• Title/Summary/Keyword: Sensing and Application

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A Modulation Transfer Function Compensation for the Geostationary Ocean Color Imager (GOCI) Based on the Wiener Filter

  • Oh, Eunsong;Ahn, Ki-Beom;Cho, Seongick;Ryu, Joo-Hyung
    • Journal of Astronomy and Space Sciences
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    • v.30 no.4
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    • pp.321-326
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    • 2013
  • The modulation transfer function (MTF) is a widely used indicator in assessments of remote-sensing image quality. This MTF method is also used to restore information to a standard value to compensate for image degradation caused by atmospheric or satellite jitter effects. In this study, we evaluated MTF values as an image quality indicator for the Geostationary Ocean Color Imager (GOCI). GOCI was launched in 2010 to monitor the ocean and coastal areas of the Korean peninsula. We evaluated in-orbit MTF value based on the GOCI image having a 500-m spatial resolution in the first time. The pulse method was selected to estimate a point spread function (PSF) with an optimal natural target such as a Seamangeum Seawall. Finally, image restoration was performed with a Wiener filter (WF) to calculate the PSF value required for the optimal regularization parameter. After application of the WF to the target image, MTF value is improved 35.06%, and the compensated image shows more sharpness comparing with the original image.

Monitoring of Graveyards in Mountainous Areas with Simulated KOMPSAT-2 imagery

  • Chang, Eun-Mi;Kim, Min-Ho;Lee, Byung-Whan;Heo, Min
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1409-1411
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    • 2003
  • The application of simulated KOMPSAT-2 imagery to monitor graveyards is to be developed. Positions calculated from image were compared with those obtained from Geographic Positioning System. With 24 checkpoints, the position of graveyards showed within 5-meter range. Unsupervised classification, supervised classification, and objected-orientation classification algorithms were used to extract the graveyard. Unsupervised classification with masking processes based on National topographic data gives the best result. The graveyards were categorized with four types in field studies while the two types of graveyards were shown in descriptive statistics. Cluster Analysis and discriminant analysis showed the consistency with two types of tombs. It was hard to get a specific spectral signature of graveyards, as they are covered with grasses at different levels and shaded from the surrounding trees. The slopes and aspects of location of graveyards did not make any difference in the spectral signatures. This study gives the basic spectral characteristics for further development of objected-oriented classification algorithms and plausibility of KOMPSAT-2 images for management of mountainous areas in the aspect of position accuracy and classification accuracy.

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A Learning-based Power Control Scheme for Edge-based eHealth IoT Systems

  • Su, Haoru;Yuan, Xiaoming;Tang, Yujie;Tian, Rui;Sun, Enchang;Yan, Hairong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.12
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    • pp.4385-4399
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    • 2021
  • The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

Measuring productivity improvement by Machine Guidance through work sampling in earthwork

  • Eom, Julee;Kang, Youngcheol;Lee, Yongsei;Choi, Pyungho
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.409-416
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    • 2020
  • This paper proposes a study measuring productivity improvement by using a type of technology called "Machine Guidance" through work sampling in earthwork. Earthwork is the activity typically on the critical path, indicating that productivity for the activity is critical for managing schedule on time. Thanks to the development of sensing and information system technologies, productivity for earthwork has been improved. While there have been many studies investigating the application of a certain type of technology to earthwork, few studies have measured the productivity improvement and presented how the technology leads to productivity improvement. Based on the thorough literature review, it is hypothesized that Machine Guidance contributes to improving productivity of earthwork by reducing indirect workhours spent for information waiting and inspection. In addition to the literature review, this paper presents a research model to test the hypothesis by using the work sampling technique. By proving and quantifying the productivity improvement from the technology use, this study can help practitioners justify the investment for technology use, which will contribute to the deployment of technology and more effective execution of earthwork.

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Weighted Centroid Localization Algorithm Based on Mobile Anchor Node for Wireless Sensor Networks

  • Ma, Jun-Ling;Lee, Jung-Hyun;Rim, Kee-Wook;Han, Seung-Jin
    • Journal of Korea Spatial Information System Society
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    • v.11 no.2
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    • pp.1-6
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    • 2009
  • Localization of nodes is a key technology for application of wireless sensor network. Having a GPS receiver on every sensor node is costly. In the past, several approaches, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. Most of them use some special nodes, called anchor nodes, which are assumed to know their own locations. Other sensors compute their locations based on the information provided by these anchor nodes. This paper uses a single mobile anchor node to move in the sensing field and broadcast its current position periodically. We provide a weighted centroid localization algorithm that uses coefficients, which are decided by the influence of mobile anchor node to unknown nodes, to prompt localization accuracy. We also suggest a criterion which is used to select mobile anchor node which involve in computing the position of nodes for improving localization accuracy. Weighted centroid localization algorithm is simple, and no communication is needed while locating. The localization accuracy of weighted centroid localization algorithm is better than maximum likelihood estimation which is used very often. It can be applied to many applications.

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Combining Dynamic Time Warping and Single Hidden Layer Feedforward Neural Networks for Temporal Sign Language Recognition

  • Thi, Ngoc Anh Nguyen;Yang, Hyung-Jeong;Kim, Sun-Hee;Kim, Soo-Hyung
    • International Journal of Contents
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    • v.7 no.1
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    • pp.14-22
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    • 2011
  • Temporal Sign Language Recognition (TSLR) from hand motion is an active area of gesture recognition research in facilitating efficient communication with deaf people. TSLR systems consist of two stages: a motion sensing step which extracts useful features from signers' motion and a classification process which classifies these features as a performed sign. This work focuses on two of the research problems, namely unknown time varying signal of sign languages in feature extraction stage and computing complexity and time consumption in classification stage due to a very large sign sequences database. In this paper, we propose a combination of Dynamic Time Warping (DTW) and application of the Single hidden Layer Feedforward Neural networks (SLFNs) trained by Extreme Learning Machine (ELM) to cope the limitations. DTW has several advantages over other approaches in that it can align the length of the time series data to a same prior size, while ELM is a useful technique for classifying these warped features. Our experiment demonstrates the efficiency of the proposed method with the recognition accuracy up to 98.67%. The proposed approach can be generalized to more detailed measurements so as to recognize hand gestures, body motion and facial expression.

APPLICATION OF QUICKBIRD SATELLITE IMAGE TO STORM RUNOFF MODELLING

  • Kim, Sang-Ho;Lee, Mi-Seon;Park, Geun-Ae;Hong, Suk-Young;Choi, Chul-Uong;Kim, Seong-Joon
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.602-605
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    • 2006
  • This study is to apply QuickBird satellite image for the simulation of storm runoff in a small rural watershed. For a 1.05 $km^2$ watershed located in Goesan-Gun of Chungbuk Province, the land use from the QuickBird image was produced by on-screening digitising after ortho-rectifying using 2 m DEM. For 3 cases of land use, soil and elevation scale (1:5,000, 1:25,000 and 1:50,000), SCS (Soil Conservation Service)-CN (Curve Number) and the watershed physical parameters were prepared for the storm runoff model, HEC-HMS (Hydrological Modelling System). The model was evaluated for each case and compared the simulated results with couple of selected storm events.

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RPC MODEL FOR ORTHORECTIFYING VHRS IMAGE

  • Ke, Luong Chinh
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.631-634
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    • 2006
  • Three main important sources for establishing GIS are the orthomap in scale 1:5 000 with Ground Sampling Distance of 0,5m; DEM/DTM data with height error of ${\pm}$1,0m and topographic map in scale 1: 10 000. The new era with Very High Resolution Satellite (VHRS) images as IKONOS, QuickBird, EROS, OrbView and other ones having Ground Sampling Distance (GSD) even lower than 1m has been in potential for producing orthomap in large scale 1:5 000, to update existing maps, to compile general-purpose or thematic maps and for GIS. The accuracy of orthomap generated from VHRS image affects strongly on GIS reliability. Nevertheless, orthomap accuracy taken from VHRS image is at first dependent on chosen sensor geometrical models. This paper presents, at fist, theoretical basic of the Rational Polynomial Coefficient (RPC) model installed in the commercial ImageStation Systems, realized for orthorectifying VHRS images. The RPC model of VHRS image is a replacement camera mode that represents the indirect relation between terrain and its image acquired on the flight orbit. At the end of this paper the practical accuracies of IKONOS and QuickBird image orthorectified by RPC model on Canadian PCI Geomatica System have been presented. They are important indication for practical application of producing digital orthomaps.

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A Calibration and Uncertainty Analysis on the Load Monitoring System for a Low Speed Shaft and Rotor Blade of a Wind Turbine (풍력발전기 주축 및 날개 부하 측정시스템의 보정 및 불확실성 해석)

  • Park Moo-Yeol;Yoo Neung-Soo;Nam Yoon-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.5 s.248
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    • pp.560-567
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    • 2006
  • The exact load measurements for the mechanical parts of a wind turbine are important step both fur the evaluation of a specific wind turbine design and for a certification process. A common method for a mechanical load measurement is using a strain gauge sensing. Two main problems ought to be answered in order for this method to be applied to the wind turbine project. These are strain gauge calibration and non-contact signal transmission from the strain gauge output to a load monitoring system. This paper suggests reliable solutions fer these two problems. A Bluetooth, a short range wireless data communication technology, is used to solve the second problem. The first one, the strain gauge calibration methodology for a load measurement in a wind turbine application, is fully explained in this paper. Various mechanical loadings for a strain gauge calibration in a wind turbine load measurement are introduced and analyzed. Initial experimental results which are obtained from a 1 kW small size wind turbine are analyzed, and the uncertainty problem in estimating mechanical loads using a calibration matrix is fully covered in this paper.

A Localization Scheme Using Mobile Robot in Wireless Sensor Networks (무선 센서 네트워크에서 이동성 로봇을 이용한 센서 위치 인식 기법에 관한 연구)

  • Kim, Woo-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.10 no.2
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    • pp.105-113
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    • 2007
  • Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of application. Sensor position is used for its data to be meaningful and for energy efficient data routing algorithm especially geographic routing. The previous works for sensor localization utilize global positioning system(GPS) or estimate unknown-location nodes position with help of some small reference nodes which know their position previously. However, the traditional localization techniques are not well suited in the senor network for the cost of sensors is too high. In this paper, we propose the sensor localization method with a mobile robot, which knows its position, moves through the sensing field along pre-scheduled path and gives position information to the unknown-location nodes through wireless channel to estimate their position. We suggest using the sensor position estimation method and an efficient mobility path model. To validate our method, we carried out a computer simulation, and observed that our technique achieved sensor localization more accurately and efficiently than the conventional one.

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