• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.2
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• pp.75-81
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• 2018

In this paper for developing and implementing the car driver's front lane attention enhancement developed system using the car camera. The developed system automatically alarm the car driver when front cars make the dangerous situation. We use Raspberry Pi camera module V2 as car camera module, Raspberry Pi 3 board as hardware main board of implementing embedded system and develop the application library module which can be operated on the Raspberry situation. The application library module widely consist of two part, front car recognition part and dangerous situation distinguish part. Our developed system satisfy the performance test of the target system at the software test certification laboratory of TTA(Telecommunication Technology Association). We test four items as attentive car recognition ability at day and night, system performance, response time. We get the performance of developed system based on the four goal. The car driver's front lane attention enhancement system in this paper will be widely used at the ADAS(Advanced Driving Assistance System) because of the better performance and function.

• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.84-92
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• 2016

Since the mankind started its space mission, the number of artificial space objects has been increasing exponentially. It contains not just the space machines which are in use but the machines which are out of order. Meantime, those dead machines are being a serious danger, a real threat to human's lives and property because of it could re-enter into the earth's atmosphere and fall to the ground causing mega-disaster. As the number of space activities gets growing so far, the re-entry of the space objects will be a lot more happened in the future. Therefore, not just natural space object like asteroids but the artificial space object like artificial satellite and space station can cause the disaster by falling to the ground. To protect our nation and our property, the government has set up the space disaster management center in Korea astronomy and Space science Institute. In this study, we surveyed public's recognition of the space object's re-entry situation and analyzed it to contribute building national space disaster management policy.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.408-418
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• 2015

This paper describes the design and implementation of situation recognition system with smart phone sensors, which recognizes the dangerous situation at anytime, anywhere through intuitive data analysis of the combination of the sensor. The implemented system consists of wearable heart rate sensor and acceleration sensor of smart phone instead of existing sensor that is attached to the body. It is also designed to get more effective results of recognition about the dangerous situation using merged displacement values of acceleration sensor and heart rate sensor which are measured in the process of recognizing dangerous situations. This research, in accordance with the wide penetration of smartphones, achieves the fast status determination through the combination of an acceleration sensor and a heart rate sensor applied to its own status perception algorithm for anyone who needs the stable perception of risk without the need for a separate provision of the sensor.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.44-50
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• 2017

To understand whether Falling, which is one of the causes of injuries, occurs, various behavior recognition research is proceeding. However, in most research recognize only the fact that Falling has occurred and provide the service. As well as the occurrence of the Falling, the risk varies greatly based on the type of Falling and the situation before and after the Falling. Therefore, when Falling occurs, it is necessary to infer the user's current situation and provide appropriate services. In this paper, we propose to base on Fog Computing and Cloud Computing to design Context-aware System using analysis of behavior data and process sensor data in real-time. This system solved the problem of increase latency and server overload due to large capacity sensor data.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.5 s.98
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• pp.558-563
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• 2005

This research aims to derive the general emotion and preference of the 25 sounds by using the questionnaire method to provide the contents for the soundscape design fit to the characteristics of the given situation. The results can be summarized as follows : Nature sounds except dog barking and locust crying showed highest preference, and the traffic sounds, baby crying and footstep of upper floor showed the lowest. Hereby, the sound recognition can be different each other according to quality of tone and situation even they are the same sounds. The most impressive, wanted to be conserved and retrospective sound was the nature sound, and the most wanted to be removed sound was the machinery sound. And the social sound was shown as the most korean and fit to the art theme street.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.806-809
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• 2004

This research aims to derive the general emotion and preference of the 25 sounds by using the questionnaire method to provide the contents for the soundscape design fit to the characteristics of the given situation. The results can be summarized as follows; Nature sounds except dog barking and locust crying showed highest preference, and the traffic sounds, baby crying and footstep of upper floor showed the lowest. Hereby, the sound recognition can be different each other according to quality of tone and situation even they are the same sounds. The most impressive, wanted to be conserved and retrospective sound was the nature sound, and the most wanted to be removed sound was the machinery sound. And the social sound was shown as the most korean and fit to the art theme street.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.881-889
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• 2016

Ocular region recently emerged as a new biometric trait for overcoming the limitations of iris recognition performance at the situation that cannot expect high user cooperation, because the acquisition of an ocular image does not require high user cooperation and close capture unlike an iris image. This study proposes a new method for ocular image recognition based on BRISK (binary robust invariant scalable keypoints). It uses the distance ratio of the two nearest neighbors to improve the accuracy of the detection of corresponding keypoint pairs, and it also uses geometric constraint for eliminating incorrect keypoint pairs. Experiments for evaluating the validity the proposed method were performed on MMU public database. The person recognition rate on left and right ocular image datasets showed 91.1% and 90.6% respectively. The performance represents about 5% higher accuracy than the SIFT-based method which has been widely used in a biometric field.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.67-72
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• 2015

Recently, studies that interact with human and things through motion recognition are increasing due to the expansion of IoT(Internet of Things). This paper proposed the system that recognizes the user's logical activity in home environment by attaching some sensors to various objects. We employ Arduino sensors and appreciate the logical activity by using the physical activitymodel that we processed in the previous researches. In this System, we can cognize the activities such as watching TV, listening music, talking, eating, cooking, sleeping and using computer. After we produce experimental data through setting virtual scenario, then the average result of recognition rate was 95% but depending on experiment sensor situation and physical activity errors the consequence could be changed. To provide the recognized results to user, we visualized diverse graphs.

• The Korean Journal of Emergency Medical Services
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• v.25 no.2
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• pp.55-69
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• 2021

Purpose: This study aimed to develop 360° virtual reality videos and common videos for cardiac arrest recognition. Methods: A sequential mixed methods study was conducted, using qualitative interviews (with a total of seven experts) and a quantitative survey. Results: First, the cardiac arrest situation should be developed within 2-3 minutes after witnessing the patient collapse, for each of the four cardiac arrest videos about apnea, gasping, seizure, gasping, and seizure. Second, the education program should be designed so that the education on cardiac arrest recognition can proceed before CPR practice begins. Conclusion: 360° virtual reality videos and common videos for cardiac arrest recognition can play an important role in the education of the general public about cardiac arrest experience.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.94-98
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• 2009

In this paper, we deal with a face recognition method for the emotional face images. Since the face recognition is one of the most natural and straightforward biometric methods, there have been various research works. However, most of them are focused on the expressionless face images and have had a very difficult problem if we consider the facial expression. In real situations, however, it is required to consider the emotional face images. Here, three basic human emotions such as happiness, sadness, and anger are investigated for the face recognition. And, this situation requires a robust face recognition algorithm then we use a fuzzy Fisher's Linear Discriminant (FLD) algorithm with the wavelet transform. The fuzzy Fisherface is a statistical method that maximizes the ratio of between-scatter matrix and within-scatter matrix and also handles the fuzzy class information. The experimental results obtained for the CBNU face databases reveal that the approach presented in this paper yields better recognition performance in comparison with the results obtained by other recognition methods.