• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.389-403
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• 2019

This study has a purpose, that investigating influence of learning characteristic, lifelong learning participation motive, and wisdom that adult has at learning outcome and whether it has mediating effect of wisdom at influence that learning characteristic and lifelong learning participation motive have. For this, the subjects of the study was 425 adult learners from 20 to 69 years old who participated or are participating at Seoul, Incheon, and Gyeonggi-do. The results of this study are as in the following. At first, as a result of investigating relationship between learning characteristic, lifelong learning participation motive, wisdom, and learning outcome, the correlation coefficient of all variables appeared meaningfully. Second, as a result of investigating influence that learning characteristic, lifelong learning participation motive, and wisdom have in learning outcome, the most influential variable was learning value, the rest were cognitive capability, activity direction motive, learning direction motive and positive life attitude in this order. The third, as a result of investigating mediation effect of wisdom at influence that learning characteristic and lifelong learning participation motive have in learning outcome, Wisdom at the influence that learning characteristic have on learning outcome had completely mediated effect, and the wisdom at the influence that lifelong participation motive have on learning outcome had partially mediated effect. Thus, it was shown up that adult's learning characteristic and lifelong learning participation motive are able to increase effectively learning outcome by mediating wisdom. Therefore it is implying that it is essential to consider learning characteristic and lifelong learning participation motive in lifelong education field, and learning circumstance related with wisdom is important, as wisdom is important variable for increasing learning outcome.

• Journal of the Korean School Mathematics Society
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• v.14 no.2
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• pp.199-213
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• 2011

The factors contributing to learning can be broadly classified into four different groups; Learner's characteristic variable, Instructor's characteristic variable, Learning task characteristic variable and environmental characteristic variable. And the first thing we need to do here is understanding of learner's characteristics among those factors in order to devise a plan for education. Accordingly, the purpose of this study is to find out what impact the affective traits (self-concept learning habits learning attitude), one of the learner's features, have on the mathematics-learning achievement and to seek for a good teaching method with reference to elementary school students' learning accomplishments and attitudes. For this, a questionnaire survey was conducted of 78 students of two fifth-grade classes in an elementary school located in South Chungcheong Province in this study. In consequence, it has been shown that the mathematics-learning achievement has the greatest relevance to the self-concept in connection with mathematics followed by the self-concept in connection with learning, the learning habits relating to mathematics, the attitude towards mathematics, the learning habits concerning studies and the attitude towards learning.

• Journal of the Korea Safety Management & Science
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• v.9 no.3
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• pp.153-163
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• 2007

Over the fast few years, web-based e-Learning have made remarkable progress. According to advance of e-Learning, the evaluation of e-Learning effectiveness and success model become more important. This study had a focus on the effect of system characteristic of e-Learning systems and self-efficacy on learning performance. Data has been collected from 192 person experienced in e-Learning. The questionnaire method was adopted to collect the data for this study. The research was conducted by using SPSS 12.0 and AMOS 4.0. The research results and suggestions of the study are as follow. First of all, system quality and information quality of e-Learning system had positive relationship with perceived usefulness. Second, information quality was related positively to user satisfaction. Third, perceived usefulness was positively connected with user satisfaction. Fourth, user satisfaction and self-efficacy had relation to learning performance.

• The Mathematical Education
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• v.53 no.2
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• pp.219-237
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• 2014

In this study we desire to deduce implications for mathematics curriculum, teaching- learning, and evaluation from the data of Nation Assessment of Educational Achievement. For this, first we extracted the items written by the same achievement standard over two years from 2010 to 2012. Next we investigated whether the items are the representative items of a certain proficiency level and classified into the case of the items of the same proficiency level and the case of the items of different proficiency levels. Based on these we analysed learning characteristic of the each proficiency level. From the results of the above, we proposed what should be changed in mathematics curriculum, what should be considered in teaching-learning, and what should be paid attention to test item development.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1042-1045
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• 2003

In this paper, we propose the speaker identification system that uses vowel that has speaker's characteristic. System is divided to speech feature extraction part and speaker identification part. Speech feature extraction part extracts speaker's feature. Voiced speech has the characteristic that divides speakers. For vowel extraction, formants are used in voiced speech through frequency analysis. Vowel-a that different formants is extracted in text. Pitch, formant, intensity, log area ratio, LP coefficients, cepstral coefficients are used by method to draw characteristic. The cpestral coefficients that show the best performance in speaker identification among several methods are used. Speaker identification part distinguishes speaker using Neural Network. 12 order cepstral coefficients are used learning input data. Neural Network's structure is MLP and learning algorithm is BP (Backpropagation). Hidden nodes and output nodes are incremented. The nodes in the incremental learning neural network are interconnected via weighted links and each node in a layer is generally connected to each node in the succeeding layer leaving the output node to provide output for the network. Though the vowel extract and incremental learning, the proposed system uses low learning data and reduces learning time and improves identification rate.

• Journal of The Korean Association of Information Education
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• v.8 no.3
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• pp.307-317
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• 2004

In web-based education environment, it is necessary to provide individually adjusting feedback according to learner's characteristic. Despite this necessity, it is a current state that there are difficulties in deriving the variables of learners' characteristics and lack in developing the systematic strategies and practical tools for providing individually adjusting feedback. This study analyzed the learners' learning patterns, one of learner's characteristic variables regarded as important in web-based teaching and learning environment by employing Apriori algorithm, and also grouped the learners by learning pattern. Under this framework, the e-SRM feedback system was designed and developed to provide learning content, learning channel, and learning situation, etc. for individual learners. The proposed system in this study is expected to provide an optimal learning environment complying with learner's characteristic.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.175-182
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• 1994

In this study, we present unvoiced consonant recognition system using characteristic parameters of the phoneme of the each syllable. For the recognition, the characteristic parameters on the time domain such as ZCR, total energy of the consonant region and half region energy of the consonant region, and those on the frequency domain such as the frequency spectrum of the transition region are used. The objective unvoiced consonants in this study are /ㄱ/,/ㄷ/,/ㅂ/,/ㅈ/,/ㅋ/,/ㅌ/,/ㅍ/ and /ㅊ/. Each characteristic parameter of two regions extracted from these segmented unvoiced consonants are used for each recognition system of the region, independently, And complementing two outputs of each other system, the final output is to be produced. The recognition system is implemented using MLP which has learning ability. The recognition simulation results for 112 unvoiced consonant samples are that average recognition rates are 96.4$\%$ under 80$\%$ learning rates and 93.7$\%$ under 60$\%$ learning rates.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.199-209
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• 2022

Typical anomaly detection algorithms are trained by using prior data. Thus the batch learning based algorithms cause inevitable performance degradation when characteristics of newly incoming normal data change over time. We propose an online anomaly detection algorithm which can consider the gradual characteristic changes of incoming normal data. The proposed algorithm based on one-class classification model includes both offline and online learning procedures. In offline learning procedure, the algorithm learns the prior data to be close to centroid of the latent space and then updates the centroid of the latent space incrementally by new incoming data. In the online learning, the algorithm continues learning by using the updated centroid. Through experiments using public underwater acoustic data, the proposed online anomaly detection algorithm takes only approximately 2 % additional learning time for the incremental centroid update and learning. Nevertheless, the proposed algorithm shows 19.10 % improvement in Area Under the receiver operating characteristic Curve (AUC) performance compared to the offline learning model when new incoming normal data comes.

• East Asian mathematical journal
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• v.34 no.4
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• pp.451-462
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• 2018

This study analyzed the learning components of the web-based adaptive math learning programs in order to develop adaptive math learning program using artificial intelligence. The components of the web-based adaptive math learning program set for analysis are classified into learning process presentation, concept learning, problem presentation, problem solving process, and learning result processing then analyzed three programs. As a result of analysis, the typical characteristic of components is that it uses a method of repeatedly presenting the same type of problem in order to learn one concept.

• Journal of The Korean Society of Integrative Medicine
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• v.2 no.2
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• pp.1-12
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• 2014

Purpose : The purpose of this study was to investigate the effect that the academic achievement of the students about the evidence based learning investigates the learning utility value about and the request. Method : The agreement of college students explaining the purpose of research for 12 weeks against 17 students and investigate through a questionnaire. The level of academic achievement according to the sex and claim showed a characteristic with a percentage. An utility investigate the descriptive epidemiologic characteristic about the class of the evidence based learning. Result : The most of college students the level of academic achievement and requests the expected grade of the students about the evidence based learning wanted the 'high' grade of 9 persons, 'middle' grade of 8 persons in the part and the expectation for the class taken so much was high(p<.05). There was the significant different in the utility aspect in the need of the evidence based learning, homework solution, learning synergy effect improvement, and reference search ability improvement(p<.05). Conclusion : These finding revealed that the evidence based learning the satisfaction with class raises the improvement and utility value, and provided the need and the has to develop the educational model which the college students contentment raises an improvement after this opportunity for the new recognition.