• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.291-298
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• 2012

Objective: The aim of this study is to predict Korean text entry on touchscreens using ACT-R cognitive architecture. Background: Touchscreen application in devices such as satellite navigation devices, PDAs, mobile phones, etc. has been increasing, and the market size is expanding. Accordingly, there is an increasing interest to develop and evaluate the interface to enhance the user experience and increase satisfaction in the touchscreen environment. Method: In this study, Korean text entry performance in the touchscreen environment was analyzed using ACT-R. The ACT-R model considering the characteristics of the Korean language which is composed of vowels and consonants was established. Further, this study analyzed if the prediction of Korean text entry is possible through the ACT-R cognitive model. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed model can predict the accurate physical movement time as well as cognitive processing time. Application: This study is useful in conducting model-based evaluation on the text entry interface of the touchscreen and enabled quantitative and effective evaluation on the diverse types of Korean text input interfaces through the cognitive models.

• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.77-84
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• 2013

There are lots of tries to make a combination between the technology development which is fast arisen and cultural phenomenon which imply in it. We called this research area as the cultural computing or cultural modeling. In this paper, we examine the cultural user interface design, especially cultural design structure based on the contents considering the research trend of the cultural modeling. To design of the contents based on the culture, there is a need to draw a structure of the cultural feature for the contents. To do this, we combine Hofstede's cultural dimensions model with the data of contents and then we suggest cultural index of content(CiCo). Furthermore, we draw national index of cultural content(NiCC), through conjoining CiCo with preference pattern of content consumption for the nations. Suggested CiCo and NiCC are based on Hofstede's model, however they are improved approximately 10% of the explanatory of model than the Hofstede's.