• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.968-976
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• 2014

Authentication methods on smartphone are demanded to be implicit to users with minimum users' interaction. Existing authentication methods (e.g. PINs, passwords, visual patterns, etc.) are not effectively considering remembrance and privacy issues. Behavioral biometrics such as keystroke dynamics and gait biometrics can be acquired easily and implicitly by using integrated sensors on smartphone. We propose a biometric model involving keystroke dynamics for implicit authentication on smartphone. We first design a feature extraction method for keystroke dynamics. And then, we build a fusion model of keystroke dynamics and gait to improve the authentication performance of single behavioral biometric on smartphone. We operate the fusion at both feature extraction level and matching score level. Experiment using linear Support Vector Machines (SVM) classifier reveals that the best results are achieved with score fusion: a recognition rate approximately 97.86% under identification mode and an error rate approximately 1.11% under authentication mode.

• Proceedings of the ESK Conference
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• 1998.04a
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• pp.173-178
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• 1998

본 연구에서는 국내에서 보급되고있는 전용 PC 통신 소프트웨어 사용자 인터페이스의 사 용편이성을 향상시키기 위한 설계요인을 분석하고자 한다. 사용편이성을 평가하는 척도로서 정차적 복잡도를 이용하였다. 절차적 복잡도를 기술하기 위해 KLM을 이용하였으며, 국내4 대 전용 PC통신 소프트웨어 각각에 대해 분석하였다. 분석결과 국내에 보급되고 있는 전용 PC 통신 소프트웨어는 사용편이성 측면에서 차이가 발견되었다. 이 차이는 PC 통신 소프트웨어 사용자 인터페이스의 설계요인 및 PC통신 서비스를 위한 데이터베이스 설계요인의 차이에서 비롯 되는 것으로 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4700-4705
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• 2013

The purpose of this study is to investigate the usability and user interface in different types of smart phones. KLM(key-stroke-level model) model estimation and observation values were calculated to perform 12 functional factors in 3 different groups. In results, it was found that the usability of smart phones are similar in basic and general functions. On the contrary, the usability of smart phones are different in more complex functions. Current results can be used to anticipate the future effort to improve user interface design in smart phone.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2081-2085
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• 2013

The purpose of this study is to investigate the usability and user interface in different types of mobile phones. KLM(key-stroke-level model) model estimation and observation values were calculated to perform 11 functional factors in 4 ordinary mobile phones and 4 smart phones. In results, it was found that the usability of ordinary phone is superior to smart phone in basic and simple function likes phone call. On the contrary, the usability of smart phone is superior to memorizing and picturing function. Current results can be used to anticipate the future effort to improve user interface design especially in smart phone.

• Journal of the Ergonomics Society of Korea
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• v.35 no.4
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• pp.277-291
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• 2016

Objective: The aim of this study is to propose a unit touch gesture model, which would be useful to predict the performance time on mobile devices. Background: When estimating usability based on Model-based Evaluation (MBE) in interfaces, the GOMS model measured 'operators' to predict the execution time in the desktop environment. Therefore, this study used the concept of operator in GOMS for touch gestures. Since the touch gestures are comprised of possible unit touch gestures, these unit touch gestures can predict to performance time with unit touch gestures on mobile devices. Method: In order to extract unit touch gestures, manual movements of subjects were recorded in the 120 fps with pixel coordinates. Touch gestures are classified with 'out of range', 'registration', 'continuation' and 'termination' of gesture. Results: As a results, six unit touch gestures were extracted, which are hold down (H), Release (R), Slip (S), Curved-stroke (Cs), Path-stroke (Ps) and Out of range (Or). The movement time predicted by the unit touch gesture model is not significantly different from the participants' execution time. The measured six unit touch gestures can predict movement time of undefined touch gestures like user-defined gestures. Conclusion: In conclusion, touch gestures could be subdivided into six unit touch gestures. Six unit touch gestures can explain almost all the current touch gestures including user-defined gestures. So, this model provided in this study has a high predictive power. The model presented in the study could be utilized to predict the performance time of touch gestures. Application: The unit touch gestures could be simply added up to predict the performance time without measuring the performance time of a new gesture.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.743-748
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• 2007

Recently, various types of camera mouse are developed using the image processing. The camera mouse showed limited performance compared to the traditional optical mouse in terms of the response time and the usability. These problems are caused by the mismatch between the size of the monitor and that of the active pixel area of the CMOS Image Sensor. To overcome these limitations, we designed a new input device that uses the face recognition as well as the speech recognition simultaneously. In the proposed system, the area of the monitor is partitioned into 'n' zones. The face recognition is performed using the web-camera, so that the mouse pointer follows the movement of the face of the user in a particular zone. The user can switch the zone by speaking the name of the zone. The multimodal mouse is analyzed using the Keystroke Level Model and the initial experiments was performed to evaluate the feasibility and the performance of the proposed system.