• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.88-95
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• 2005

Direct Georeferencing by combined multi-sensor based on the direct measurement of the projection centers and rotation angle of sensor through loading the GPS and INS in aircraft. The method of combined multi-sensor can offer us to acquire the exterior orientation parameters with only minimum GCPs, even the ground control process could be completely skipped. Consequently, It is possible extreme to reduce the time and expense for the mapping process. In this study, a CCD camera is simultaneously used in combined multi-sensor surveying, and acquired CCD image through Direct Georeferencing produce digital orthoimage. In this process, methods of combining sensor and digital orthoimage are examined and estimated. For the comparison of the positioning accuracy digital orthoimage through Direct Georeferencing, GCPs determined by GPS surveying are used. Two digital orthoimage are produced; one with a few GCP and the other without them. The accuracy of orthoimages produced through combined multi-sensor with GCPs meets that of 1:1,000 maps. Without GCPs, it meets that of 1:5,000 maps.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.43-49
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• 2010

Aerodynamic design of the vane type multi-function probe was tried by using CFD and wind tunnel test for the MALE UAV and small business jets. The present multi-function probe can measure total pressure, static pressure and angle of attack by using rotating vane. Therefore major performances are determined by aerodynamic characteristics of vane. In oder to design the sensor compatible to the requirement, aerodynamic characteristics of sensors was investigated by using CFD and dynamic response analysis was also performed for trasient performance. The final aerodynamic performance was measured by the wind tunnel test at Aeorsonic and the results successfully used for the design of vane type multi-function air data sensor.

• Journal of computational fluids engineering
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• v.15 no.3
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• pp.32-38
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• 2010

Aerodynamic design of the vane type multi-function probe was tried by using CFD and wind tunnel test for the MALE UAV and small business jets. The present multi-function probe can measure total pressure, static pressure and angle of attack by using rotating vane. Therefore, major performances are determined by aerodynamic characteristics of vane. In order to design the sensor compatible to the requirement, aerodynamic characteristics of sensors were investigated by using CFD and dynamic response analysis was also performed for transient performance. The final aerodynamic performance was measured by the wind tunnel test at Aerosonic and the results were compared with the present design. The results showed that the aerodynamic design using the CFD can be successfully used for the design of vane type multi-function air data sensor.

• Journal of Sensor Science and Technology
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• v.30 no.4
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• pp.218-222
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• 2021

Wearable multi-sensors based on nanocrystals have attracted significant attention, and studies on patterning technology to implement such multi-sensors are underway. Conventional patterning processes may affect material properties based on high temperatures and harsh chemical conditions. In this study, we developed an inkjet printing technique that can overcome these drawbacks through the application of patterning processes at room temperature and atmospheric pressure. Nanocrystal-based ink is used to adjust properties efficiently. Additionally, the viscosity and surface tension of the solvents are investigated and optimized to increase patterning performance. In the patterning process, the electrical, electrothermal, and electromechanical properties of the nanocrystal pattern are controlled by the ligand exchange process. Experimental results demonstrate that a multi-sensor with a temperature coefficient of resistance of 3.82 × 10^-3 K^-1 and gauge factor of 30.6 can be successfully fabricated using one-step inkjet printing.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1254-1258
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• 2003

One of the major factors that effect sensor performance is analog noise that added in a sensor signal such as voltage. In multi-axis force sensors, error sources may be classified mainly in two groups. One is structural error due to inaccuracy of sensor body. The other error source is noise signals existing in the sensed information. This paper presents a brief review about the principle of multi-axis force sensors, and then proposes a method that can reduce the effect of noise signal to sensor performance. The method is to convert analog voltage signal to digital numbers near sensor body and then to read these digital signals and conduct signal processing in the computer. By this way, we can eliminate a bad effect of electromagnetic wave emitted from computer and of 60 Hz noise emitted from AC source. The proposed method is investigated through experimental demonstration. The experimental results show that it improves S/N ratio of the sensor about 40 times in our experimental setup.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.21-26
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• 2009

A sensor system capable of automatically recognize activities would allow many potential Ubiquitous applications. This paper presents a new system for recognizing the activities of daily living(ADL) like walking, running, standing, sitting, lying etc. The system based on the state-dependent motion analysis using Tri-Accelerometer and Zigbee tag. Two accelerometers are used for the classification of body and hand activities. Classification of the environment and instrumental activities is performed based on the hand interaction with an object ID using.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.4
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• pp.581-587
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• 2011

A wireless sensor network needs to consist of multi-sensors in order to infer a high level of information on circumstances. Data fusion, in turn, is required to utilize the data collected from multi-sensors for the inference of information on circumstances. The current paper, based on Dempster-Shafter's evidence theory, proposes data fusion in a wireless sensor network with different weights assigned to different sensors. The frequency of events per sensor is the crucial element in calculating different weights of the data of circumstances that each sensor collects. Data fusion utilizing these different weights turns out to show remarkable difference in reliability, which makes it much easier to infer information on circumstances.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.913-919
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• 2011

In this paper, we present a new efficient event detection algorithm for sensor networks with faults. We focus on multi-attributed events, which are sets of data points that correspond to interesting or unusual patterns in the underlying phenomenon that the network monitors. Conventional algorithms cannot detect some events because they treat only their own sensor readings which can be affected easily by environmental or physical problem. Our approach exploits spatio-temporal correlation of sensor readings. Sensor nodes exchange a fault-tolerant code encoded their own readings with neighbors, organize virtual sensor readings which have spatio-temporal correlation, and determine a result for multi-attributed events from them. In the result, our proposed algorithm provides improvement of detecting multi-attributed events and reduces the number of false-negatives due to negative environmental effects.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.1003-1011
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• 2011

In this paper, a real-time multi-source sensor data management system based on wireless sensor network is proposed and implemented. The proposed management system is designed to transmit the wireless data to the server in order to monitor and control the multi-source target's status efficiently by analyzing them. The proposed system is implemented to make it possible to control and transmit the wireless sensor data by classifying them, of which data are issued from the clustered sources composed of a number of the remote multiple sensors. In order to evaluate the performance of the proposed system, we measure and analyze both the transmission delay time according to the distance and the data loss rate issued from multiple data sources. From these results, it is verified that the proposed system has a good performance.