• Journal of Korean society of Dental Hygiene
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• v.10 no.1
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• pp.33-49
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• 2010

Obiectives : The purpose of this study was to develop PBL packages geared toward improving the problem-solving abilities, self-directed learning capabilities and communicative competency of dental hygienists, which were all required for dental hygienists to have in the dental field. Methods : After three PBL packages for a semester of oral health education were developed, the PBL packages were evaluated by an expert to determine what improvements should be made. Results : The findings of the study were as follows. The three PBL packages were based on real clinical situations and designed to have a different degree of difficulty and provide problems in the form of scenario for learners to solve in a self-directed manner. When the packages were assessed by an expert, the packages were expected to make a contribution to the improvement of the three different abilities on which this study focused, and the packages were found to be appropriate in general in terms of learning content and field applicability, though they needed some modifications. Thus, this study attempted to develop PBL packages and let an expert assess the packages in order to give some suggestions about the development of PBL packages. The packages developed in this study are expected to help boost the problem-solving abilities, self-directed learning capabilities and communicative competency of dental hygienists, which should all be possessed by dental hygienists in the dental field. Moreover, the packages were found to be conducive to the introduction of PBL in the field of dental hygiene. Conclusions : To ensure the successful application of the packages, dental hygiene students should be provided with the packages in situations similar to real clinical situations, and they should have an opportunity to practice dental hygiene duties.

• The Journal of Sustainable Design and Educational Environment Research
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• v.8 no.1
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• pp.23-33
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• 2009

The purpose of this study was to examine the basic academic achievement of technical high school students, their learning capability about major, their adaptability to school instruction and whether those factors of them was linked to their career in an effort to suggest workable reform measures. Technical high school seniors to grasp their basic learning capabilities and their opinions on the curricula. The findings of the study were as follows: First, the civil engineering students at technical high school weren't fully able to understand what they learned because of their poor basic achievement. They should take all the required courses to fix their academic deficiencies in the first year of high school, and client-centered additional education should be provided about particular subjects, such as mathematics, which they should learn to study their major. Second, many of the students chose technical high school through the advice of parents or since they weren't able to go onto academic high school. So they entered technical high school without knowing well about their major, and vocational education wasn't properly publicized. As students make a critical career decision in middle school, the government should build permanent pavilions for vocational-education exhibition where interested students can acquire information and explore their career without any restraints. Current fragrant vocational education that is based on experiential learning should be avoided. Third, the government substituted regular classroom teaching for field practice, and that resulted in providing just uniform instruction, destroying learning atmosphere and eventually holding teachers back from offering quality education. To remedy the situation, two different sorts of classes should be prepared. One type of classes are for college- bound students, and the others are for job-seeking students. College- bound students should receive education about humanities to improve their academic deficiencies, and job-seeking seniors should be allowed to take field-practice courses at authorized companies in the second semester. It's advisable personally and socially to help ensure their successful and immediate social adjustment.

• Journal of Engineering Education Research
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• v.9 no.4
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• pp.10-18
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• 2006

Today it is critical for all engineers to have the capability of interacting in teams with members of different background and to meet the challenges that they will encounters in their careers. To satisfy such needs multidisciplinary engineering-design courses are attracting more attentions than ever in the engineering education community. In this paper we analyze the learning effectiveness of interdisciplinary design teams in an engineering design course in Dongguk University. The comparison analysis between monodisciplinary teams and interdisciplinary ones demonstrates higher learning effectiveness of interdisciplinary teams. In addition, the student evaluation of learning effectiveness points out that communication skill is one of the most important factors for a successful project. Such results show that multidisciplinary design courses must gain wider acceptance in engineering education and engineering students must have more chances to experience multidisciplinary teamwork.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.201-208
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• 2006

This study is to make in-depth and supplementary web-based courseware concerning each student's developed intelligence. The seventh elementary school social studies in-depth and supplementary curriculum is student-centered curriculum that concerns a student's learning ability, aptitude, concern, interesting. career and so on. But, present social science courseware does study without regard to learners's interest and aptitude So in this study, We have a target to build and develope web-based devise that helps student's in-depth and supplementary learning after evaluating multiple intelligence. That should be based on student's favorite intelligence in multiple intelligence theory. Considering Intrapersonal intelligence, Interpersonal intelligence, Musical intelligence, Bodily-kinesthetic intelligence, Logical-mathematical intelligence, Linguistic intelligence, Spatial intelligence, We expect student's effective in-depth and supplementary learning based on each student's interest and capability.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.63-72
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• 2018

This paper examined the learning transfer of job training participants and its influencing factors. A survey of 279 care workers in the city of Seoul and Kyeong Gi province who recently participated dementia job training was conducted. The results of multiple regression analysis indicated that the self-efficacy of the care workers, the capability of instructor, the training methods and the transfer opportunity positively influenced the level of learning transfer. The findings suggested increasing care workers' self-efficacy, enhancing practical skill-based training program, hiring instructors with high workplace experiences, fostering work environment with higher transfer opportunity are required.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.269-276
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• 2015

Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.9
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• pp.267-280
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• 2020

Mirror is a physical reflective surface, typically of glass coated with a metal amalgam, and it is to reflect an image clearly. They are available everywhere anytime and become an essential tool for us to observe our faces and appearances. With the advent of modern software technology, we are motivated to enhance the reflection capability of mirrors with the convenience and intelligence of realtime processing, microservices, and machine learning. In this paper, we present a development of Digital Mirror System that provides the realtime reflection functionality as mirror while providing additional convenience and intelligence including personal information retrieval, public information retrieval, appearance age detection, and emotion detection. Moreover, it provides a multi-model user interface of touch-based, voice-based, and gesture-based. We present our design and discuss how it can be implemented with current technology to deliver the realtime mirror reflection while providing useful information and machine learning intelligence.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.751-770
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• 2018

Web applications are indispensable in the software industry and continuously evolve either meeting a newer criteria and/or including new functionalities. However, despite assuring quality via testing, what hinders a straightforward development is the presence of defects. Several factors contribute to defects and are often minimized at high expense in terms of man-hours. Thus, detection of fault proneness in early phases of software development is important. Therefore, a fault prediction model for identifying fault-prone classes in a web application is highly desired. In this work, we compare 14 machine learning techniques to analyse the relationship between object oriented metrics and fault prediction in web applications. The study is carried out using various releases of Apache Click and Apache Rave datasets. En-route to the predictive analysis, the input basis set for each release is first optimized using filter based correlation feature selection (CFS) method. It is found that the LCOM3, WMC, NPM and DAM metrics are the most significant predictors. The statistical analysis of these metrics also finds good conformity with the CFS evaluation and affirms the role of these metrics in the defect prediction of web applications. The overall predictive ability of different fault prediction models is first ranked using Friedman technique and then statistically compared using Nemenyi post-hoc analysis. The results not only upholds the predictive capability of machine learning models for faulty classes using web applications, but also finds that ensemble algorithms are most appropriate for defect prediction in Apache datasets. Further, we also derive a consensus between the metrics selected by the CFS technique and the statistical analysis of the datasets.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.599-606
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• 2021

Water Distribution Networks, one of the social infrastructures buried underground, has the function of transporting and supplying purified water to customers. In recent years, as measurement capability is improved, a number of studies related to leak recognition and detection by applying a deep learning technique based on flow rate data have been conducted. In this study, a cognitive model for leak occurrence was developed using an LSTM-based deep learning algorithm that has not been applied to the waterworks field until now. The model was verified based on the assumed data, and it was found that all cases of leaks of 2% or more can be recognized. In the future, based on the proposed model, it is believed that more precise results can be derived in the prediction of flow data.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.617-627
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• 2022

Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.