• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.311-318
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• 2010

In this paper, we proposed the integrated education program of informatics and math for solving problem using EPL. We applied a integrated math curriculum with EPL and analyzed mathematical thinking and attitude to the 3rd and 5th students. We used mathematical thinking test, mathematical attitude test and interview through student review. We also analyzed data of observers who are elementary school teachers. The results of test are as follows; First, we found effective points of meta-cognition and visualization of thought in solving the mathematical problem using Scratch. Second, mathematical thinking and attitude showed the result that 3rd grade students are more increased than 5th grade students in pre and post t-test of the mathematical. Consequently, we expect that the integrated education program of informatics and math using EPL can be applied to solve problem in math effectively.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.111-120
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• 2020

As an application of big data and artificial intelligence techniques, this study proposes an atypical language-based sentimental opinion poll methodology, unlike conventional opinion poll methodology. An alternative method for the sentimental classification model based on existing statistical analysis was to collect real-time Twitter data related to parliamentary elections and perform empirical analyses on the Polarity and Intensity of public opinion using attribute-based sensitivity analysis. In order to classify the polarity of words used on individual SNS, the polarity of the new Twitter data was estimated using the learned Lasso and Ridge regression models while extracting independent variables that greatly affect the polarity variables. A social network analysis of the relationships of people with friends on SNS suggested a way to identify peer group sensitivity. Based on what voters expressed on social media, political opinion sensitivity analysis was used to predict party approval rating and measure the accuracy of the predictive model polarity analysis, confirming the applicability of the sensitivity analysis methodology in the political field.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.209-218
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• 2017

To propose a contents model for children's smart watch, this study interview 15mothers who have a child using smart watches. Most mothers purchase smart watches for children to warrant their security and manage their schedules, and they use them for sending a call or text to their children, tracking or managing children's location and schedule. Mothers were satisfied with a smart watch's function of communication and safety management, but dissatisfied learning-oriented contents and worrried about bad influenced on children development. Through in-depth interviews, this study propose a persona model for children's smart watch for enhancing parent-child interaction and physical cognitive language socioemotional convergence play contents.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.7-13
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• 2020

With the recent World Health Organization (WHO) Declaration of Pandemic for Coronavirus Disease-19 (COVID-19), COVID-19 is a global concern and many deaths continue. To overcome this, there is an increasing need for sharing information between countries and countermeasures related to COVID-19. However, due to linguistic boundaries, smooth exchange and sharing of information has not been achieved. In this paper, we propose a Neural Machine Translation (NMT) model specialized for the COVID-19 domain. Centering on English, a Transformer based bidirectional model was produced for French, Spanish, German, Italian, Russian, and Chinese. Based on the BLEU score, the experimental results showed significant high performance in all language pairs compared to the commercialization system.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.18-33
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• 2014

A Word is the smallest unit for text analysis, and the premise behind most text-mining algorithms is that the words in given documents can be perfectly recognized. However, the newly coined words, spelling and spacing errors, and domain adaptation problems make it difficult to recognize words correctly. To make matters worse, obtaining a sufficient amount of training data that can be used in any situation is not only unrealistic but also inefficient. Therefore, an automatical word extraction method which does not require a training process is desperately needed. WordRank, the most widely used unsupervised word extraction algorithm for Chinese and Japanese, shows a poor word extraction performance in Korean due to different language structures. In this paper, we first discuss why WordRank has a poor performance in Korean, and propose a customized WordRank algorithm for Korean, named KR-WordRank, by considering its linguistic characteristics and by improving the robustness to noise in text documents. Experiment results show that the performance of KR-WordRank is significantly better than that of the original WordRank in Korean. In addition, it is found that not only can our proposed algorithm extract proper words but also identify candidate keywords for an effective document summarization.

• The KIPS Transactions:PartA
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• v.18A no.5
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• pp.165-176
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• 2011

In this paper, we show how a curriculum using LEGO MINDSTORMS NXT robot based ROBOTC for undergraduate students has been developed, and we analyze the educational effect of the curriculum. The curriculum is composed of basic knowledge learning, practice with basic robots, practice with advanced robots, and creative design and implementation of robots. During the three year period since 2009, educational achievement has been analyzed by surveys for 6 classes, 94 students. According to the analysis, the curriculum has highly motivated the students and made them to achieve effectively our educational and academic goals. Also, we observe that the curriculum helped the students to improve their creativity and the problem solving skill, and that the students were autonomously and deeply involved in the homework and the term projects, which made them be very cooperative. Finally, the intensive practice with ROBOTC programming is shown to help students to improve their programming ability of C language.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.341-346
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• 2013

In this paper, we propose a rule extraction method using a modified Fuzzy Min-Max (FMM) neural network. The suggested method supplements the hyperbox definition with a frequency factor of feature values in the learning data set. We have defined a relevance factor between features and pattern classes. The proposed model can solve the ambiguity problem without using the overlapping test process and the contraction process. The hyperbox membership function based on the fuzzy partitions is defined for each dimension of a pattern class. The weight values are trained by the feature range and the frequency of feature values. The excitatory features and the inhibitory features can be classified by the proposed method and they can be used for the rule generation process. From the experiments of sign language recognition, the proposed method is evaluated empirically.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.146-147
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• 2017

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 "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.511-522
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• 2002

WBI (Web-Based Instruction), a web-based tool for teaching the students at a long distance, makes possible to Interact between learners and instructors, provides a wide variety of learning materials, has an advantage of overcoming spatial constraints. In this paper, as a model of using the web for education, a web-based education-evaluation system has been designed and implemented. Web-based education-evaluation system has to be equipped with both of the online setting question mode and the upload setting question mode, the former makes questions on web and the latter uploads the setted questions on offline with settling a defeat of the existing systems on setting questions. And the system has to be equipped with the function of analyzing the questions that gives teacher several kinds of analysis information and makes possible to feedback to questions by adjusting the difficulty and revising the questions. In this paper, a system that reflects the above requirements has been designed and implemented with PHP script language and MySQL database system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4167-4173
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• 2010

ICT education guidelines revised in 2005 reinforce computer science elements such as algorithm, data structure, and programming covering all schools. It means that goal of computer education is improving problem-solving abilities not using of commercial software. So this paper suggests problem-solving method of maze escape through robots' cooperation in an effort of learning these elements. Problems robots should solve are first-search and role-exchange. First-search problem is that first robot searches maze and send informations about maze to the second robot in real time. Role-exchange problem is that first robot searches maze, but loses its function at any point. At this time second robot takes a role of first robot and performs first robot's missions to the end. To solve these two problems, it goes through four steps; problem analysis, algorithm description, flowchart and programming. Additional effects of our suggestion are chance of cooperation among students and use of queue in data structure. Further researches are use of more generalized mazes, application to real field and a talented curriculum.