• Journal of The Korean Association For Science Education
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• v.40 no.4
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• pp.359-374
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• 2020

This study is a complex type consisting of survey study and self-study. The former investigated elementary teachers' epistemological beliefs on convergence knowledge and teaching. As a representative of the result of survey study I, as a teacher as well as a researcher, was the participant of the self-study, which investigated my epistemological belief on convergence knowledge and teaching and my execution of convergent science teaching based on family resemblance of mathematics, science, and physical education. A set of open-ended written questionnaires was administered to 28 elementary teachers. Participating teachers considered convergent teaching as discipline-using or multi-disciplinary teaching. They also have epistemological beliefs in which they conceived convergence knowledge as aggregation of diverse disciplinary knowledge and students could get it through their own problem solving processes. As a teacher and researcher I have similar epistemological belief as the other teachers. During the self-study, I tried to apply convergence knowledge system based on the family resemblance analysis among math, science, and PE to my teaching. Inter-disciplinary approach to convergence teaching was not easy for me to conduct. Mathematical units, ratio and rate were linked to science concept of velocity so that it was effective to converge two disciplines. Moreover PE offered specific context where the concepts of math and science were connected convergently so that PE facilitated inter-disciplinary convergent teaching. The gaps between my epistemological belief and inter-disciplinary convergence knowledge based on family resemblance and the cases of how to bridge the gap by my experience were discussed.

• Journal of Dental Rehabilitation and Applied Science
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• v.19 no.4
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• pp.297-308
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• 2003

Face-bow is used to transfer models to the articulator in diagnosing the patient or treating problems associated with occlusion. However, there have been few reports on the reliability of the face-bow procedure and the relationship between the experience of the operator and the reliability of the face-bow procedure. The purposes of this study are to examine the reliability of the face-bow procedure and to evaluate whether the face-bow transferring has any training effect. Nine dentists working at M hospital conducted a face-bow transfer in one patient having a normal dentition and interdental relationship. The procedure was done two times a week for four weeks. The maxillary model was mounted to the articulator every time, then the landmarks on the maxillary right first molar, the maxillary left central incisor, and the maxillary left first molar were measured with a special three-dimensional instrument. These data were input into a computer, and evaluated statistically. The results were as follows ; 1. When examined with ANOVA test, the results were p=0.2040 in maxillary right first molar, p=0.0578 in maxillary left incisor, and p=0.1433 in maxillary left first molar. There was no significant(0< $p{\leq}0.05$). 2. Training 1) The correlation coefficient between trial and rejection was -0.578 when analyzed with T-distribution. The more we tried, the less errors we found. 2) When the S.D. of the first three trials was compared to the S.D. of the last three trials in face-bow transfer, the results showed that the former was larger than the latter in thirty-nine times, and the latter was larger than the former in fifteen times. The more we tried face-bow transfer, the less errors we found. 3. When the S.D. of x, y, z coordinates were examined, the S.D. of x coordinates had the largest measurement in five times, the S.D. of y coordinates had the largest measurement in four times, and the S.D. of z coordinates had the largest measurement in nine times. The possibility which the error can occur in z coordinate was the highest.

• The Journal of Bigdata
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• v.4 no.2
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• pp.23-34
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• 2019

Recently, the crime that utilizes the digital platform is continuously increasing. About 140,000 cases occurred in 2015 and about 150,000 cases occurred in 2016. Therefore, it is considered that there is a limit handling those online crimes by old-fashioned investigation techniques. Investigators' manual online search and cognitive investigation methods those are broadly used today are not enough to proactively cope with rapid changing civil crimes. In addition, the characteristics of the content that is posted to unspecified users of social media makes investigations more difficult. This study suggests the site-based collection and the Open API among the content web collection methods considering the characteristics of the online media where the infringement crimes occur. Since illegal content is published and deleted quickly, and new words and alterations are generated quickly and variously, it is difficult to recognize them quickly by dictionary-based morphological analysis registered manually. In order to solve this problem, we propose a tokenizing method in the existing dictionary-based morphological analysis through WPM (Word Piece Model), which is a data preprocessing method for quick recognizing and responding to illegal contents posting online infringement crimes. In the analysis of data, the optimal precision is verified through the Vote-based ensemble method by utilizing a classification learning model based on supervised learning for the investigation of illegal contents. This study utilizes a sorting algorithm model centering on illegal multilevel business cases to proactively recognize crimes invading the public economy, and presents an empirical study to effectively deal with social data collection and content investigation.

• Journal of Environmental Policy
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• v.8 no.2
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• pp.119-144
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• 2009

The integration of environmental and innovation policies is perceived to be essential in order to deal efficiently with environmental and innovation problems. This study analyzed environmental policy integration in Finnish technology policies in view of system transitions and policy integration. Finnish environment-innovation policy integration is assessed empirically by focusing on the policy strategies, implementation, and evaluation processes. Furthermore, this study compared Korea's environment-innovation policy integration with that of the Finnish experience, and drew up policy implications from the comparative study in order to come up with Korean contexts. Moreover, since green growth and eco-innovation are core issues in Korea today, it is important to ensure that system transitions and policy implementations take into account the various forms of policymaking, as well as political, organizational, and procedural activities.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.10
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• pp.1009-1016
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• 2016

In this study, an educational program was developed. The program can perform the claim for examination of medical expense, which is one of NCS Competence Unit Elements for hospital administration. Considering various coding to complex compute and process, VB.Net was employed for this development. For database, ACCESS Database was used because it is easy to learn and use. The learning effects by the developed program are expected to be as follows. First, the composition of medical expense can be understood by analyzing Medical history and then selecting insurance code according to the Standard of Medical Care Code. Second, unit cost per score can be learned according to hospital class. Third, selection of Column (medical materials) and Column II(medical practice) can classify items of additional ratio. Fourth, because patient's payment rate on hospitalization and meal expense and use of special equipment are differently applied, user can know patient's payment rate by type and can calculate it. Fifth, additional amount is the amount calculated by additional ratio of Column II(medical practice), and user can learn additional ratio according by insurance type and hospital class. Sixth, user can learn self-pay rate by hospital class and understand the process that self-pay amount and claim amount are calculated according by self-pay rate.

• Journal of the Korean School Mathematics Society
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• v.14 no.4
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• pp.423-442
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• 2011

The purpose of this study was to examine the effects of tasks setting for mathematical modelling in the complex real situations. The tasks setting(MMa, MeA) in mathematical modelling was so important that we can't ignore its effects to develop meaning and integrate mathematical ideas. The experimental setting were two groups ($N_1=103$, $N_2=103$) at public high school and non-experimental setting was one group($N_3=103$). In mathematical achievement, we found meaningful improvement for MeA group on modelling tasks, but no meaningful effect on information processing tasks. The statistical method used was ACONOVA analysis. Beside their achievement, we were much concerned about their modelling approach that TSG21 had suggested in Category "Educational & cognitive Midelling". Subjects who involved in experimental works showed very interesting approach as Exploration, analysis in some situation ${\Rightarrow}$ Math. questions ${\Rightarrow}$ Setting models ${\Rightarrow}$ Problem solution ${\Rightarrow}$ Extension, generalization, but MeA group spent a lot of time on step: Exploration, analysis and MMa group on step, Setting models. Both groups integrated actively many heuristics that schoenfeld defined. Specially, Drawing and Modified Simple Strategy were the most powerful on approach step 1,2,3. It was very encouraging that those experimental setting was improved positively more than the non-experimental setting on mathematical belief and interest. In our school system, teaching math. modelling could be a answer about what kind of educational action or environment we should provide for them. That is, mathematical learning.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.43-54
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• 2018

Images taken in haze weather are characteristic of low contrast and poor visibility. The process of reconstructing clear-weather image from a hazy image is called dehazing. The main challenge of image dehazing is to estimate the transmission map or depth map for an input hazy image. In this paper, we propose a single image dehazing method by utilizing the Generative Adversarial Network(GAN) for accurate depth map estimation. The proposed GAN model is trained to learn a nonlinear mapping between the input hazy image and corresponding depth map. With the trained model, first the depth map of the input hazy image is estimated and used to compute the transmission map. Then a guided filter is utilized to preserve the important edge information of the hazy image, thus obtaining a refined transmission map. Finally, the haze-free image is recovered via atmospheric scattering model. Although the proposed GAN model is trained on synthetic indoor images, it can be applied to real hazy images. The experimental results demonstrate that the proposed method achieves superior dehazing results against the state-of-the-art algorithms on both the real hazy images and the synthetic hazy images, in terms of quantitative performance and visual performance.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.67-75
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• 2018

According to Symantec's Internet Security Threat Report(2018), Internet security threats such as Cryptojackings, Ransomwares, and Mobile malwares are rapidly increasing and diversifying. It means that detection of malwares requires not only the detection accuracy but also versatility. In the past, malware detection technology focused on qualitative performance due to the problems such as encryption and obfuscation. However, nowadays, considering the diversity of malware, versatility is required in detecting various malwares. Additionally the optimization is required in terms of computing power for detecting malware. In this paper, we present Stream Order(SO)-CNN and Incremental Coordinate(IC)-CNN, which are malware detection schemes using CNN(Convolutional Neural Network) that effectively detect intelligent and diversified malwares. The proposed methods visualize each malware binary file onto a fixed sized image. The visualized malware binaries are learned through GoogLeNet to form a deep learning model. Our model detects and classifies malwares. The proposed method reveals better performance than the conventional method.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.231-247
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• 2010

This research examines a number of theoretical and practical issues when measuring the economic value of library services. In particular, using two recent studies conducted in Korea as illustrations, the study shows how various measurement decisions affect the final outcomes in the economic valuation of library services and thus points to the need for a more reliable study design. Specific areas of measurement discussed include the following: scope of measurement, application of CVM(Contingent Valuation Method), time vs. monetary value measurement, dealing with outliers, allowing alternatives, and the use of estimation. ROI(Return on Investment) scores or benefit cost ratios vary significantly according to different measurement choices even in the same study. There is a need for collecting qualitative data that complements the quantitative data typically collected in economic valuation studies. The outcome of economic valuation of library services should be considered as one of many representations of library values. Practitioners and researchers should exercise caution in interpreting those results but be able to leverage them to better communicate the value of library services.

• Industry Promotion Research
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• v.2 no.1
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• pp.85-91
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• 2017

This study analyzed the effect of NCS - based education and training of small and medium manufacturing on job performance. The results of this study were as follows: First, the effects of NCS education and training on job performance(p<.001, ${\beta}=5.130$) were analyzed. As a result, (p<.01, ${\beta}=3.783$) and on-the-job training had a significant effect on job attitude (p <.05, ${\beta}=-2.448$). (P <.01, ${\beta}=.740$), job skill and collective education (p <.01, ${\beta}=.459$), and job skill (P <.01, ${\beta}=.575$), job attitude and field training (p <.05, ${\beta}=-.320$), collective education and field training (p < .268) were found to be correlated. Third, the analysis of the effect of the age of general characteristics on job attitude showed that the fifties (3.75) had higher attitude than the 20s (3.44), 30s (3.26) and 40s (3.63). The purpose of this study is to investigate the effect of NCS - based education and training on the job performance of small and medium manufacturing industries.