• Journal of the Korean Society of Earth Science Education
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• v.12 no.2
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• pp.165-173
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• 2019

This study purposes to figure out the effects of applying discussion-based science class on concept of science achievement and science teaching efficacy. This study established an twelve-week period of experimental treatment from April to June 2019, and the students who participated in this study formed a research group consisting of 27 students in the first semester of the second year of the B University of Education. and taking courses in 'elementary Science Textbook Research 1' For the classes applying discussion-based science class, the analysis was made on 2015 revised curriculum, and 12th process-centered performance assessment based on discussion. The developed data had designed to develop concept of science achievement and science teaching efficacy. The study group applied process-centered performance assessment based on discussion science class, so unaffectedly study group could improve their concept of science achievement and science teaching efficacy. B University of education is singleness class that doesn't have compare group, so this study is constituted only study group. Applying based-discussion science class to study group, before and after concept of science concept test, science teaching efficacy test is performed. The results of the study were as follows. First, the study group applied discussion-based science class had statistically significant differences in concept of science achievement (p<.05). Second, the study group applied discussion-based science class had statistically significant differences in science teaching efficacy(p<.05). Third, after discussion-based science class of pre-service teachers have a very good feeling. Through such study results, the study could figure out that the class applying discussion-based science class has positive effect on concept of science achievement and science teaching efficacy.

• Journal of the Korean Society of Food Culture
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• v.26 no.3
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• pp.249-260
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• 2011

The current research aims to verify whether distance learning can be adopted in practical cooking class for Korean foods in a two-year college. The distance learning education can be a supplementary method to the traditional cooking class. The face-to-face teaching method and the distance learning method were compared in order to determine which of the one is more effective teaching method in the practical cooking class. The results of the present experimental study were analyzed based on the participant's learning expectation and satisfaction, the evaluation of the experimental process, and the academic performance. The results of this study showed that the participants in the face-to-face class evaluated their class experience higher than those in the distance learning class with respect to the participant's learning expectation and satisfaction, and the evaluation of the experimental process. On the contrary, regarding the academic performance, the participants in the distance learning class showed higher scores than those in the face-to-face class. The end result supports the claim that the distance learning method is more effective in the participants for gaining cooking knowledge.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.863-870
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• 2002

The current class scheduling has difficulties in reflecting students' preferences for the classes that they want to take and forecasting the demands of classes. Also, it is usually a repetitive and tedious work to allocate classes to limited time and cesourres Although many research studios in task allocation and meeting scheduling intend to solve similar problems, they have limitations to be directly applied to the class-scheduling problem. In this paper. a class scheduling system using multi agents-based negotiation is suggested. This system consists of student agents, professor agents and negotiation agents each agent arts in accordance with its respective human user's preference and performs the repetitive and tedious process instead of the user The suggested system utilizes negotiation cost concept to derive coalition in the agent's negotiation. The negotiation cost is derived from users' bidding prices on classes, where each biding price represents a user's preference on a selected class. The experiments were performed to verify the negotiation model in the scheduling system. The result of the experiment showed that it could produce a feasible scheduling solution minimizing the negotiation cost and reflecting the users' performance. The performance of the experiments was evaluated by a class success ratio.

• Journal of Engineering Education Research
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• v.20 no.6
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• pp.3-11
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• 2017

The purpose of this study is to investigate the variables that learners should consider for learning persistence when applying blended learning to mathematics class which is a basic curriculum of engineering college. For this purpose, this study compared the basic mathematics class with the blended learning and the class without it. In addition, this study analyzed the influence of the learning outcomes of the blended learning on the willingness to learning persistence by using the self-efficacy and self-regulated learning variables that can predict it. As a result, it was found that the blended learning applied mathematics class of K university which is the subject of analysis in this study has higher self - efficacy, self - regulated learning, and learning persistence intention than general classroom. Finally, the results of this study are meaningful to provide the points to be considered for improving the learning performance when applying the blended learning to the subject class in the future.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.71-86
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• 2022

The water quality index (WQI) has been widely used to evaluate marine water quality. The WQI in Korea is categorized into five classes by marine environmental standards. But, the WQI calculation on huge datasets is a very complex and time-consuming process. In this regard, the current study proposed machine learning (ML) based models to predict WQI class by using water quality datasets. Sihwa Lake, one of specially-managed coastal zone, was selected as a modeling site. In this study, adaptive boosting (AdaBoost) and tree-based pipeline optimization (TPOT) algorithms were used to train models and each model performance was evaluated by metrics (accuracy, precision, F1, and Log loss) on classification. Before training, the feature importance and sensitivity analysis were conducted to find out the best input combination for each algorithm. The results proved that the bottom dissolved oxygen (DO_Bot) was the most important variable affecting model performance. Conversely, surface dissolved inorganic nitrogen (DIN_Sur) and dissolved inorganic phosphorus (DIP_Sur) had weaker effects on the prediction of WQI class. In addition, the performance varied over features including stations, seasons, and WQI classes by comparing spatio-temporal and class sensitivities of each best model. In conclusion, the modeling results showed that the TPOT algorithm has better performance rather than the AdaBoost algorithm without considering feature selection. Moreover, the WQI class for unknown water quality datasets could be surely predicted using the TPOT model trained with satisfactory training datasets.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.13-22
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• 2021

Recently network based attack technologies are rapidly advanced and intelligent, the limitations of existing signature-based intrusion detection systems are becoming clear. The reason is that signature-based detection methods lack generalization capabilities for new attacks such as APT attacks. To solve these problems, research on machine learning-based intrusion detection systems is being actively conducted. However, in the actual network environment, attack samples are collected very little compared to normal samples, resulting in class imbalance problems. When a supervised learning-based anomaly detection model is trained with such data, the result is biased to the normal sample. In this paper, we propose to overcome this imbalance problem through One-Class Anomaly Detection using an auto encoder. The experiment was conducted through the NSL-KDD data set and compares the performance with the supervised learning models for the performance evaluation of the proposed method.

• ETRI Journal
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• v.29 no.5
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• pp.700-702
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• 2007

We present a relevance feedback approach based on multi-class support vector machine (SVM) learning and cluster-merging which can significantly improve the retrieval performance in region-based image retrieval. Semantically relevant images may exhibit various visual characteristics and may be scattered in several classes in the feature space due to the semantic gap between low-level features and high-level semantics in the user's mind. To find the semantic classes through relevance feedback, the proposed method reduces the burden of completely re-clustering the classes at iterations and classifies multiple classes. Experimental results show that the proposed method is more effective and efficient than the two-class SVM and multi-class relevance feedback methods.

• Fourth Industrial Review
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• v.4 no.1
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• pp.11-18
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• 2024

Purpose: The purpose of this study is to develop a geography class teaching and learning guide that enables learners to realistically explore the characteristics of the world's climate and geographical environment using digital tools. Research design, data and methodology: We review previous research on classes using goal-based scenario learning models, gamification, and digital tools, and explore tools that can be applied to world geography classes. Based on the exploration results, a goal-based scenario learning module is designed and a strategy for promoting educational gamification is established based on the ADDIE instructional design model. Results: The study comprises four sessions. Sessions 1-3 involve performance evaluations using a goal-based scenario learning module. Learners create game characters reflecting geographical characteristics, present results, and proceed with 3D modeling. In Session 4, a gamification class using Google Sites on the CoSpaces metaverse platform will be conducted. Conclusions: The study introduces a goal-based scenario learning model and a gamification class using digital tools to empower learners in exploring geographical diversity and its impact on lifestyles. Utilizing an accessible online platform, the study provides practical measures for integrating digital tools into geography education, addressing the current importance of digital technology in teaching.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.258-267
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• 2013

New incremental learning algorithm using extended data expression, based on probabilistic compounding, is presented in this paper. Incremental learning algorithm generates an ensemble of weak classifiers and compounds these classifiers to a strong classifier, using a weighted majority voting, to improve classification performance. We introduce new probabilistic weighted majority voting founded on extended data expression. In this case class distribution of the output is used to compound classifiers. UChoo, a decision tree classifier for extended data expression, is used as a base classifier, as it allows obtaining extended output expression that defines class distribution of the output. Extended data expression and UChoo classifier are powerful techniques in classification and rule refinement problem. In this paper extended data expression is applied to obtain probabilistic results with probabilistic majority voting. To show performance advantages, new algorithm is compared with Learn++, an incremental ensemble-based algorithm.

• ETRI Journal
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• v.33 no.3
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• pp.393-400
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• 2011

A systematic approach for the design of two-stage class AB CMOS unity-gain buffers is proposed. It is based on the inclusion of a class AB operation to class A Miller amplifier topologies in unity-gain negative feedback by a simple technique that does not modify quiescent currents, supply requirements, noise performance, or static power. Three design examples are fabricated in a 0.5 ${\mu}m$ CMOS process. Measurement results show slew rate improvement factors of approximately 100 for the class AB buffers versus their class A counterparts for the same quiescent power consumption (< 200 ${\mu}W$).