• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.9 s.351
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• pp.23-30
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• 2006

This paper presents a design of a high-efficiency CMOS DC-DC boost converter using a current-sensing feedback method. High-precision current-sensing circuity is incorporated in order to sense the current flowing in the inductor, which determines the switching scheme of the pulse-width modulation. The external components or large chip area for the frequency compensation can be avoided while maintaining the stable operations of the converter. Various input/output voltage levels can be available through the external resistor strings. The designed DC-DC converter is fabricated in a 0.18-um CMOS technology with a thick-gate oxide option. The converter shows the maximum efficiency over 90% for the output voltage of 3.3V and load current larger than 200mA. The load regulation is 1.15% for the load current change of 100mA.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.712-721
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• 2010

This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have continuous and an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generated and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.133-141
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• 2006

Recently many wearable computers have been developed. But they still have many user interface problems from both an input and output perspective. This paper presents a wearable user interface based on EOG(electrooculogram) sensing circuit and marker recognition. In the proposed user interface, the EOG sensor circuit which tracks the movement of eyes by sensing the potential difference across the eye is used as a pointing device. Objects to manipulate are represented human readable markers. And the marker recognition system detects and recognize markers from the camera input image. When a marker is recognized, the corresponding property window and method window are displayed to the head mounted display. Users manipulate the object by selecting a property or a method item from the window. By using the EOG sensor circuit and the marker recognition system, we can manipulate an object with only eye movement in the wearable computing environment.

• The KIPS Transactions:PartB
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• v.16B no.6
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• pp.463-470
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• 2009

In this paper, we propose the advanced fire-flame detection algorithm using camera image for better performance than previous sensors-based systems which is limited on small area. Also, previous works using camera image were depend on a lot of heuristic thresholds or required an additional computation time. To solve these problems, we use statistical values and divide image into blocks to reduce the processing time. First, from the captured image, candidate flame regions are detected by a background model and fire colored models of the fire-flame. After the probability models are formed using the change of luminance, wavelet transform and the change of motion on time axis, they are used for membership function of fuzzy logic. Finally, the result function is made by the defuzzification, and the probability value of fire-flame is estimated. The proposed system has shown better performance when it compared to Toreyin's method which perform well among existing algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.9
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• pp.807-813
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• 2016

Recently, a spherical pendulum attached to an end-effector of a robot manipulator has been frequently used for a test bed of residual vibration suppression control in a multi-dimensional motion. However, there was no automatic tracking system to detect the current bob position on-line, and there was inconvenience to not be able to store the bob position in real time and plot the trajectory. In this study, we developed a two-dimensional, real-time bob-detecting system using a digital USB camera, of which the key is hardware component design and software C programming for fast image processing and interfacing. The developed system was applied to residual vibration suppression control of a two-dimensional spherical pendulum that is attached at the end-effector of a two degree-of-freedom SCARA robot, and the effectiveness of the developed system has been demonstrated.

• Fire Science and Engineering
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• v.34 no.3
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• pp.35-42
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• 2020

The accurate prediction of fire detector activation time is required to ensure the reliability of fire modeling during the safety assessment of performance-based fire safety design. The main objective of this study is to determine the activation temperature and the response time index (RTI) of a fixed heat detector, which are the main input factors of a fixed-temperature heat detector applied to the fire dynamics simulator (FDS), a typical fire model. Therefore, a fire detector evaluator, which is a fire detector experimental apparatus, was applied, and 10 types of domestic fixed-temperature heat detectors were selected through a product recognition survey. It was found that there were significant differences in the activation temperature and RTI among the detectors. Additionally, the detector activation time of the FDS with the measured DB can be predicted more accurately. Finally, the DB of the activation temperature and RTI of the fixed-temperature heat detectors with reliability was provided.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1010-1012
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• 2017

본 논문에서는 HSV, YCbCr 컬러 모델의 색상정보를 통한 화재 검출 알고리즘을 제안한다. 첫 번째 단계에서는 영상의 변화를 감지하기 위해서 입력된 영상으로부터 평균배경영상을 계산하여 전경영상을 분리한다. 그리고 차영상을 이용해 움직임을 인식하여 컬러 모델 색상정보를 비교할 영역을 구한다. 전경영상의 구해진 영역에서 컬러모델의 복합 색상정보를 이용하여 화재 영역을 검출한다.

• Proceedings of the KAIS Fall Conference
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• 2002.05a
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• pp.203-205
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• 2002

본 연구에서는 원예작물의 저장고 내 정확한 품질판정을 위하여 관련된 여러 환경요인들을 일차적으로 센서에서 감지하고 그 정보를 컴퓨터에 자동 입력하여 이러한 환경을 자동으로 관리한 수 있는 시스템의 개발을 목적으로 한다. 또한 측정된 데이터를 언제 어디서나 볼 수 있도록 웹 페이지로 구축하고 인터넷을 통하여 저장고의 상태를 설정을 할 수 있는 원격 시스템을 구현함으로 효율적인 관리를 할 수 있는 시스템을 구성한다. 따라서 신뢰성 있는 센서 제어기를 이용하여 원예작물의 저장환경을 관리할 수 있도록 시스템 하드페어 및 응용 소프트웨어를 구축하여 자동 측정된 데이터의 분석 및 환경을 효율적으로 관리할 수 있는 자동화 시스템을 구성한다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.253-255
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• 2004

현재의 센서 네트워크를 구성하고 있는 센서 노드들은 배치 전에 미리 입력된 라우팅 및 감지 서비스만을 제공한다. 이러한 센서 네트워크 및 노드 구조는 기존의 고정화된 환경에는 적합하나 차세대 유비쿼터스 환경과 같이 시스템이 스스로 성장하며 서비스 추가 및 재설정 요구가 빈번하게 일어나는 환경에서는 그대로 적용하기가 힘들다. 따라서 본 논문에서는 유비쿼터스 환경에서 시스템 레벨의 정책 및 환경 변화에 따라 적응적으로 동작할 수 있는 센서 네트워크 노드 구조를 제안하여, 또한 제안된 구조에서 기존의 구조에 대한 에너지 소모 정도를 분석하여 제안의 현실성을 검증한다.