• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.679-682
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• 2012

본 논문은 지능형 실감 통신 서비스를 위해 단순히 영상 데이터만을 상대방에게 전송하는 것이나 영상 내에 포함된 사용자 상황 정보(위치, 얼굴, 문자 등)들을 인식한 후 자연스럽게 사용자 화면상에 오버레이 시키는 증강현실 기반의 상황인식 기술 개발을 위한 방안을 기술한다. 제안한 방안은 사용자 위치 인식 기술, 사용자 인식 기술, 웨어러블 컴퓨팅 기술, 증강현실 기술, 그리고 화질 개선을 위한 에러 은닉 기술들을 기반으로 한 연구이다. 제안한 방안은 향후 이동 통신 환경에서 사용자에게 보다 편리한 정보 제공 환경으로 공함으로써, 도서관이나 박물관 또는 관광지 등에서 사용자에게 쉽게 새로운 정보를 제공하는 수단으로 자리 잡을 수 있을 것이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.242-248
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• 2017

The purpose of this research is investigate the perception of first aid and differentiate between factors. The research subjects were 188 childcare teachers who work for day care centers in Chungchungnam-do, Republic of Korea and 70 pre-service childcare teachers who major in childcare in colleges in the same area. Collected data were converted to frequency and percentage, and cross correlation analysis was conducted for difference verification. The survey results are as follows. First, regarding the perception of first aid, there was a difference between childcare teachers and pre-service childcare teachers in their ability to cope with an emergency situation and responses to questions regarding frequent emergency situation. Second, the percentage of incorrect answers was high in the questions about impaction, poisoning, and biting. There were significant differences between the answers of childcare teachers and pre-service childcare teachers in questions about bleeding(injury), high fever, and CPR. In all of these questions, the percentage of correct answers of childcare teachers was higher. Regarding this result, clinical training for various emergency situations is needed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1161-1175
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• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• The Journal of the Acoustical Society of Korea
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• v.33 no.4
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• pp.248-254
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• 2014

Among acoustic signal analysis tasks, acoustic context awareness is one of the most formidable tasks in terms of complexity since it requires sophisticated understanding of individual acoustic events. In conventional context awareness methods, individual acoustic event detection or recognition is employed to generate a relevant decision on the impending context. However this approach may produce poorly performing decision results in practical situations due to the possibility of events occurring simultaneously or the acoustically similar events that are difficult to distinguish with each other. Particularly, the babble noise acoustic event occurring at a bus or subway environment may create confusion to context awareness task since babbling is similar in any environment. Therefore in this paper, a frequency-cepstral feature vector is proposed to mitigate the confusion problem during the situation awareness task of binary decisions: bus or metro. By employing the Support Vector Machine (SVM) as the classifier, the proposed feature vector scheme is shown to produce better performance than the conventional scheme.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.73-83
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• 2008

This paper proposes an implementation of an orchestration service of web services, which work as context aware applications in Ubiquitous Computing. The proposed method alms to decrease the cost of adapting to the context changes. UC requires the context adaptation more than any other computing environments, and it works based on networks of various heterogeneous platforms. Web services on SOA could be one of the solutions for the requirements. This paper proposes the way how to implement an orchestration service of SOA to handle the context adaptation while keeping the performance high. We develops an implementation model of orchestration services of web services, and the model decreases the number of code lines of the orchestration service. This paper also shows a simple empirical study, and it also analyzes two different method implementing the polymorphism, overloading and overriding.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.351-357
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• 2017

The purpose of this study is to analyze the relationship between users' expectation and satisfaction through analyzing smart phone voice recognition service and surveying the situational satisfaction of voice recognition service. First, the concept and current status of speech recognition service were investigated through literature research, and the questionnaire survey was carried out through questionnaires based on the second and third principles. As a result, the user is most likely to use the smartphone voice recognition service when making a telephone call. Also, it was found that the service is the most used at home and the service is used most when the hand is not available. Through these results, various methods such as personalization service, condition recognition function, automatic emergency recognition, unlocking by voice could be derived. Based on this research, it is expected that it will be used effectively for improving smartphone voice recognition service and developing wearable device in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.343-350
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• 2015

This paper presents a context recognition method using environmental sound signals, which is applied to a mobile-based client monitoring system. Seven acoustic contexts are defined and the corresponding environmental sound signals are obtained for the experiments. To evaluate the performance of the context recognition, MFCC and LPCC method are employed as feature extraction, and statistical pattern recognition method are used employing GMM and HMM as acoustic models, The experimental results show that LPCC and HMM are more effective at improving context recognition accuracy compared to MFCC and GMM respectively. The recognition system using LPCC and HMM obtains 96.03% in recognition accuracy. These results demonstrate that LPCC is effective to represent environmental sounds which contain more various frequency components compared to human speech. They also prove that HMM is more effective to model the time-varying environmental sounds compared to GMM.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.222-223
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• 2016

보행자 인식을 위한 컴퓨터 비전 알고리즘은 야간 상황과 같이 저조도 환경에서는 인식 성능이 떨어지고 있다. 이로 인하여 최근 저조도 환경에서 촬영된 영상으로 야간 상황에서 객체 인식 성능을 높이는 기법들이 연구되고 있다. 야간 환경은 주간 환경과는 다르게 광량이 적기 때문에 인간의 시각으로도 객체 인식에 어려움이 있고 일반적인 카메라로 촬영된 영상으로 객체 인식이 어렵다. 최근에는 NIR 카메라를 이용하여 촬영된 영상으로 야간 보행자 인식 알고리즘이 개발되고 있으나, 인식률과 객체 인식 가능 거리 및 범위가 한정적이다. 또한 기존의 야간 보행자 검출 기법들은 방대한 연산량이 필요하기 때문에 실시간 객체 인식이 불가능하다. 본 논문에서는 NIR 카메라로부터 촬영된 영상으로 preprocessing 후 ACF(Aggregated Channel Feature)를 이용하여 최근 연구되고 있는 카메라 움직임이 있는 야간 환경에서 보행자 인식 알고리즘을 PC 및 TK1 Board 환경에서 구현하고 객체 인식률을 높인다.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.148-153
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• 2008

네트워크 환경과 컴퓨팅 기술이 발전하고 모바일 디바이스의 수가 증가함에 따라 상황 인식 서비스(Context-Aware Service)의 중요성이 부각되고 있다. 최근 몇 년 동안, 상황 인식 서비스(Context-Aware Service)를 실현하기 위한 여러 연구가 진행되었지만, 해결해야 할 문제점들이 남아있다. 기존의 접근 방법들은 상황에 적합한 서비스나 추천 알고리즘을 도입함에 있어서 특정 응용(Application)이나 영역(Domain)에 종속적이고 유연성이 떨어진다는 문제가 있다. 또한 온톨로지 추론 엔진에 서비스 제공을 위한 대부분의 정보 표현과 추론을 전가하기 때문에 실제 서비스에 활용할 수 있는 정도의 성능을 기대하기 어려우며 확장성(Scalability)이 떨어진다. 본 논문에서는 서비스 요청과 서비스 처리 계층으로 계층을 분리하고 두 계층에서의 온톨로지 추론 엔진과 관계형 데이터베이스의 역할을 명확히 정의함으로써 이와 같은 문제점들을 해결하는 실용적(Practical)인 상황 인식 서비스 전달 프레임워크(Context-Aware Service Delivery Framework)를 제시하고. 시나리오를 통해 서비스 프로세스를 설명한다. 제시된 프레임워크는 현재 프로토타입의 개발을 진행 중이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2265-2271
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• 2011

This paper presents an u-health Care system based on context-awareness information. Extended project induced an education for creative engineering design. It could occur one of the issue for life care or wellness in recently life. Especially u-health Care system help on achieving this object as an efficient care-training with user blood pressure or with echocardiogram, electromyogram, electroencephalogram, or Electrocardiography. In this paper, development project show an u-health care system based on this parameters of the context-awareness with network service and analysis provide with working memory(DB) for user data base applications.