• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.494-510
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• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.

• Management & Information Systems Review
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• v.2
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• pp.311-334
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• 1998

By decreasing in CPU price and development of computer assembling technology, personal computer fake a good chance to accelerate its supply. Recently, as being introduced new computing technology so called multi media, teaming assist system which is based on single media such as studying book, cassette tape, video tape, or something else is rapidly being replaced by new assist education system based on multi media in which it is operated by the personal computer. In the computer assist education system, there is an evaluation module which appraise learner's study level into the next study strategy. At the view of this point, this part is very important. In this part, there are some factors like Importance, complexity, or difficulty which commonly include fuzzy factors in our surrounding. But until now, we are still out of the level to handle the evaluation module adequately among the some studies. In this study, we would like to suggest a new module that evaluate learning achievement of ICAI which have a variety of fuzzy environment. We combine Independent fuzzy environment like importance, complexity, difficulty into making total evaluation of learner's achievement. By the result, with expressing by linguistic form, this study can provide the theoretical basis in which we will be able to carry out sentence toward evaluation among elementary school.

• Journal of Korean Elementary Science Education
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• v.22 no.1
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• pp.37-50
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• 2003

The purpose of this study was to develop the quality of the textbook and to find out reasonable selection and structure by examining and analyzing the cognition of teacher and students on the structure and contents of elementary science textbook in the 7th curriculum. The findings of this study were as follows: First, as a result of the students’ cognition, their interest level of the learning contents was high and the degree of the difficulty of the learning contents was low on the whole. Second, as a result of the teachers’ cognition of contents of the textbook, teachers who taught third graders understood that the third graders have relatively much contents to be studied and the level of the contents of the textbook was high. On the other hand, fourth graders’ teachers recognized that contents to be studied and the level of the contents were appropriate. And they understood that there were much work to be studied in the units which were difficult and there were difference between contents to be studied and the degree of the difficulty in some units such as life or the earth fold. Third, as a result of the teachers' cognition of structure of the textbook. teachers were very affirmative to reduce school hours. They understood that current numbers and scale of the unit were appropriate. Teachers were satisfied with the structure of elementary science textbook in the 7th curriculum on the whole.

• The Journal of Korean Academic Society of Nursing Education
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• v.25 no.4
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• pp.436-447
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• 2019

Purpose: The purpose of this study is to identify the educational effect among nursing students who performed the patient role in women's health nursing simulations. Methods: In this exploratory qualitative study, a sample of 31 third- and fourth-grade nursing students who participated in scenario-based patient roles in clinical performance examination of the women's health nursing simulation practice training. Data were collected through focus group interviews. Qualitative data were analyzed using qualitative content analysis. Results: Three themes emerged from the data analysis. Participants experienced an enhancement of patient-centered nursing competence, deep learning immersion and display of self-regulated learning. The difficulty of performing the patient role contributed additional effects such as the difficulty to perform the patient role in the psychological training environment. Conclusion: It is recommended to utilize nursing students as patients in simulation practice training. On the other hand, the psychological training environment can cause difficulties in performing patient roles, a burden on the role of the patient, and involves the interruption of the role.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.801-808
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• 2018

The learning of the linear regression model is stable on the assumption that the sample size is sufficiently larger than the number of explanatory variables and there is no serious multicollinearity between explanatory variables. In this study, we investigated the difficulty of model learning when the assumption was violated by analyzing a real heavy rain damage data and we proposed to use a principal component regression model or a ridge regression model after integrating data to overcome the difficulty. We evaluated the predictive performance of the proposed models by using the test data independent from the training data, and confirmed that the proposed methods showed better predictive performances than the linear regression model.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.241-248
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• 2011

Many learning systems are applying Self-Directed Learning to improve learning efficiency. The degree of understanding of the same learning contents can be different even if the learner's level is same. Therefore, it is difficult to represent an effective learning experience because the learning is progressed by the determined difficulty of learning and the learning process even thought the provided content is difficult to understand. In this paper, we augmented SCORM to reconstruct the learning contents which are suitable for the changed level of each learner in real-time. Also, we designed and implemented this augmented SCORM based DCOS(Differential Contents Organization System). In order to provide the suitable contents for each learner, DCOS reorganizes learning contents based on the learner's level, the learner's achievement of learning objectives, and the correlation between learning objects, that is the component of the learning content. Each 30 Each 30 students studied e-learning contents, which are constructed based on the existing System and DCOS respectively. And the average score and system's satisfaction of the students who studied DCOS based e-learning contents was higher.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.519-528
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• 2005

Computers have been increasingly recognized as tools for teaming, in addition to supporting industrial works. Such advantages e-Learning have as teaming at any time and place, distribution and management of standardized contents, mentoring with learners, immediate feed-backs, and dynamic learning have been applied in a variety of divisions. Despite of the researches and interests, the study on the different views between teachers who design and operate e-learning and students who receive lessons hasn't been enough. So it studied the recognition of middle school teachers and students on the e-Learning. <중략>The research result showed that there were similarity in the views between teachers and students on the concept of e-Learning. Many teachers and students have experienced the e-Learning directly or indirectly. Teachers and students showed similar opinions on the beforehand education and preferred subjects of the e-Learning. But the students required fast and immediate feedback of the teachers. Teachers and students showed similar opinions on the utilization of multimedia components to achieve the goal of education. But teachers thought that immediate feedback was important. The students thought it important to control the degree of difficulty. It suggests a way to activate the e-Learning of middle school efficiently with the research result.

• The Korea Journal of Herbology
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• v.37 no.2
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• pp.13-21
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• 2022

Objectives : The evaluation of academic achievement is pivotal for establishing accurate direction and adequate level of medical education. The purpose of this study was to firstly establish innovative item analysis technique of Item Response Theory (IRT) for analyzing multiple-choice test of herbology in the traditional Korean medicine education which has not been available for the difficulty of test theory and statistical calculation. Methods : The answers of 390 students (2012-2018) to the 14 item herbology test in college of Korean medicine were used for the item analysis. As for the multidimensional analysis of item characteristics, difficulty, discrimination, and guessing parameters along with item-total correlation and percentage of correct answer were calculated using Classical Test Theory (CTT) and IRT. Results : The validity parameters of strong and weak items were illustrated in multiple perspectives. There were 4 items with six acceptable index scores, and 5 items with only one acceptable index score. The item discrimination of IRT was found to have no significant correlation with difficulty and discrimination indices of CTT emphasizing attention of professionals of medical education as for the test credibility. Conclusion : The critical suggestions for the development, utilization and revision of test items in the e-learning and evidence-based Teaching era were made based on the results of item analysis using IRT. The current study would firstly provide foundation for upgrading the quality of Korean medicine education using test theory.

• Journal of Korea Technology Innovation Society
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• v.9 no.1
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• pp.149-174
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• 2006

Although conceptual and empirical researches on the technological learning is increasing rapidly, a few empirical researches of technological learning processes have been undertaken, taking into account a reality of learning processes of a firm. In order to analyze the learning processes of technological knowledges, based on integrative organizational learning theory, this study investigated technological learning processes by analyzing 13 technology development projects of one company with case study research design. Results of the empirical analyses suggested two taxonomy of technological learning processes. First are tour group of technological learning processes derived by the dimension of flow of cognitive and behavioral learning which is explained by the technological competency level of a firm. The other is two group of technological learning processes derived by the dimension of relative difficulty of cognitive and behavioral learning which is explained by the technology characteristics. Finally, the managerial implications for effective management of technological learning and limitations are discussed.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.135-145
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• 2020

Recently, deep-learning based methods for low-light image enhancement accomplish great success through supervised learning. However, they still suffer from the lack of sufficient training data due to difficulty of obtaining a large amount of low-/normal-light image pairs in real environments. In this paper, we propose an unsupervised learning approach for single low-light image enhancement using the bright channel prior (BCP), which gives the constraint that the brightest pixel in a small patch is likely to be close to 1. With this prior, pseudo ground-truth is first generated to establish an unsupervised loss function. The proposed enhancement network is then trained using the proposed unsupervised loss function. To the best of our knowledge, this is the first attempt that performs a low-light image enhancement through unsupervised learning. In addition, we introduce a self-attention map for preserving image details and naturalness in the enhanced result. We validate the proposed method on various public datasets, demonstrating that our method achieves competitive performance over state-of-the-arts.