• The Journal of Korean Association of Computer Education
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• v.13 no.2
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• pp.25-34
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• 2010

The Internet has brought us a new paradigm called WEB 2.0 which inherently represents the openness, participation, sharing, and cooperation. The WEB 2.0 has rendered people to actively participate in the creation of information and to dynamically interact with others to build mutual knowledge-bases, introducing a whole new web environment. One of the most representative techniques demonstrating the value of the WEB 2.0 is the WIKI which is essentially based on the 'Collective Intelligence' and the 'Wisdom of Crowds'. So far, the WIKI has drawn lots of attention for its potential as an educational tool. In this research, we explored the educational potential of the WIKI by investigating various programs and web-based tools offering WIKI services, and then, analyzing the usage model and characteristics of its users. Based on the analysis, we developed a WIKI-based instructional model and also proposed concrete lesson plans adopting this model. Besides, we introduced preliminary methodologies on the active use of the WIKI in the Edunet and the Cyber Home Learning System as well.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.946-950
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• 2010

Many sentiment categorization systems based on machine learning methods use morphological analyzers in order to extract linguistic features from sentences. However, the morphological analyzers do not generally perform well in a customer review domain because online customer reviews include many spacing errors and spelling errors. These low performances of the underlying systems lead to performance decreases of the sentiment categorization systems. To resolve this problem, we propose a feature extraction method based on simple longest matching of Eojeol (a Korean spacing unit) and phoneme patterns. The two kinds of patterns are automatically constructed from a large amount of POS (part-of-speech) tagged corpus. Eojeol patterns consist of Eojeols including content words such as nouns and verbs. Phoneme patterns consist of leading consonant and vowel pairs of predicate words such as verbs and adjectives because spelling errors seldom occur in leading consonants and vowels. To evaluate the proposed method, we implemented a sentiment categorization system using a SVM (Support Vector Machine) as a machine learner. In the experiment with Korean customer reviews, the sentiment categorization system using the proposed method outperformed that using a morphological analyzer as a feature extractor.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.304-310
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• 2010

Chronic pain and herniated disk is a common disease that 80% of adults are experienced. There diseases rates of caused by the physical shock, such as the traffic accident, and the accidental fall is about 10%. And the most of these diseases is caused by having habitual incorrect position. People know that incorrect position would cause to accumulate continuous stress, but it is not easy to correct position. Because it does not recognize incorrect position repeated habitual consequently. This system collects data of user position after sensors that could measure position attach on use and presumes correct position used by position presumption algorithms. Its system purpose is continuing incorrect position could be aware to user and lead to change to correct position to prevent habituation of incorrect position. If habitual of correct position continues through accurate measurement and repeating cognitive learning, it would help for children and chronic patience.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1325-1334
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• 2014

Recently game addiction of young people has become a social issue. Therefore, many studies, mostly surveys, have been conducted to diagnose game addiction. In this paper, we suggest how to distinguish levels of addiction based on EEG. To this end, we first classify four groups by the degrees of addiction to internet games (High-risk group, Vigilance group, Normal group, Good-user group) using CSG (Comprehensive Scale for Assessing Game Behavior) and then measure their Event Related Potential(ERP) in the Go/NoGo Task. Specifically, we measure the signals of P300, N400 and N200 from the channels of the NoGo stimulus and Go stimulus. In addition, we extract distinct features from the discrete wavelet transform of the EEG signal and use these features to distinguish the degrees of addiction to internet games. The experiments in this study show that High-risk and Vigilance group exhibit lower Go-N200 amplitude of Fz channel than Normal and Good-user groups. In Go-P300 and NoGo-P300 of Fz channel, High-risk and Vigilance groups exhibit higher amplitude than Normal and Good-user group. In Go-N400 and NoGo-N400 of Pz channel, High-risk and Vigilance group exhibit lower amplitude than Normal and Good-user group. The test after the learning study of the extracted characteristics of each frequency band from the EEG signal showed 85% classification accuracy.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.889-899
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• 2007

In proteomics, recent advancements In mass spectrometry technology and in protein extraction and separation technology made high-throughput analysis possible. This leads to thousands to hundreds of thousands of MS/MS spectra per single LC-MS/MS experiment. Such a large amount of data creates significant computational challenges and therefore effective data analysis methods that make efficient use of computational resources and, at the same time, provide more peptide identifications are in great need. Here, SIFTER system is designed to avoid inefficient processing of shotgun proteomic data. SIFTER provides software tools that can improve throughput of mass spectrometry-based peptide identification by filtering out poor-quality tandem mass spectra and estimating a Peptide charge state prior to applying analysis algorithms. SIFTER tools characterize and assess spectral features and thus significantly reduce the computation time and false positive rates by localizing spectra that lead to wrong identification prior to full-blown analysis. SIFTER enables fast and in-depth interpretation of tandem mass spectra.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.285-290
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• 2020

This study focus on improving the text language proficiency regarding users' written text. In order to tone up accuracy improvement in writing, Computer Assisted Language Learning(CALL) can be primarily used as one of the most efficient tools. This study proposes a English Grammar Checking Application that can improve the accuracy over the current applications. The proposed system is capable of defining the difference between a Noun and a Noun Phrase which is critical in improving grammar accuracy for those who use Englilsh as a foreign language in English writing.

• Journal of the Korean Geographical Society
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• v.47 no.6
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• pp.955-974
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• 2012

This study investigated six teachers who used the lessons utilizing geospatial technologies including GPS and Google Earth. The lessons were designed to ask students to solve problems with the technologies rather than to teach students to just use technology and teachers to function more as a facilitator. Key findings include: (1) The teachers with background and interest in learner-centered teaching were more effective in implementing the lessons with their students while the teachers who were familiar with teacher-centered instruction often reduced learners' roles in the lesson; (2) Generally, students expressed huge interests in the lessons. Changes in attitude and participation toward lessons were more clearly observed from low achievers and passive learners; (3) Key influencing factors in adoption of lessons utilizing geospatial technologies were school culture toward innovativeness, characteristics of school administrators, learning experience of the lessons during the workshops, and support systems for lesson preparation and implementation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.53-54
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• 2006

The main purpose of tunnel ventilation system is to maintain CO pollutant and VI (visibility index) under an adequate level to provide drivers with safe driving condition. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve the objectives, the control algorithm used in this research is reinforcement teaming (RL) method. RL is a goal-directed teaming of a mapping from situations to actions. The goal of RL is to maximize a reward which is an evaluative feedback from the environment. Constructing the reward of the tunnel ventilation system, two objectives listed above are included. RL algorithm based on actor-critic architecture and natural gradient method is adopted to the system. Also, the recursive least-squares (RLS) is employed to the learning process to improve the efficiency of the use of data. The simulation results performed with real data collected from existing tunnel are provided in this paper. It is confirmed that with the suggested controller, the pollutant level inside the tunnel was well maintained under allowable limit and the performance of energy consumption was improved compared to conventional control scheme.

• Journal of Educational Research in Mathematics
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• v.18 no.1
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• pp.63-80
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• 2008

In this paper, we suggested generally some samples and cases of portfolio but centered on elementary mathematics in New Zealand elementary school in the aspects of the assessment for learning activity of learner and so we have found some suggestive points by comparing New Zealand portfolio with ours. Finally, we have an objects that the teachers here in Korea can use these results as a cases which are benchmarked by them. We had known through this paper that portfolio assessment in New Zealand elementary school deals with various aspects and it was accessing in the direction of creating knowledge positively through the real life, not textbookish or artificial problem and also it had a characteristics dealing with real life situation or context without filtering. Especially, it always dealt with all regions of curriculum and looked like focusing on the connections of curriculum relatively.

• School Mathematics
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• v.12 no.4
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• pp.605-617
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• 2010

This study explores the characteristics and roles of non-textual elements in secondary mathematics textbooks in the United States and South Korea, using a conceptual framework that I have developed: variety, contextuality, and connectivity. Analyzing five U.S. standards-based textbooks and 13 Korean textbooks, this study shows that although non-textual elements in mathematics textbooks are free of literal language, they exhibit different emphases and reflect assumptions about what is important in learning mathematics and how it can be taught and learned in a particular societal context (Mishra, 1999; Zazkis & Gadowsky, 2001). While there are similar patterns in the use of different types of non-textual elements in textbooks from both countries, different opportunities are provided for students to learn mathematics between the two countries.