• Title/Summary/Keyword: sensor noise

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Estimation of Dynamic Displacements of a Bridge using FBG Sensors (FBG센서를 이용한 교량의 동적변위 추정)

  • Shin, Soobong;Yun, Byeong-Goo;Kim, Jae-Cheon
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.13 no.3 s.55
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    • pp.101-109
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    • 2009
  • An algorithm is proposed for estimating dynamic displacements of a bridge by using FBG sensors and by superposing some measurable low modes. Modal displacements are obtained from the beam theory and the generalized coordinates are deduced from the strains measured by FBG sensors. By considering flexural and torsional modes occurred in bridges only as flexural modes of a simply supported beam by separating a bridge into multiple girders or parts, the proposed algorithm can be applied to various types of bridges. Guidelines are provided theoretically for determining the number of modes and the number of strain gages to be used. The proposed algorithm has been examined through simulation studies on various types of bridges, laboratory experiments on a model bridge, and field tests on a simple span PC Box girder bridge. Through the simulation study, the effects of the error in the vibration modes and measurement noise on estimating the dynamic displacements are analyzed.

Hybrid LSTM and Deep Belief Networks with Attention Mechanism for Accurate Heart Attack Data Analytics

  • Mubarak Albathan
    • International Journal of Computer Science & Network Security
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    • v.24 no.10
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    • pp.1-16
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    • 2024
  • Due to its complexity and high diagnosis and treatment costs, heart attack (HA) is the top cause of death globally. Heart failure's widespread effect and high morbidity and death rates make accurate and fast prognosis and diagnosis crucial. Due to the complexity of medical data, early and accurate prediction of HA is difficult. Healthcare providers must evaluate data quickly and accurately to intervene. This novel hybrid approach predicts HA using Long Short-Term Memory (LSTM) networks, Deep belief networks (DBNs) with attention mechanism, and robust data mining to fill this essential gap. HA is predicted using Kaggle, PhysioNet, and UCI datasets. Wearable sensor data, ECG signals, and demographic and clinical data provide a solid analytical base. To maintain consistency, ECG signals are normalized and segmented after thorough cleaning to remove missing values and noise. Feature extraction employs complex approaches like Principal Component Analysis (PCA) and Autoencoders to pick time-domain (MNN, SDNN, RMSSD, PNN50) and frequency-domain (PSD at VLF, LF, HF bands) characteristics. The hybrid model architecture uses LSTM networks for sequence learning and DBNs for feature representation and selection to create a robust and comprehensive prediction model. Accuracy, precision, recall, F1-score, and ROC-AUC are measured after cross-entropy loss and SGD optimization. The LSTM-DBN model outperforms predictive methods in accuracy, sensitivity, and specificity. The findings show that several data sources and powerful algorithms can improve heart attack predictions. The proposed architecture performed well on many datasets, with an accuracy rate of 96.00%, sensitivity of 98%, AUC of 0.98, and F1-score of 0.97. High performance proves this system's dependability. Moreover, the proposed approach is outperformed compared to state-of-the-art systems.

Simulation Approach for the Tracing the Marine Pollution Using Multi-Remote Sensing Data (다중 원격탐사 자료를 활용한 해양 오염 추적 모의 실험 방안에 대한 연구)

  • Kim, Keunyong;Kim, Euihyun;Choi, Jun Myoung;Shin, Jisun;Kim, Wonkook;Lee, Kwang-Jae;Son, Young Baek;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.249-261
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    • 2020
  • Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.

Temperature Compensation of Optical FBG Sensors Embedded Tendon for Long-term Monitoring of Tension Force of Ground Anchor (광섬유 센서 내장형 텐던을 이용한 그라운드 앵커의 장기 장력모니터링을 위한 온도보상)

  • Sung, Hyun-Jong;Kim, Young-Sang;Kim, Jae-Min;Park, Gui-Hyun
    • Journal of the Korean Geotechnical Society
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    • v.28 no.5
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    • pp.13-25
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    • 2012
  • Ground anchor method is one of the most popular reinforcing technology for slope in Korea. For the health monitoring of slope which is reinforced by permanent anchor for a long period, monitoring of the tension force of ground anchor is very important. However, since electromechanical sensors such as strain gauge and V/W type load cell are also subject to long-term risk as well as suffering from noise during long distance transmission and immunity to electromagnetic interference (EMI), optical FBG sensors embedded tendon was developed to measure strain of 7-wire strand by embedding FBG sensor into the center king cable of 7-wire strand. This FBG sensors embedded tendon has been successfully applied to measuring the short-term anchor force. But to adopt this tendon to long-term monitoring, temperature compensation of the FBG sensors embedded tendon should be done. In this paper, we described how to compensate the effect in compliance with the change of underground temperature during long-term tension force monitoring of ground anchors by using optical fiber sensors (FBG: Fiber Bragg Grating). The model test was carried out to determine the temperature sensitivity coefficient (${\beta}^{\prime}$) of FBG sensors embedded tendon. The determined temperature sensitivity coefficient ${\beta}^{\prime}=2.0{\times}10^{-5}/^{\circ}C$ was verified by comparing the ground temperatures predicted from the proposed sensor using ${\beta}^{\prime}$ with ground temperatures measured from ground thermometer. Finally, temperature compensations were carried out based on ${\beta}^{\prime}$ value and ground temperature measurement from KMA for the tension force monitoring results of tension type and compression type anchors, which had been installed more than 1 year before at the test site. Temperature compensated tension forces are compared with those measured from conventional load cell during the same measuring time. Test results show that determined temperature sensitivity coefficient (${\beta}^{\prime}$) of FBG sensors embedded tendon is valid and proposed temperature compensation method is also appropriate from the fact that the temperature compensated tension forces are not dependent on the change of ground temperature and are consistent with the tension forces measured from the conventional load cell.

Hand-Eye Laser Range Finder based Welding Plane Recognition Method for Autonomous Robotic Welding (자동 로봇 용접을 위한 Hand-Eye 레이저 거리 측정기 기반 용접 평면 인식 기법)

  • Park, Jae Byung;Lee, Sung Min
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.9
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    • pp.307-313
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    • 2012
  • This paper proposes a hand-eye laser range finder (LRF) based welding plane recognition method for autonomous robotic welding. The robot welding is the process of joining a metal piece and the welding plane along the welding path predefined by the shape of the metal piece. Thus, for successful robotic welding, the position and direction of the welding plane should be exactly detected. If the detected position and direction of the plane is not accurate, the autonomous robotic welding should fail. For precise recognition of the welding plane, a line on the plane is detected by the LRF. For obtaining the line on the plane, the Hough transform is applied to the obtained data from the LRF. Since the Hough transform is based on the voting method, the sensor noise can be reduced. Two lines on the plane are obtained before and after rotation of the robot joint, and then the direction of the plane is calculated by the cross product of two direction vectors of two lines. For verifying the feasibility of the proposed method, the simulation with the robot simulator, RoboticsLab developed by Simlab Co. Ltd., is carried out.

Conceptual Design Study of NISS onboard NEXTSat-1

  • Jeong, Woong-Seob;Park, Sung-Joon;Park, Kwijong;Lee, Dae-Hee;Moon, Bongkon;Pyo, Jeonghyun;Park, Youngsik;Kim, Il-Joong;Park, Won-Kee;Lee, Duk-Hang;Park, Chan;Ko, Kyeongyeon;Nam, Ukwon;Han, Wonyong;Im, Myungshin;Lee, Hyung Mok;Lee, Jeong-Eun;Shin, Goo-Hwan;Chae, Jangsoo
    • The Bulletin of The Korean Astronomical Society
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    • v.38 no.2
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    • pp.82.2-82.2
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    • 2013
  • The NISS (Near-infrared Imaging Spectrometer for Star formation history) onboard NEXTSat-1 is being developed by KASI. The NISS will perform the imaging low-resolution spectroscopic observation in the near-infrared range for nearby galaxies, low background regions, starforming regions and so on. The off-axis reflecting telescope with a wide field of view (2 deg. ${\times}$ 2 deg.) will be operated in the wavelength range from 0.95 to $3.8{\mu}m$. In order to reduce thermal noise, a telescope and a HgCdTe infrared sensor will be cooled down to 200K and 80K, respectively. To evade a stray light outside a field of view and use limited space efficiently, the NISS adopted the off-axis reflective optical system. The primary and secondary mirrors, optomechanical part and mechanical structure were designed to use the same material. It will lessen the degradation of optical performance due to a thermal variation. The purpose of NISS is the observation of cosmic near-infrared background in the wide wavelength range as well as the detection of near-infrared spectral lines in nearby galaxies, cluster of galaxies and star forming regions. It will give us less biased information on the star formation history. In addition, we will demonstrate the space technologies related to the development of the Korea's leading near-infrared instrument for the future large infrared telescope, SPICA.

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Design and Manufacture of Improved Obstacle-Overcoming type Indoor Moving and Lifting Electric Wheelchair (향상된 장애물 극복형 실내 이·승강 전동휠체어의 설계 및 제작)

  • Kim, Young-Pil;Ham, Hun-Ju;Hong, Sung-Hee;Ko, Seok-Cheol
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.11
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    • pp.851-860
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    • 2020
  • With an increase in the aging population and a rising social interest in health and welfare, studies to improve healthcare in the elderly are being actively conducted. This study attempted to improve the current design and manufacture of elevating electric wheelchairs to enhance user safety and convenience. Seat design based on the user's body shape, convenience while boarding or alighting, caster turning radius and, safety and stability features that prevent shaking when the user gets up or sits down were improved. A driving experiment was conducted to evaluate the operation of the indoor electric wheelchair designed and manufactured with these additional functionalities. During the test, the performance parameters evaluated were continuous driving time, turning radius, maximum lifting and lowering load, maximum lifting height, noise level, minimum distance sensing by the driving auxiliary sensor, ability to interact with server and app programs, and the duty cycle maximum error rate. The test confirmed that this improved electric wheelchair successfully met target parameters. In a future study, we will evaluate this improved electric wheelchair from a user's perspective for its usability parameters, such as satisfaction, convenience and stability.

The Study on Spatial Classification of Riverine Environment using UAV Hyperspectral Image (UAV를 활용한 초분광 영상의 하천공간특성 분류 연구)

  • Kim, Young-Joo;Han, Hyeong-Jun;Kang, Joon-Gu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.10
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    • pp.633-639
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    • 2018
  • High-resolution images using remote sensing (RS) is importance to secure for spatial classification depending on the characteristics of the complex and various factors that make up the river environment. The purpose of this study is to evaluate the accuracy of the classification results and to suggest the possibility of applying the high resolution hyperspectral images obtained by using the drone to perform spatial classification. Hyperspectral images obtained from study area were reduced the dimensionality with PCA and MNF transformation to remove effects of noise. Spatial classification was performed by supervised classifications such as MLC(Maximum Likelihood Classification), SVM(Support Vector Machine) and SAM(Spectral Angle Mapping). In overall, the highest classification accuracy was showed when the MLC supervised classification was used by MNF transformed image. However, it was confirmed that the misclassification was mainly found in the boundary of some classes including water body and the shadowing area. The results of this study can be used as basic data for remote sensing using drone and hyperspectral sensor, and it is expected that it can be applied to a wider range of river environments through the development of additional algorithms.

Design of Sliding Mode Fuzzy Controller for Vibration Reduction of Large Structures (대형구조물의 진동 감소를 위한 슬라이딩 모드 퍼지 제어기의 설계)

  • 윤정방;김상범
    • Journal of the Earthquake Engineering Society of Korea
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    • v.3 no.3
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    • pp.63-74
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    • 1999
  • A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

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Concentration of Sodium Chloride Solutions Sensing by Using a Near-Field Microwave Microprobe (비접촉 근접장 마이크로파 현미경을 이용한 NaCl 용액의 농도 측정)

  • Kim, Song-Hui;Yoon, Young-Woon;Babajanyan, Arsen;Kim, Jong-Chul;Lee, Kie-Jin
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.1
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    • pp.23-30
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    • 2007
  • We observed the NaCl concentration of solutions using a near-field microwave microprobe(NFMM). Instead of the usual technique, we take advantage of the noncontact evaluation capabilities of a NFMM. A NFMM with a high Q dielectric resonator allows observation of small variations of the permittivity due to changes in the NaCl concentration. The changes of NaCl concentration due to a change of permittivity of the NaCl solution were investigated by measuring the microwave reflection coefficient $S_{11}$ of the resonator. The NaCl sensor consisted of a dielectric resonator coupled to a probe tip at an operating frequency of about f=4 GHz. The change of the NaCl concentration is directly related to the change of the reflection coefficient due to a near field electromagnetic interaction between the probe tip and the NaCl solution. In order to determine the probe selectivity, we measured a mixture solution of NaCl and glucose.