• Title/Summary/Keyword: Multiple sensors

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Design of Mobile Phone Middleware based on Integrated Context Provisioning Strategy (통합 상황 프로비저닝 전략을 기반으로 한 모바일 폰 미들웨어의 설계)

  • Jeong, Hyun-Jin;Won, You-Hun
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.1 s.45
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    • pp.89-98
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    • 2007
  • In these days, the use of context in application running on mobile devices such as PDAs and smart Phone has become a crucial requirement for several research areas, including ubiquitous computing. mobile computing. Previous middlewares which support context provisioning uses single strategy. But, this paper proposed middleware integrated multiple strategies for context provisioning, namely internal sensors-based, external infrastructure-based, and distributed provisioning in ad hoc networks. Applications can query needed context items using SQL like context query language and require context information to use different provisioning mechanisms depending on resource availability and presence of external infrastructures.

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Feature Based Decision Tree Model for Fault Detection and Classification of Semiconductor Process (반도체 공정의 이상 탐지와 분류를 위한 특징 기반 의사결정 트리)

  • Son, Ji-Hun;Ko, Jong-Myoung;Kim, Chang-Ouk
    • IE interfaces
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    • v.22 no.2
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    • pp.126-134
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    • 2009
  • As product quality and yield are essential factors in semiconductor manufacturing, monitoring the main manufacturing steps is a critical task. For the purpose, FDC(Fault detection and classification) is used for diagnosing fault states in the processes by monitoring data stream collected by equipment sensors. This paper proposes an FDC model based on decision tree which provides if-then classification rules for causal analysis of the processing results. Unlike previous decision tree approaches, we reflect the structural aspect of the data stream to FDC. For this, we segment the data stream into multiple subregions, define structural features for each subregion, and select the features which have high relevance to results of the process and low redundancy to other features. As the result, we can construct simple, but highly accurate FDC model. Experiments using the data stream collected from etching process show that the proposed method is able to classify normal/abnormal states with high accuracy.

The Bearing Estimation of Narrowband Acoustic Signals Using DIFAR Beamforming Algorithm (DIFAR 빔형성 알고리듬을 이용한 협대역 음향신호의 방향성 추정)

  • 장덕홍;박홍배;정문섭;김인수
    • Journal of the Korea Institute of Military Science and Technology
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    • v.5 no.2
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    • pp.169-184
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    • 2002
  • In order to extract bearing information from the directional sensors of DIFAR(directional frequency analysis and recording) that is a kind of passive sonobuoy, the cardioid beamforming algorithm applicable to DIFAR system was studied in the frequency domain. the algorithm uses narrow-band signals propagated though the media from the acoustic sources such as ship machineries. The proposed algorithm is expected to give signal to noise ratio of 6dB when it uses the maximum response axis(MRA) among the Cardioid beams. The estimated bearings agree very well with those from GPS data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1~$6.7^{\circ}$ and 13.3~$43.6^{\circ}$, respectively. Estimation errors are caused by SMR degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

Human Detection in Images Using Optical Flow and Learning (광 흐름과 학습에 의한 영상 내 사람의 검지)

  • Do, Yongtae
    • Journal of Sensor Science and Technology
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    • v.29 no.3
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    • pp.194-200
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    • 2020
  • Human detection is an important aspect in many video-based sensing and monitoring systems. Studies have been actively conducted for the automatic detection of humans in camera images, and various methods have been proposed. However, there are still problems in terms of performance and computational cost. In this paper, we describe a method for efficient human detection in the field of view of a camera, which may be static or moving, through multiple processing steps. A detection line is designated at the position where a human appears first in a sensing area, and only the one-dimensional gray pixel values of the line are monitored. If any noticeable change occurs in the detection line, corner detection and optical flow computation are performed in the vicinity of the detection line to confirm the change. When significant changes are observed in the corner numbers and optical flow vectors, the final determination of human presence in the monitoring area is performed using the Histograms of Oriented Gradients method and a Support Vector Machine. The proposed method requires processing only specific small areas of two consecutive gray images. Furthermore, this method enables operation not only in a static condition with a fixed camera, but also in a dynamic condition such as an operation using a camera attached to a moving vehicle.

Species Concentration Measurement Using Diode Laser Absorption Spectroscopy (I) (다이오드 레이저를 이용한 광흡수 농도 계측 기법 (I))

  • Ahn, Jae-Hyun;Kim, Yong-Mo;Kim, Se-Won
    • Journal of the Korean Society of Combustion
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    • v.9 no.3
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    • pp.27-35
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    • 2004
  • Diode laser absorption sensors are advantageous because they may provide fast, sensitive, absolute, and selective measurements of species concentration. These systems are very attractive for practical applications owing to its compactness, resonable cost, robustness, and ease of use. In addition, diode lasers are fiber-optic compatible and thus enable simultaneous measurements of multiple species along a line-of-sight. Recent advances of room-temperature, near-IR and visible diode laser sources for telecommunication, optical data storage applications make it possible to be applied for combustion diagnostics based on diode laser absorption spectroscopy. Therefore, combined with fiber-optics and high sensitive detection strategies, compact and portable sensor systems are now appearing for variety of applications. The objectives of this research are to develope a new gas sensing system and to verify feasibility of this system. Wavelength and power characteristics as a function of injection current and temperature are experimentally found out. Direct absorption spectroscopy has been demonstrated in these experiments and has a bright prospect to this diode laser system.

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Study on Tactical Target Tracking Performance Using Unscented Transform-based Filtering (무향 변환 기반 필터링을 이용한 전술표적 추적 성능 연구)

  • Byun, Jaeuk;Jung, Hyoyoung;Lee, Saewoom;Kim, Gi-Sung;Kim, Kiseon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.17 no.1
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    • pp.96-107
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    • 2014
  • Tracking the tactical object is a fundamental affair in network-equipped modern warfare. Geodetic coordinate system based on longitude, latitude, and height is suitable to represent the location of tactical objects considering multi platform data fusion. The motion of tactical object described as a dynamic model requires an appropriate filtering to overcome the system and measurement noise in acquiring information from multiple sensors. This paper introduces the filter suitable for multi-sensor data fusion and tactical object tracking, particularly the unscented transform(UT) and its detail. The UT in Unscented Kalman Filter(UKF) uses a few samples to estimate nonlinear-propagated statistic parameters, and UT has better performance and complexity than the conventional linearization method. We show the effects of UT-based filtering via simulation considering practical tactical object tracking scenario.

User-centric Scalability Measurement System of Large-Scale Measurement Data for 400km/h High-Speed Railway (400km/h 고속철도 대규모 계측데이터 사용자 중심 확장성 계측시스템)

  • Hwang, Kyung-Hun;Park, Sun-Kyu;Song, Byung-Keun;Yang, OK-Yul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.2
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    • pp.1157-1163
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    • 2014
  • Needs for a new technologies of infrastructure systems arose, following the development of next generation EMU(Electric Multiple Unit) train with maximum speed over 400km/h. For high-speed operation tests of the new EMU, a high-speed railway infrastructure test-bed was constructed in a 28km long section of the Honam High-speed Railway. Diverse sensors and monitoring system was installed for continuous monitoring of the railway. Due to such effort, further demands and needs of the integrated monitoring system was derived in a more comprehensive and long-term perspective.

The Performance Analysis of IMM-MPDA Filter in Multi-lag Out of Sequence Measurement Environment (Multi-lag Out of Sequence Measurement 환경에서의 IMM-MPDA 필터 성능 분석)

  • Seo, Il-Hwan;Song, Taek-Lyul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.8
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    • pp.1476-1483
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    • 2007
  • In a multi-sensor target tracking systems, the local sensors have the role of tracking the target and transferring the measurements to the fusion center. The measurements from the same target can arrive out of sequence called, the out-of-sequence measurements(OOSMs). The OOSM can arise in a form of single-lag or multi-lag throughout the transfer at the fusion center. The recursive retrodiction step was proposed to update the current state estimates with the multi-lag OOSM from the several previous papers. The real world has the possible situations that the maneuvering target informations can arrive at the fusion center with the random clutter in the possible OOSMs. In this paper, we incorporate the IMM-MPDA(Interacting Multiple Model - Most Probable Data Association) into the multi-lag OOSM update. The performance of the IMM-MPDA filter with multi-lag OOSM update is analyzed for the various clutter densities, OOSM lag numbers, and target maneuvering indexes. Simulation results show that IMM-MPDA is sufficient to be used in out of sequence environment and it is necessary to correct the current state estimates with OOSM except a very old OOSM.

Data Alignment for Data Fusion in Wireless Multimedia Sensor Networks Based on M2M

  • Cruz, Jose Roberto Perez;Hernandez, Saul E. Pomares;Cote, Enrique Munoz De
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.1
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    • pp.229-240
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    • 2012
  • Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.

Global Map Building and Navigation of Mobile Robot Based on Ultrasonic Sensor Data Fusion

  • Kang, Shin-Chul;Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.198-204
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    • 2007
  • In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.