• 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.

• Cross-Cultural Studies
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• v.27
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• pp.415-434
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• 2012

The Hanja used in Korean are traditional Chinese characters, but what Chinese people use now is simplified characters. So, there are differences in pronunciation and meaning between the characters used by Korean and Chinese. More than 70% of the Korean language vocabulary derived from or were influenced by hanja. For the inheritance and development of traditional culture,and for the communication among countries of the Chinese characters cultural circle in Northeast Asia, should we build up an authentic Chinese education system. But the government hasn't pay much attention to this work, and the government's policy can't implement the efficient education. Consequently, in these days, there are more and more Korean people who are functionally illiterate in Chinese. Recently, proficiency tests of Chinese characters are expected to promote the development of Chinese education. But, most Koreans' motives for Chinese study are usually to pass the college entrance exam or to compete for jobs. However, after passing the test, the motive for studying gradually fade away. It is the basic problem faced by Korean Chinese character education. Since the 1950s, various character education methods have been studied in China, the research results were appliedin their textbooks and other materials. Therefore, a well-organized and efficient learning-by-step education system was built up. At present, China's literacy education in the textbooks utilizes a range of methods including revisional centralized and distributed. Unfortunately, there is still one shortcoming worthy of concerns: how to solve the problems due to the simplification of traditional Chinese characters? Is it possible to revive traditional Chinese characters? Before adopting the results of research on China's literacy education and applying them to our character education, we should consider our specific situation carefully. Adopting the research results with cautious review and objective criticism should have a positive impact on Korean Chinese character education.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.55-61
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• 2019

In order to realize foreign language education, various existing educational media have been provided, but there are disadvantages in that the cost of the parish and the media program is high and the real-time responsiveness is poor. In this paper, we propose an artificial intelligence English conversation system based on VR and speech recognition. We used Google CardBoard VR and Google Speech API to build the system and developed artificial intelligence algorithms for providing virtual reality environment and talking. In the proposed speech recognition server system, the sentences spoken by the user can be divided into word units and compared with the data words stored in the database to provide the highest probability. Users can communicate with and respond to people in virtual reality. The function provided by the conversation is independent of the contextual conversations and themes, and the conversations with the AI assistant are implemented in real time so that the user system can be checked in real time. It is expected to contribute to the expansion of virtual education contents service related to the Fourth Industrial Revolution through the system combining the virtual reality and the voice recognition function proposed in this paper.

• Education of Primary School Mathematics
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• v.22 no.4
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• pp.223-237
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• 2019

There is a close interaction between the linguistic-syntactic representation system and the affective representation system that appear in the mathematical process. On the other hand, since the mathematical conceptual system is fundamentally metaphoric, the analysis of the mathematical concept structure through linguistic representation can help to identify the source of cognitive and affective obstacles that interfere with mathematics learning. In this study, we analyzed the problem-solving protocols of mathematical gifted children from the perspective of cognitive language and meta-affect to identify the relationship between the functional characteristics of the text and metaphor they use and the functional characteristics of meta-affect. As a result, the behavior of the cognitive and affective characteristics of mathematically gifted children differed according to the success of problem solving. In the case of unsuccessful problem-solving, the use of metaphor as an internal representation system was relatively more frequent than in the successful case. In addition, while the cognitive linguistic aspects of metaphors play an important role in problem-solving, meta-affective attributes are closely related to the external representation of metaphors.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.1-7
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• 2021

In the latest trend of machine translation research, the model is pretrained through a large mono lingual corpus and then finetuned with a parallel corpus. Although many studies tend to increase the amount of data used in the pretraining stage, it is hard to say that the amount of data must be increased to improve machine translation performance. In this study, through an experiment based on the mBART model using parallel corpus filtering, we propose that high quality data can yield better machine translation performance, even utilizing smaller amount of data. We propose that it is important to consider the quality of data rather than the amount of data, and it can be used as a guideline for building a training corpus.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.