• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.789-802
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• 2021

Synthetic Aperture Radar (SAR) at C-band is an ideal remote sensing system for crop monitoring owing to its short wavelength, which interacts with the upper parts of the crop canopy. This study evaluated the potential of dual polarimetric Sentinel-1 at C-band for monitoring rice phenology. Rice phenological variations occur in a short period. Hence, the short revisit time of Sentinel-1 SAR system can facilitate the tracking of short-term temporal morphological variations in rice crop growth. The sensitivity of SAR backscattering coefficients, backscattering ratio, and polarimetric decomposition parameters on rice phenological stages were investigated through a time-series analysis of 33 Sentinel-1 Single Look Complex images collected from 10th April to 25th October 2020 in Gimhae, South Korea. Based on the observed temporal variations in SAR parameters, we could identify and distinguish the phenological stages of the Gimhae rice growth cycle. The backscattering coefficient in VH polarisation and polarimetric decomposition parameters showed high sensitivity to rice growth. However, amongst SAR parameters estimated in this study, the VH backscattering coefficient realistically identifies all phenological stages, and its temporal variation patterns are preserved in both Sentinel-1A (S1A) and Sentinel-1B (S1B). Polarimetric decomposition parameters exhibited some offsets in successive acquisitions from S1A and S1B. Further studies with data collected from various incidence angles are crucial to determine the impact of different incidence angles on polarimetric decomposition parameters in rice paddy fields.

• Smart Structures and Systems
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• v.30 no.3
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Smart Structures and Systems
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• v.28 no.6
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• pp.827-838
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• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• Advances in nano research
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• v.15 no.2
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• pp.155-163
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• 2023

Exercise is beneficial to the body in some ways. It is vital for people who have heart problems to perform exercise according to their condition. This paper describes how an Android platform can provide early warnings of fatigue during wushu exercise using Photoplethysmography (PPG) signals. Using the data from a micro-electro-mechanical system (MEMS) gyroscope to detect heart rate, this study contributes an algorithm to determine a user's fatigue during wushu exercise. It sends vibration messages to the user's smartphone device when the heart rate exceeds the limit or is too fast during exercise. The heart rate monitoring system in the app records heart rate data in real-time while exercising. A simple pulse sensor and Android app can be used to monitor heart rate. This plug-in sensor measures heart rate based on photoplethysmography (PPG) signals during exercise. Pulse sensors can be easily inserted into the fingertip of the user. An embedded microcontroller detects the heart rate by connecting a pulse sensor transmitted via Bluetooth to the smartphone. In order to measure the impact of physical activity on heart rate, Wushu System tests are conducted using various factors, such as age, exercise speed, and duration. During testing, the Android app was found to detect heart rate with an accuracy of 95.3% and to warn the user when their heart rate rises to an abnormal level.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1199-1209
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• 2023

Where concrete structures are designed to have a service life of over 100 years, their performance must be monitored, for the prediction models available are fraught with uncertainties that need to be eliminated. The present study was conducted to meet that need by monitoring a pilot structure for low and intermediate radioactive waste storage. Long-term operation of the sensors was observed to be adequate to determine the value of the parameters that characterise structural durability, such as corrosion current density. The parameters analysed were correlated to calculate their reciprocal impact: where applied in conjunction with artificial intelligence tools, temperature, for instance, was found suitable for finding activation energy and expansion coefficients and detecting outliers. The results showed the pilot structure to perform satisfactorily.

• Journal of Ocean Engineering and Technology
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• v.38 no.4
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• pp.174-186
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• 2024

In coastal video monitoring, the direct linear transform (DLT) method with ground control points (GCPs) is commonly used for geo-rectification. However, current practices often overlook the impact of GCP quantity, arrangement, and the geographical characteristics of beaches. To address this, we designed scenarios at Chuam Beach to evaluate how factors such as the distance from the camera to GCPs, the number of GCPs, and the height of each point affect the DLT method. Accuracy was assessed by calculating the root mean square error of the distance errors between the actual GCP coordinates and the image coordinates for each setting. This analysis aims to propose an optimal GCP placement method. Our results show that placing GCPs within 200 m of the camera ensures high accuracy with few points, whereas positioning them at strategic heights enhances shoreline extraction. However, since only fixed cameras were used in this study, factors like varying heights, orientations, and resolutions could not be considered. Based on data from a single location, we propose an optimal method for GCP placement that takes into account distance, number, and height using the DLT method.

• Journal of Environmental Impact Assessment
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• v.16 no.6
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• pp.381-391
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• 2007

The air quality modeling was carried out to assess the impact of air quality for large scale urban development. The site for the assessment is Multi-fuctional Administrative City which locates in Yeongi-gun, Chungcheongnam-do and estimated population in 2030 is 500,000. Two automatic weather monitoring stations were installed to monitor the meteorological variables for a year and upper air meteorological parameters were measured using radiosonde for 5 days with 4 hours interval in every season. The air quality of standard air pollutants were also measured for 5 days continuously in every season. The results of wind field analysis based on the site measurements and CALMET modeling showed that the valley and mountain winds were prevailed when the sypnotic wind was weak. It also showed that wind speed and directions were highly space-variable within the site basin. The variable wind characteristics implies that the Gaussian dispersion model such ISC3 and AERMOD are not appropriate and the unsteady-sate Lagrangian model such as CALPUFF is preferable. CALPUFF model was applied to assess air quality impact of new sources. The new sources were those for individual and group heating facilities as well as the traffic increases. The results showed that the estimated concentrations of CO and $SO_2$ pollutants by summing the impact concentration of new sources by the dispersion model and the ambient air concentrations by the site measurements were acceptable but those of PM-10 and $NO_2$ would violate ambient air quality standards at several locations due to high ambient air concentrations. It is recommended that the emission reductions near the site should be enforced to improve the ambient air quality.

• Composites Research
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• v.29 no.2
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• pp.60-65
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• 2016

In this paper, finite element analysis and real time monitoring experimental work using FBG sensor were carried out for analyzing structural integrity of a Type IV hydrogen pressure vessel under impact loading condition. By using finite element analysis with the ply based modeling technique, sensor insertion points and pressure condition were suggested. Tensile test with an angle ply specimen was conducted for getting the reliability of FBG sensor insertion method. After fabricating the vessel, total five times pressurization fatigue tests were conducted (Non-impact pressurization: 1, After impact pressurization: 4). Experimental results revealed that filling cycle time was gradually increased and filling gradient was decreased when the vessel experienced impact.

• Journal of Environmental Impact Assessment
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• v.13 no.6
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• pp.295-305
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• 2004

After the Rio declaration on environment and development in 1992, developed countries are undertaking "environmentally sustainable transportation (EST)" projects. To meet the needs for EST, current transportation policies in Korea are rapidly reforming and one of its concerns is modernizing and upgrading railway freight system. Planning new railroad construction projects is increasing and subsequent environmental impact assessment (EIA) demands improvements, especially in both the EIA and decision making systems. In this paper, we discuss the present status of EIA for railroad construction projects, especially, by analyzing the EIA documents for the last six years. The EIA for railroad construction projects accounts for only 4.9% of total 918 project EIAs during 1998-2003, and the portion is gradually increasing. Major environmental concerns for EIA in railroad construction projects were geomorphological and ecological changes, protection of rare organisms, air pollution, water pollution, waste management, and noise, etc. We compared characteristics of environmental impacts of railroad construction with those of vehicle road construction, based on environmental and construction-planning indicators appeared in Environmental Impact Statements. Railroad construction usually requires longer tunnels and bridges for a given length than those for vehicle road construction. In addition, the amounts of geomorphological and ecological changes (road-cutting, embankment, devegetation, etc.) in railroad construction were generally less than 50% of those in vehicle road construction. To develop environmentally friendly railway systems, monitoring studies for environmental impacts of railroads such as habitat fragmentation and road kills, dispersal of alien plants, tunnelling effects on groundwater and vegetation, and noise impacts are highly recommended.