• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.41-46
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• 2015

In this work, pure hierarchical ZnO structure was prepared using a simple hydrothermal method, and Ag nanoparticles doped hierarchical ZnO structure was synthesized uniformly through photochemical route. The reduced graphene oxide (rGO) has been synthesized by typical Hummer's method and reduced by hydrazine. Prepared Ag/ZnO nanostructures are uniformly dispersed on the surface of rGO sheets using ultrasonication process. The synthesized samples were characterized by SEM, TEM, EDS, XRD and PL spectra. The average size of prepared ZnO microspheres was around $2{\sim}3{\mu}m$ and showed highly uniform. The average size of doped-Ag nanoparticles was 50 nm and decorated into ZnO/rGO network. The $C_2H_2$ gas sensing properties of as-prepared products were investigated using resistivity-type gas sensor. Ag/ZnO-rGO based sensors exhibited good performances for $C_2H_2$ gas in comparison with the Ag/ZnO. The $C_2H_2$ sensor based on Ag/ZnO-rGO had linear response property from 3~1000 ppm of $C_2H_2$ concentration at working temperature of $200^{\circ}C$. The response values with 100 ppm $C_2H_2$ at $200^{\circ}C$ were 22% and 78% for Ag/ZnO and Ag/ZnO-rGO, respectively. In additions, the sensor still shows high sensitivity and quick response/recovery to $C_2H_2$ under high relative humidity conditions. Moreover, the device shows excellent selectivity towards to $C_2H_2$ gas at optimal working temperature of $200^{\circ}C$.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.629-632
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• 2007

While conventional interferometric SAR (InSAR) technique is an excellent tool for displacement observation, it is only sensitive to one-dimensional deformation along the satellite's line-of-sight (LOS). Recently, a multiple aperture interferogram (MAI) technique has been developed to overcome this drawback. This method successfully extracted along-track displacements from InSAR data, based on split-beam InSAR processing, to create forward- and backward- looking interferograms, and was superior to along-track displacements derived by pixel-offset algorithm. This method is useful to measure along-track displacements. However, it does not only decrease the coherence of MAI because three co-registration and resampling procedures are required for producing MAI, but also is confined to a suitable interferometric pair of SAR images having zero Doppler centroid. In this paper, we propose an efficient and robust method to generate MAI from interferometric pair having non-zero Doppler centroid. The proposed method efficiently improves the coherence of MAI, because the co-registration of forward- and backward- single look complex (SLC) images is carried out by time shift property of Fourier transform without resampling procedure. It also successfully removes azimuth flat earth and topographic phases caused by the effect of non-zero Doppler centroid. We tested the proposed method using ERS images of the Mw 7.1 1999 California, Hector Mine Earthquake. The result shows that the proposed method improved the coherence of MAI and generalized MAI processing algorithm.

• Journal of the Korean institute of surface engineering
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• v.50 no.4
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• pp.289-295
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• 2017

Detection of $CO_2$ gas in both indoor and outdoor atmospheres is now becoming an important issue because of greenhouse effect and climate crisis. In this study, gas sensors based on $SnO_2-Cr_2O_3$ composite nanofibers were fabricated by the electrospinning method to detect $CO_2$ gas. The gas sensors showed a response to ppm level of $CO_2$ gas from room temperature to $200^{\circ}C$ while the highest response was observed at $150^{\circ}C$. The gas response is enhanced by the catalytic property of $Cr_2O_3$. Selective $CO_2$ detection is obtained through the chemical reaction of $Cr_2O_3$ to chromium carbonate. All the results suggest the $SnO_2-Cr_2O_3$ composite material is promising for the use of $CO_2$ gas sensors.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Korean Chemical Engineering Research
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• v.55 no.1
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• pp.115-120
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• 2017

In recent, it is worldwide issued that nanoscale science and technology as a solution have supported to increase the sensing performance in carbon nanotube based biosensor system. Containing material chemistry in various nanostructures has formed their high potentials for stabilizing and activating biocatalyst as a bioreceptor for medical, food contaminants, and environmental detections using electrode modification technologies. Especially, the large surface area provides the attachment of biocatalysts increasing the biocatalyst loading. Therefore, nano-scale engineering of the biocatalysts have been suggested to be the next stage advancement of biosensors. Here, we would like to study the electrical mechanism depending on the exposure methods (soaking or dropping) to the sample solution to the assembled carbon nanotubes (CNTs) on the gold electrodes of biosensor for a simple and highly sensitive detection. We performed various experiments using polar and non-polar solutions as sampling tests and identified electrical response of assembled CNTs in those solutions.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.104-107
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• 2001

The fabricated La-modified lead titanate (PLT) thin flirt without poling treatment was investigated for modulation frequency dependence of pyroelectric properties by the dynamic method. $Pb_{1-x}La_{x}Ti_{1-x/4}O_3$PLT (x=0.1) thin film having 10 mol% La content was deposited on a Pt/$TiO_{x}$/$SiO_2$/Si substrate by sol-gel method. The PLT(10) thin film exhibits a relatively excellent dielectric property. The pyroelectric coefficient (p) of the PLT(10) thin film is 6.6 x $10^{-9}$C/$\textrm{cm}^2$.K without frequency dependence. The figure of merits for the voltage responsivity and specific detectivity are 1.03${\times}$$10^{-11}$/C.cm/J and 1.46 x $10^{-9}$C.cm/J, respectively. The PLT(10) thin film has voltage responsivity ($R_{V}$) of 5.15 V/W at 8 Hz. Noise equivalent power (NEP) and specific detectivity (D＊) of the PLT(10) thin film are 9.93 x $10^{-8}$W/Hz$^{1/2}$ and 1.81 x $10^{6}$ cmHz$^{1/2}$/W at the same frequency of 100 Hz, respectively. The results means that PLT thin film having 10 mol % La content is suitable for the sensing materials of pyroelectric IR sensors.

• Applied Chemistry for Engineering
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• v.30 no.2
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• pp.186-189
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• 2019

Polypyrrole is a typical electrical conducting polymer, which has an excellent charge transport property. Cyclodextrins are a group of toxic-free and cyclic oligosaccharide molecules, capable of capturing low molecular weight chemicals. Considering these advantages, hybrid materials of polypyrrole and cyclodextrin can be used to detect hazardous compounds. Cyclodextrin molecules can accommodate toxic chemicals by the formation of host-guest complexes and generate electric signals, which are effectively delivered by polypyrrole backbone. In this study, the polypyrrole/cyclodextrin hybrid material was prepared using a facile wet method and included into a hydrogel. Subsequently, it was applied to a simple sensor system with a gold-patterned electrode for the detection of potentially hazardous material, methyl paraben. Compared with pristine polypyrrole, it was found that the polypyrrole/cyclodextrin hybrid showed an improved performance. This study can be an example of using environmentally benign conducting polymer/cyclodextrin hybrids as sensing media.

• Journal of the Korean Geosynthetics Society
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• v.22 no.1
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• pp.1-7
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• 2023

This study has utilized self-assembled monolayers technology to improve electrical property of graphene-oxide, which has been seperated graphine powder through a chemical exfoliation. Aluminum sulfate (Al₂(SO₄)₃) was applied on graphene-oxide as a reactant, and the fundamental research was carried out to apply on the self-sensing of cement-based construction structures. Electric resistance measurement result has shown that cement-composites with GO and Al-GO can be used as a conductor, electric resistance of GO and Al-GO contained composites improved by 10.2% and 15.9% respectively when compared to the standard cement-composite. Microstructure analyzation shown the formation of Al(OH)₃ gel when Al-GO was added, which is speculated to result the smooth flow of current by improving the density of cement-composite. This implies that graphene-oxide has a possibility to be utilized as smart building materials and construction structure itself rather than just a structure.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.867-878
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• 2011

Development restriction areas (greenbelt areas) of Korea were recognized in 1970 as a means to control urban sprawl and conserve the natural environment. Although there have been some achievements, for a long time many planners and residents have requested a redefining of the green belt due to individual property rights restrictions and urban management problems. In fact, a lot of the greenbelt area is being destroyed by urban development. Therefore, conservation of ecological spaces in the green belt is needed to maintain urban naturalness. In this regard, this study suggests efficient methods to manage the greenbelt through the adoption of a landscape ecological value assessment. The greenbelt of the Seoul Metropolitan Area (SMA) is represented as the case study because there has been mounting pressure to develop the area in Korea. In this study, the assessment of the landscape ecology in the greenbelt area focuses on landscape structure and function. The assessment consists of the following steps: First, patches were derived by NDVI analysis using landsat remote sensing data. Second, characteristics of the patches were quantified by analyzing the landscape structure, such as patch size and shape index. Lastly, the gravity model and least cost path analysis to assess connectivity were applied to evaluate the landscape function in the green belt areas. The assessment result showed that 48.45% of green belt area should be conserved to maintain ecological stability and function. Moreover, major ecological networks were identified near the large patches in the northern and southern areas. However, relative low ecological values were identified in the western part of the green belt area due to the lack of green spaces. Furthermore, some development plans in the green belt were also identified near the conservation area. Based on these results, the restoration needed areas to enhance ecological value in green belt were displayed. This study suggests efficient management of the greenbelt area, which is disappearing as a result of urban development. The area for conservation chosen in this study should be managed carefully in urban planning. Finally, the results of this study can be used in green belt polices and plans for the promotion of ecological naturalness and stability.