• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.510-518
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• 2022

The diagnostic evaluation conducted at the national level is very important to detect underachievers in school early. This study used an artificial intelligence method to find the characteristics of underachievers that affect learning development for middle school students. In this study an artificial intelligence model was constructed and analyzed to determine whether the Busan Education Longitudinal Data in 2020 by entering data from the first year of middle school in 2019. A predictive model was developed to predict basic middle school Korean, English, and mathematics education with machine learning algorithms, and it was confirmed that the accuracy was 78%, 82%, and 83%, respectively, in the prediction for the next school year. In addition, by drawing an achievement prediction decision tree for each middle school subject we are analyzing the process of prediction. Finally, we examined what characteristics affect achievement prediction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1111-1120
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• 2022

Image Capturing is a matter of viewing images and describing images in language. The problem is an important problem that can be solved by keeping, understanding, and bringing together two areas of image processing and natural language processing. In addition, by automatically recognizing and describing images in text, images can be converted into text and then into speech for visually impaired people to help them understand their surroundings, and important issues such as image search, art therapy, sports commentary, and real-time traffic information commentary. So far, the image captioning research approach focuses solely on recognizing and texturing images. However, various environments in reality must be considered for practical use, as well as being able to provide image descriptions for the intended purpose. In this work, we limit the universally available Korean and English image captioning models and text generation techniques for the purpose of image captioning.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.491-498
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• 2022

In this paper, as a liberal arts course for non-major students, a case study of recurrent neural network SW practice, which is essential for designing a basic recurrent neural network subject curriculum, was developed. The developed SW practice case focused on understanding the operation principle of the recurrent neural network, and used a spreadsheet to check the entire visualized operation process. The developed recurrent neural network practice case consisted of creating supervised text completion training data, implementing the input layer, hidden layer, state layer (context node), and output layer in sequence, and testing the performance of the recurrent neural network on text data. The recurrent neural network practice case developed in this paper automatically completes words with various numbers of characters. Using the proposed recurrent neural network practice case, it is possible to create an artificial intelligence SW practice case that automatically completes by expanding the maximum number of characters constituting Korean or English words in various ways. Therefore, it can be said that the utilization of this case of basic practice of recurrent neural network is high.

• Transactions of the KSME C: Technology and Education
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• v.2 no.1
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• pp.15-20
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• 2014

Intuitive learning method was applied at the beginning of each lecture to induce students to draw their interests. Avoiding simple explanation of equations and problem solving by using them, we repeated theoretical concepts verbally and applied physical meanings when we developed and wrote equations. By these methods we expected to find a way to increase students' learning effects. We also took a group investigation on pursuing term projects. Students choose their own subjects individually and submitted reports according to the time schedule. The reports included the contents that they learned during classes. After choosing best reports for each group by instructor, students at each group divided roles and prepared presentations. Thorough these methods they increased their scores from mid-term to final exams, and got aquatinted with responsibilities among group and organizations. They also experienced physical meanings from the usual daily life phenomena which could be connected to the engineering concepts and improved abilities as junior engineers.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.317-325
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• 2017

In this paper, we try to classify Korean hedge sentences, which are regarded as not important since they express uncertainties or personal assumptions. Through previous researches to English language, we found dependency information of words has been one of important features in hedge classification, but not used in Korean researches. Additionally, we found that word embedding vectors include the word usage information. We assume that the word usage information could somehow represent the dependency information. Therefore, we utilized word embedding and neural networks in hedge sentence classification. We used more than one and half million sentences as word embedding dataset and also manually constructed 12,517-sentence hedge classification dataset obtained from online news. We used SVM and CRF as our baseline systems and the proposed system outperformed SVM by 7.2%p and also CRF by 1.2%p. This indicates that word usage information has positive impacts on Korean hedge classification.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.509-520
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• 2015

College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.1-11
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• 2000

An example-based machine translation approach is a new paradigm for resolving various problems caused by the rules of conventional rule-based machine translation. But, in pure example-based machine translation, it is very hard to find similar examples matched with input sentences by using reasonable parallel corpus. This problem causes large overheads in the process of sentence generation. This paper proposes new method of English-Korean transfer using both patterns and examples. The patterns are composed of sentence patterns and phrase patterns. Meta parts of the patterns make the example-based machine translation more practical by raising the probability to find similar examples. The use of patterns and examples can reduce the ambiguities in source language analysis and give us a high quality of MT. And experimental results with a test corpus are discussed.

• Analytical Science and Technology
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• v.11 no.1
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• pp.1-7
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• 1998

This study focuses on developing a controlling and analyzing software for the portable atomic emission spectrometer equipped with an electrothermal vaporizer(ETV) that can perform the in-situ trace analysis of heavy metal ions dissolved in water. The software works well for a notebook PC and it is exclusively developed for the real time analysis with a line filter and a photomultiplier light detector. The program is designed to operate under Windows 95 environment and either Korean or English can be used as a main language. The Delphi 2.0 language software is mainly used for programing. The program is designed to make a calibration curve and the system users can get the analytical data in a short time. And a final report can be generated without having difficulties. This software can be easily modified for other analytical atomic spectrometers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2125-2130
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• 2016

In this paper, we researched the excellency of 3D graphic nursery contents which is developed by mobile AR technology. AR technology has currently people's attention because of the potential to be core contents of future ICT industry. We applied AR nursery contents for kid's subtitle language selection in Korean, Chinese and English education. The original fairy tale consisted of 6~8 scenes for the 3D contents production, and was adapted and translated. Dubbing was dubbed by the native speaker using the standard pronunciation, and the effect sound was edited separately to fit the scene. After composing a scenario, constructing a 3D model, constructing a interaction, constructing a sound effect, and creating content metadata, the Unity 3D game engine is executed to create a project and describe it as a script. It provides a fun and informative tradition of fairy tales with abundant content that incorporates ICT technology, accepting advanced technology-based education, and having opportunities to perceive software in daily life.

• Journal of Engineering Education Research
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• v.8 no.1
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• pp.84-98
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• 2005

This study is on improving the general engineering education for enhancing the quality of engineers at a local engineering school in which the students are not highly qualified for engineering education. Based on the analysis on the current engineering education by asking questions to professors, students and alumni of Hongik College of Science and Engineering, we have set the basic educational philosophy as educating practical engineers and have decided the goals of basic engineering education as changing to student oriented education, enhancing the field adaptation capability, improving the problem solving ability and introducing engineering design courses. For achieving the foregoing goals, we have changed several basic engineering courses. Mathematics, science courses, computer related courses, English, communication skill related courses are strengthened, but general college education courses are reduced. We also have encouraged students to participate the classes actively and study efficiently, think logically and creatively. For the operational details, we have tried to impose less courses to freshmen and sophomores, to impose the prerequisite courses, to activate summer and winter schools. Finally, we have tried to find the ways to support continuous improvement on the basic engineering education.