web-based Virtual Learning System for discrete mathematics learning using CAS (Computer Algebra System), The system contains a series of contents that are common between secondary und university curriculum in discrete mathematics such as sets, relations, matrices, graphs etc. We designed and developed web-based virtual learning contents contained in the proposed system based on Mathematia, webMathematica and phpMath taking advantages of rapid computation and visualization. The virtual learning system for discrete math provides movie lectures and 'practice mode' authored with phpMath in order to enhance conceptual understanding of each movie lesson. In particular, matrix learning is facilitated with conceptual diagram that provides interactive quizzes. Once the quiz results are submitted, Bayesian inference network diagnoses strong and weak parts of learning nodes for generating diagnostic reports to facilitate personalized learning. As part of formative evaluation, the overall responses were collected for future revision of the system with 10 university students.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.223-230
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• 2001

Since self-organizing map (SOM) preserves the topology of ordering in input spaces and trains itself by unsupervised algorithm, it is Llsed in many areas. However, SOM has a shortcoming: structure cannot be easily detcrmined without many trials-and-errors. Structure-adaptive self-orgnizing map (SASOM) which can adapt its structure as well as its weights overcome the shortcoming of self-organizing map: SASOM makes use of structure adaptation capability to place the nodes of prototype vectors into the pattern space accurately so as to make the decision boundmies as close to the class boundaries as possible. In this scheme, the initialization of weights of newly adapted nodes is important. This paper proposes a method which optimizes SASOM with genetic algorithm (GA) to determines the weight vector of newly split node. The leanling algorithm is a hybrid of unsupervised learning method and supervised learning method using LVQ algorithm. This proposed method not only shows higher performance than SASOM in terms of recognition rate and variation, but also preserves the topological order of input patterns well. Experiments with 2D pattern space data and handwritten digit database show that the proposed method is promising.

• The Journal of Korean Association of Computer Education
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• v.4 no.2
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• pp.21-29
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• 2001

The purpose of this study is to design and implementation of the Web-based Individual Computerized Adaptive Testing(CAT) system. The Web-based Individual CAT is a kind of test system to present a set of the problems divided into basic level, intermediate level and advanced level according to the saved results after doing a diagnostic test related to each unit. The diagnostic test is done to pull out the necessary items which learners have to study. The strong points of the web-based computerized adaptive testing system are to reduce the problems of distributed teachers and to have the effect of individual learning by using this system.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.121-135
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• 2003

This paper proposes a web-based adaptive tutoring system based on fuzzy set that provides learning materials and questions dynamically according to students' knowledge state, and gives advices for the learning after an evaluation. For this, we design a courseware knowledge structure systematically and then construct a fuzzy level set on the basis of it considering importance of learning targets, difficulty of learning materials and relation degree between learning targets and learning materials. Using the fuzzy level set, our system offers learning materials and questions to adapt to individual students. Moreover, a result of the test is evaluated with fuzzy linguistic variable. Appling the fuzzy concept to the tutoring system could naturally consider and deal with various and uncertain items of learning environment thus could offer more flexible and effective instruction-learning methods.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.104-111
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• 2019

In this study, we examined the effects of University adaptation on career adaptation through self-leadership and learning commitment, and identified the regulatory effects of demographic characteristics (sex, grade, grade level, and willingness to work). To this end, we analyzed the data for 289 college students. The results of the study are as follows. First, adaptation to University life has a significant impact on learning commitment and self-leadership. However, adaptation to University life has an indirect effect on learning commitment and self-leadership rather than directly affecting career adaptation. Second, demographic characteristics have a regulatory effect on the path through which University adaptation affects career adaptation through self-leadership and learning commitment. The factors that were regulated were age, grade, and willingness to work. Therefore, in order to adapt to university life and adapt to career, we developed a program to improve self-leadership and learning commitment, and suggested that customized guidance is needed considering the differences in personal characteristics such as gender and academic background in university life and career counseling.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.467-473
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• 2014

Adaptive learning system means a system that provides adaptively learning materials according to the learning needs of learners. It consists of expert model, instructional model and student model. Expert model is that stores information which is to be taught. Student model stores the data of learning history and learning information of students. Instructional model provides necessary learning materials for actual leaners. This paper has constructed student model through learner's profile information and instructional model through dynamic scenario construction. After that, We have developed adaptively to provide learning to learners by constructing suitable dynamic scenario based on learners profile information. In the end, satisfaction result about this system showed a high degree of satisfaction and 88%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6B
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• pp.629-637
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• 2002

RLS a1gorithm is a kind of the adaptive a1gorithms in smart antennas and adapts the weight vector using the difference between the output signal of array antennas and the known training sequence. In this paper, we propose a new algorithm based on the RLS algorithm. It calculates the error signal with reference signal derived from blind scheme. Simulation results show that the proposed algorithm yields more user capacity by 67∼74% than other blind adaptive algorithms(LS-DRMTA, LS-DRMTCMA) at the same BER and the beamformer forms null beams toward interference signals and the main beam toward desired signal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4174-4181
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• 2010

This paper presents an adaptive scheduling algorithm for manufacturing processes with non-stationary rework probabilities. The adaptive scheduling scheme named by hybrid Q-learning algorithm is proposed in this paper making use of the non-stationary rework probability and coupling with artificial neural networks. The proposed algorithm is measured by mean tardiness and the extensive computational results show that the presented algorithm gives very efficient schedules superior to the existing dispatching algorithms.