• Journal of The Korean Association of Information Education
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• v.19 no.2
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• pp.243-252
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• 2015

The software education to elementary students will be conducted from 2019. One of highlights of software education is a programming experience. It requires a higher level of programming education to students that are interested in programming. This problem can be solved by the club activities. But the materials for programming education for elementary students is not much. Therefore, we developed a programming material for club activities of the elementary school. We did not develop it as a programming manual. The students can understand a problem, can design through decomposition and abstraction processes, and can write a program when they are learning with this material. As a result, we expect that they can enhance their computational thinking abilities. We proved that our material is suitable for elementary students through a demonstration class. Therefore, we expect that our development methodologies for the material for programming education will contribute to develop a material for programming education.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.524-531
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• 2014

In this paper, we have proposed the processing and analyzing the linked open data (LOD), a kind of big-data, using resources of cloud computing. The LOD is web-based open data in order to share and recycle of public data. Specially, we defined the InfograaS (Info-graphic as a service), new business area of SaaS (software as a service), to support visualization technique for BA (business analytics) and Info-graphic. The goal of this study is easily to use it by the non-specialist and beginner without experts of visualization and business analysis. Data visualization is the process to represent visually and understand the data analysis easily. The purpose of data visualization is to deliver information clearly and effectively by chart and figure. The big data of public data are shared and presented in the charts and the graphics understood easily by various processing results using Hadoop, R, machine learning, and data mining of open source and resources of cloud computing.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.2
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• pp.199-206
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• 2015

In this study, a new diagnosis method which can predict the working states of a pipe or its element in realtime is proposed by using an artificial neural network. The displacement data of an inspection element of a piping system are obtained by the use of PIV (particle image velocimetry), and are used for teaching a neural network. The measurement system consists of a camera, a light source and a host computer in which the artificial neural network is installed. In order to validate the constructed monitoring system, performance test was attempted for two kinds of mobile phone of which vibration modes are known. Three values of acceleration (minimum, maximum, mean) were tested for teaching the neural network. It was verified that mean values were appropriate to be used for monitoring data. The constructed diagnosis system could monitor the operation condition of a gas pipe.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.231-237
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• 2017

Threat intelligences collected from cyber incident sharing system and security events collected from Security Information & Event Management system are analyzed and coped with expanding malicious code rapidly with the advent of big data. Analytical classification of the threat intelligence in cyber incidents requires various features of cyber observable. Therefore it is necessary to improve classification accuracy of the similarity by using multi-profile which is classified as the same features of cyber observables. We propose a multi-profile ensemble model performed similarity analysis on cyber incident of threat intelligence based on both attack types and cyber observables that can enhance the accuracy of the classification. We see a potential improvement of the cyber incident analysis system, which enhance the accuracy of the classification. Implementation of our suggested technique in a computer network offers the ability to classify and detect similar cyber incident of those not detected by other mechanisms.

• Journal of the Korean Society of Earth Science Education
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• v.12 no.3
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• pp.252-260
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• 2019

The purpose of this study is to assist school science class by investigating effective Earth's rotation experiments of districts by school level. The researcher investigated or developed nine experiments for learning Earth's rotation, and conducted and discussed these experiments with 26 elementary school teachers. Each teachers chose an effective Earth's rotation experiment for the district and wrote the reason. As a result, elementary school teachers chose the experiment that is easy to prepare and to do. And elementary school students are interested in the experiments by conducting them on their own. Middle and high school teachers chose more difficult experiments that could be connected with other concepts. University teachers chose effective experiments based on application of knowledge, active exploration, computer literacy, and difficulty.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.129-130
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• 2018

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Artificial Intelligence" keyword, one month as of May 19, 2018. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Artificial Intelligence" has been found to be technology (4,122). This study suggests theoretical implications based on the results.

• Journal of Practical Engineering Education
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• v.11 no.2
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• pp.167-174
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• 2019

In the case of Java programming education for non-major undergraduates, there are no examples of applying the physical computing education method. The advantage of physical computing education is that you can directly check the SW processing output result according to the input value of digital and analog sensor, so that you can quickly correct programming errors and improve learner's learning interest and satisfaction. In this paper, we use the microbits to combine physical computing education with basic Java programming education. In addition, according to the computational thinking process, we proposed an educational method for creating Java programs using microbits. Through block programming to control the microbits, we designed an algorithm and applied a training method to convert it into a Java program. In addition, the results of students' evaluations were analyzed in the course applying the education method, and the effectiveness of the education method using the microbit was analyzed.

• Journal of The Korean Association of Information Education
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• v.21 no.6
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• pp.691-699
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• 2017

Along with the increased significance of SW education in the 2015 revision curriculum, SW education using various educational methods and tools is being performed, and teaching and learning contents using SW education tools are continuously being developed. In this paper, we analyzed pre-service teachers' EPL contents preference types, preferred development subjects, and their relationship with pre-service teachers based on the analysis conducted after their EPL class session in which its results were assortatively analyzed by department, letter grade, and type. The result signified a clear difference in development subject and types among the departments, and it also showed a difference in development subject and its recipients among the types. However, there was no difference between development subject and type among the letter grade. This will provide a feedback on EPL classes and help develop EPL-related curricula as well as its application.

• Journal of The Korean Association of Information Education
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• v.20 no.1
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• pp.47-56
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• 2016

In order to nurture creative talent in the 21st century knowledge-based society in elementary education software is carried from the year 2018. The educational content and achievement standards to conduct a software education had been made in the 2015. In this study, the recognition of educational software for elementary school teachers 199 people is investigated. Findings are as follows. Elementary education is the first software required, and is lacking in 17 hours. Second, the idea of a common training software education, teaching and learning methods, evaluation methods, how to develop information materials. Third, lower cognitive development and educational materials for the teaching methods appropriate for understanding, achievement standards for achievement standards. Therefore, should allow teacher training teaching materials development, assessment methods, teaching methods suitable for the achievement standards available to all teachers throughout the school know.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.595-604
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• 2004

By the help of expansion of computer network and rapid growth of Internet, the information infrastructure is now able to provide a wide range of services. Especially open architecture - the inherent nature of Internet - has not only got in the way of offering QoS service, managing networks, but also made the users vulnerable to both the threat of backing and the issue of information leak. Thus, people recognized the importance of both taking active, prompt and real-time action against intrusion threat, and at the same time, analyzing the similar patterns of in-trusion already known. There are now many researches underway on Intrusion Detection System(IDS). The paper carries research on the in-trusion detection system which hired supervised learning algorithm and Fuzzy membership function especially with Neuro-Fuzzy model in order to improve its performance. It modifies tansigmoid transfer function of Neural Networks into fuzzy membership function, so that it can reduce the uncertainty of anomaly intrusion detection. Finally, the fuzzy logic suggested here has been applied to a network-based anomaly intrusion detection system, tested against intrusion data offered by DARPA 2000 Intrusion Data Sets, and proven that it overcomes the shortcomings that Anomaly Intrusion Detection usually has.