• Title/Summary/Keyword: Sensing data

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Statistical Estimates of Cloud Thickness and Precipitable Water from GMS Brightness Data (GMS Brightness를 사용한 구름 두께와 가강수량의 통계적 추정)

  • 최영진;신동인
    • Korean Journal of Remote Sensing
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    • v.6 no.2
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    • pp.153-164
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    • 1990
  • A statistical correlation between cloud thickness and brightness is shown by regression analysis using the least-square method. Cloud thicknesses are obtained from radiosonde observation. Brightness values are obtained from GMS visible channel. Regression analyses are preformed on both thickness data used in conjunction with brightness data for summer season. The results are shown by the regression curve relating thickness and brightness accounting for 79% of variance. And the relationship between thickness and precipitable water in the cloud layers is analyzed. The thickness shows a positive correlation with precipitable water in cloudy layers.

Relational Detabase Management System as Expert System Building Tool in Geographic Information Systems

  • Lee, Kyoo-Seok
    • Korean Journal of Remote Sensing
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    • v.3 no.2
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    • pp.115-119
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    • 1987
  • After the introduction of the topologically structured geographic information system(GIS) with relational DBMS, the attribute data can be handled without considering locational data. By utilzing of the characteristic of the relational DBMS, it can be used as an expert system building tool in GIS. The relational DBMS of the GIS furnishes the data needed to perform deductive functions of the expert system, and the rule based approach provides the decision rules. Therefore, rule based approach with the expert judgement can be easily combined with relational DBMS.

Inertial Motion Sensing-Based Estimation of Ground Reaction Forces during Squat Motion (관성 모션 센싱을 이용한 스쿼트 동작에서의 지면 반력 추정)

  • Min, Seojung;Kim, Jung
    • Journal of the Korean Society for Precision Engineering
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    • v.32 no.4
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    • pp.377-386
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    • 2015
  • Joint force/torque estimation by inverse dynamics is a traditional tool in biomechanical studies. Conventionally for this, kinematic data of human body is obtained by motion capture cameras, of which the bulkiness and occlusion problem make it hard to capture a broad range of movement. As an alternative, inertial motion sensing using cheap and small inertial sensors has been studied recently. In this research, the performance of inertial motion sensing especially to calculate inverse dynamics is studied. Kinematic data from inertial motion sensors is used to calculate ground reaction force (GRF), which is compared to the force plate readings (ground truth) and additionally to the estimation result from optical method. The GRF estimation result showed high correlation and low normalized RMSE(R=0.93, normalized RMSE<0.02 of body weight), which performed even better than conventional optical method. This result guarantees enough accuracy of inertial motion sensing to be used in inverse dynamics analysis.

An Exponential Smoothing Adaptive Failure Detector in the Dual Model of Heartbeat and Interaction

  • Yang, Zhiyong;Li, Chunlin;Liu, Yanpei;Liu, Yunchang;Xu, Lijun
    • Journal of Computing Science and Engineering
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    • v.8 no.1
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    • pp.17-24
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    • 2014
  • In this paper, we propose a new implementation of a failure detector. The implementation uses a dual model of heartbeat and interaction. First, the heartbeat model is adopted to shorten the detection time, if the detection process does not receive the heartbeat message in the expected time. The interaction model is then used to check the process further. The expected time is calculated using the exponential smoothing method. Exponential smoothing can be used to estimate the next arrival time not only in the random data, but also in the data of linear trends. It is proven that the new detector in the paper can eventually be a perfect detector.

Application of the Landsat TM/ETM+, KOMPSAT EOC, and IKONOS to Study the Sedimentary Environments in the Tidal Flats of Kanghwa and Hwang-Do, Korea

  • Ryu Joo-Hyung;Lee Yoon-Kyung;Yoo Hong-Rhyong;Park Chan-Hong
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.140-143
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    • 2004
  • The west coast of the Korean Peninsula is famous for its large tidal range (up to 9 m) and vast tidal flats. With comparison the sedimentary environments of open and close tidal flat using remote sensing, we select Kanghwa tidal flat and Hwang-Do tidal flat in Cheonsu Bay. Prior to surface sediment discrimination using remote sensing, sedimentary environments including intertidal OEM, hydraulic condition, and relationship between grain size and various tidal condition are investigated. Remote sensing has the potential to provide synoptic information of intertidal environments. The objectives of this study are: (i) to generate an intertidal digital elevation model (OEM) using the waterline method of Lansat TM/ETM+, (ii) to investigate the tidal channel distribution using texture analysis, and (iii) to analyze the relationship between surface grain size by using in-situ data and intertidal OEM and tidal channel density by using high-resolution satellite data such as IKONOS and Kompsat EOC. The results demonstrate that satellite remote sensing is an efficient and effective tool for a surface sediment discrimination and long term morphologic change estimation in tidal flats.

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APPLICATION OF REMOTE SENSING FOR COASTAL HAZARD MONITORING IN TAM GIANG - CAU HAI LAGOON, VIETNAM

  • Dien, Tran Van;Lan, Tran Dinh;Huong, Do Thu
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.455-458
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    • 2006
  • Stretching on the coastline of 70 km, the Tam Giang - Cau Hai Lagoon plays a very important role for the coastal ecology and socio-economic development of Hue region where was Vietnam's Ancient Kingdom Capital and recognized as a World's Cultural Heritage. Recently, coastal hazard in the lagoon have occurred seriously such as inlet movement and fill up, coastal erosion, flood and inundation, etc. These hazards have impacted on lagoon environment, resources, ecosystems, socio-economic and sustainable development of this coastal area. This paper present a case study using remote sensing data in combination with ground survey for monitoring the coastal hazards in Tam Giang - Cau Hai lagoon in recent decades. Analysis results find that during its natural evolution, the lagoon has been being in three situations of only one, two and three inlets. When inlets opened or displaced, coastal erosion have occurred seriously toward new balance condition. Flood and inundation occurs every rainy season in lowland plain around lagoon. The historical flood happened in early of November 1999 with six days long, created very terrible damages for Thua Thien Hue province. Remote sensing data with capability of regular update, large area coverage is effective provide real-time and continuous information for coastal hazards monitoring.

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Developing an integrated software solution for active-sensing SHM

  • Overly, T.G.;Jacobs, L.D.;Farinholt, K.M.;Park, G.;Farrar, C.R.;Flynn, E.B.;Todd, M.D.
    • Smart Structures and Systems
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    • v.5 no.4
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    • pp.457-468
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    • 2009
  • A novel approach for integrating active sensing data interrogation algorithms for structural health monitoring (SHM) applications is presented. These algorithms cover Lamb wave propagation, impedance methods, and sensor diagnostics. Contrary to most active-sensing SHM techniques, which utilize only a single signal processing method for damage identification, a suite of signal processing algorithms are employed and grouped into one package to improve the damage detection capability. A MATLAB-based user interface, referred to as HOPS, was created, which allows the analyst to configure the data acquisition system and display the results from each damage identification algorithm for side-by-side comparison. By grouping a suite of algorithms into one package, this study contributes to and enhances the visibility and interpretation of the active-sensing methods related to damage identification. This paper will discuss the detailed descriptions of the damage identification techniques employed in this software and outline future issues to realize the full potential of this software.

Evaluation of Geo-based Image Fusion on Mobile Cloud Environment using Histogram Similarity Analysis

  • Lee, Kiwon;Kang, Sanggoo
    • Korean Journal of Remote Sensing
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    • v.31 no.1
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    • pp.1-9
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    • 2015
  • Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

Securing Cooperative Spectrum Sensing against Rational SSDF Attack in Cognitive Radio Networks

  • Feng, Jingyu;Zhang, Yuqing;Lu, Guangyue;Zhang, Liang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.1
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    • pp.1-17
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    • 2014
  • Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce radio spectrum resources. However, most of CSS schemes assume all secondary users (SU) are honest, and thus offering opportunities for malicious SUs to launch the spectrum sensing data falsification attack (SSDF attack). To combat such misbehaved behaviors, recent efforts have been made to trust schemes. In this paper, we argue that powering CSS with traditional trust schemes is not enough. The rational SSDF attack is found in this paper. Unlike the simple SSDF attack, rational SSDF attackers send out false sensing data on a small number of interested primary users (PUs) rather than all PUs. In this case, rational SSDF attackers can keep up high trustworthiness, resulting in difficultly detecting malicious SUs in the traditional trust schemes. Meanwhile, a defense scheme using a novel trust approach is proposed to counter rational SSDF attack. Simulation results show that this scheme can successfully reduce the power of rational SSDF, and thus ensure the performance of CSS.

Direct Depth and Color-based Environment Modeling and Mobile Robot Navigation (스테레오 비전 센서의 깊이 및 색상 정보를 이용한 환경 모델링 기반의 이동로봇 주행기술)

  • Park, Soon-Yong;Park, Mignon;Park, Sung-Kee
    • The Journal of Korea Robotics Society
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    • v.3 no.3
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    • pp.194-202
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    • 2008
  • This paper describes a new method for indoor environment mapping and localization with stereo camera. For environmental modeling, we directly use the depth and color information in image pixels as visual features. Furthermore, only the depth and color information at horizontal centerline in image is used, where optical axis passes through. The usefulness of this method is that we can easily build a measure between modeling and sensing data only on the horizontal centerline. That is because vertical working volume between model and sensing data can be changed according to robot motion. Therefore, we can build a map about indoor environment as compact and efficient representation. Also, based on such nodes and sensing data, we suggest a method for estimating mobile robot positioning with random sampling stochastic algorithm. With basic real experiments, we show that the proposed method can be an effective visual navigation algorithm.

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