• Journal of Biosystems Engineering
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• v.30 no.6 s.113
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• pp.333-339
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• 2005

The pesticide is raising public interest in the world, because it causes damage to an environmental pollution and the human health remaining agricultural products and an ecosystem, in spite of the advantages. Particularly, each country restricts the residual pesticide and induces observance about the safety and usage standard so that they can control the amount of pesticide used and defend the safety of agricultural products. The habitual practice for the analysis of the residual pesticide depends on GC (gas chromatography), HPLC (high performance liquid chromatography) and GC/MS (gas chromatography/mass spectroscopy), which triturate the fixed quantity of samples, abstract and purify as a suitable organic solvent. These methods have the highly efficient in aspects of sensitivity and accuracy. On the other hand, they need the high cost, time consuming, much effort, expensive equipment and the skillful management. Carbofuran is highly toxic by inhalation and ingestion and moderately toxic by dermal absorption. As with other carbamate compounds, it is metabolized in the liver and eventually excreted in the urine. The half-life of carbofuran on crops is about 4 days when applied to roots, and longer than 4 days if applied to the leaves. This research was conducted to develop immunoassay for detecting carbofuran residue quickly on the basis of surface plasmon resonance and to evaluate the measurement sensitivity. Gold chip used was CM5 spreaded dextran on the surface. An applied antibody to Immunoassay was GST (glutathione-s-transferase). The association and the dissociation time were 176 second and 215 second between GST and carbofuran. The total analysis time using surface plasmon resonance was 13 minutes including regeneration time, on the other hand HPLC and GC/MS was 2 hours usually. The minimum detection limit of a permissible amount for carbofuran in the country is 0.1 ppm. The immunoassay method using surface plasmon resonance was 0.002 ppm.

• Bulletin of the Korean Chemical Society
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• v.25 no.8
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• pp.1195-1201
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• 2004

Tyrosinase was covalently immobilized on platinum electrode according to the method we developed for laccase (Bull. Korean Chem. Soc. 2002, 23(7), 385) and p-chlorophenol, p-cresol, and phenol could be detected with sensitivities of 334, 139 and 122 nA/ ${\mu}M$ and the detection limits of 1.0, 2.0, and 2.5 ${\mu}M$, respectively. The response time ($t_{90\%}$) is 3 seconds for p-chlorophenol, and 5 seconds for p-cresol and phenol. The optimal pHs of the sensor are in the range of 5.0- 6.0. This sensor can tolerate at least 500 times repeated injections of p-chlorophenol with retaining 80% of initial activity. In case of tyrosinase and laccase co immobilized platinum electrode, the sensitivities are 560 nA/ ${\mu}M$ for p-phenylenediamine (PPD) and 195 nA/ ${\mu}M$ for p-chlorophenol, respectively. The sensitivity of the bi-enzyme sensor for PPD increases 70% compared to that of only laccase immobilized one, but the sensitivity for p-chlorophenol decreases 40% compared to that of only tyrosinase immobilized one. The sensitivity increase for the bi-enzyme sensor for PPD can be ascribed to the additional catalytic function of the co-immobilized tyrosinase. The sensitivity decrease for p-chlorophenol can be explained by the “blocking effect” of the co-immobilized laccase, which hinders the mass transport through the immobilized layer. If PPD was detected with the electrode that had been used for p-chlorophenol, the sensitivity decreased 20% compared to that of the electrode that had been used only for PPD. Similarly, if p-chlorophenol was detected with PPD detected electrode, the sensitivity also decreased 20%. The substrate-induced conformation changes of the enzymes in a confined layer may be responsible for the phenomena.

• Composites Research
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• v.24 no.6
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• pp.49-55
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• 2011

The use of advanced composite materials in main structures of military and civil aircraft has been increased rapidly because of their considerable metals in high specific strength and stiffness. However, the mechanical properties of composite materials may severely degrade in the presence of damage. Especially, the high-velocity impact such as a hailstorm, and a small piece of tire or stone during high taxing, can cause considerable damage to the structures and sub-system in spite of a very small mass. However, it is not easy to detect the damage in composite plates using a single sensor or any conventional methods. In this paper, the PVDF sensors and AE sensors were used for monitoring high-velocity impact damage initiation and propagation in composite laminates. The WT(wavelet transform) is used to decompose the sensor signals. In the PVDF sensor and AE sensor signal analysis, amounts of high-frequency signals are increased when the impact energy is increased. PVDF sensor and AE sensor signal appeared similar results. This study shows how various sensing techniques can be used to characterize high-velocity impact damage of advanced composite laminates.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.4
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• pp.469-477
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• 2015

In this study, the characteristics of main wind direction, vertical temperature and wind speed profile near the Moseulpo airfield for HALE UAV(High Altitude Long Endurance Unmaned Aerial Vehicle) is investigated. The results are summarized as follows, main wind direction is governed by air mass according to season and local wind such as land-sea breeze. The directions of landing and take-off of HALE UAV will be selected as the south-east direction in June ~ August, north-west direction in October ~ March, and south-east direction at daytime in April ~ May, September. Annual variation of temperature at 100 hPa showed that temperature in summer season is lower than winter season. On the other hands, wind speed at 250 hPa in winter season is higher than summer season. The threshold values of temperature and wind speed for HALE UAV flight are $-75^{\circ}C$ and $90ms^{-1}$, which were determined by 5 % frequency value($1.96{\sigma}$), respectively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.817-819
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• 2003

Land degradation is a crucial issue in mountainous areas and is manifested in a variety of processes. For its assessment, application of existing models is not straightforward. In addition, data availability might be a problem. In this paper, a procedure for land degradation assessment is described, which follows a four-step approach: (1) detection, inventory and mapping of land degradation features, (2) assessing the magnitude of soil loss, (3) study of causal factors, and (4) hazard assessment by applying decision trees. This approach is applied to a case study in the Middle Mountain region of Nepal. The study shows that individual mass movement features such as debris slides and slumps can be easily mapped by photo interpretation techniques. Application of soil loss estimation models helps get insight on the magnitude of soil losses. In the study area soil losses are higher in rainfed crops on sloping terraces (highest soil loss is 32 tons/ha/yr) and minimal under dense forest and in irrigated rice fields (less than 1 ton/ha/yr). However there is high frequency of slope failures in the form of slumps in the rice fields. Debris slides are more common on south-facing slopes under rainfed agriculture or in degraded forest. Field evidences and analysis of causal factors for land degradation helps in building decision trees, the use of which for modelling land degradation has the advantage that attributes can be ranked and tested according to their importance. In addition, decision trees are simple to construct, easy to implement and very flexible in adaptations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4087-4094
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• 2010

The sensor data which is measured by Quadruped robot is utilized to recognize the physical environment or other information and to control the posture and walking of robot system. In order to control the robot precisely, high accuracy of sensor data is required, most of these sensors however, belongs to expensive and low-durable products. Moreover, these are exposed excessive load operation in a field condition if it is applied to field robot system. This issue becomes more serious one when the robot system is manufactured as a mass product. As in this context, this study suggests a virtual sensor technology to alternate or assist the main sensor system. This scheme is realized by using back-propagation algorithm of neural network theory, and the quality of estimated sensor data could be improved through the algorithmic and hardware based treatments. This study performs the various trial to identify the effective parameters which effect to the quality and reliability of estimated sensor data and tries to show the possibility of proposed methodology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.151-162
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• 2022

Prefab members have attracted attention because they can be mass-produced in factories through smart construction technology. For prefab prestressed concrete girders, it is important to manage the shapes of the girders properly from production to the pre-installation stage for consistency with the prefab floor plate during the erection process. This paper presents a camber reconstruction method using collocated strain measurements from the top and bottom of the prefab girder. In particular, the camber reconstruction method is applied to measured strain data in which the time-dependent behavior of concrete is considered after the introduction of prestress. Through Monte Carlo numerical simulations, the statistical accuracy of the reconstructed camber for a limited number of sensors, measurement errors, and nonlinear time-dependent behaviors are analyzed and validated.

• Journal of Astronomy and Space Sciences
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• v.41 no.1
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• pp.1-15
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• 2024

The Korean heliospheric community, led by the Korea Astronomy and Space Science Institute (KASI), is currently assessing the viability of deploying a spacecraft at the Sun-Earth Lagrange Point L4 in collaboration with National Aeronautics and Space Administration (NASA). The aim of this mission is to utilize a combination of remote sensing and in situ instruments for comprehensive observations, complementing the capabilities of the L1 and L5 observatories. The paper outlines longterm scientific objectives, underscoring the significance of multi-point in-situ observations to better understand critical heliospheric phenomena. These include coronal mass ejections, magnetic flux ropes, heliospheric current sheets, kinetic waves and instabilities, suprathermal electrons and solar energetic particle events, as well as remote detection of solar radiation phenomena. Furthermore, the mission's significance in advancing space weather prediction and space radiation exposure assessment models through the integration of L4 observations is discussed. This article is concluded with an emphasis on the potential of L4 observations to propel advancements in heliospheric science.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.481-491
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• 2014

Blue-ice area is a glacial ice field in ice sheet, ice shelf and glaciers where snow ablation and sublimation is larger than snowfall. As the blue-ice area has large influences on the meteorite concentration mechanism and ice mass balance, it is required to quantify the concentration of blue-ice. We analyzed spectral reflectance characteristics of blue-ice, snow and cloud by using MODIS images obtained over blue-ice areas in McMurdo Dry Valleys, East Antarctica, from 2007 to 2012. We then developed Normalized Difference Blue-ice Index (NDBI) algorithm which quantifies the concentration of blue-ice. Snow and cloud have a high reflectance in visible and near-infrared (NIR) bands. Reflectance of blue-ice is high in blue band, while that lowers in the NIR band. NDBI is calculated by dividing the difference of reflectance in the blue and NIR bands by the sum of reflectances in the two bands so that NDBI = (Blue-NIR)/(Blue + NIR). NDBI calculated from the MODIS images showed that the blue-ice areas have values ranging from 0.2 to 0.5, depending on the exposure and concentration of blue-ice. It is obviously different from that of snow and cloud that has values less than 0.2 or rocks with negative values. The change of NDBI values in the blue-ice area has higher correlation with snow depth ($R^2=0.699$) than wind speed ($R^2=0.012$) or air temperature ($R^2=0.278$), all measured at a meteorological station installed in McMurdo Dry Valleys. As the snow depth increased, the NDBI value decreased, which suggests that snow depth can be estimated from NDBI values over blue-ice areas. The NDBI algorithm developed in this study will be useful for various polar research fields such as meteorite exploration, analysis of ice mass balance as well as the snow depth estimation.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.551-558
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• 2008

It is well known that the protein content of rice grain is an indicator of taste of cooked rice in the countries where people as the staple food. Ground-based optical sensing over the crop canopy would provide information not only on the mass of plant body which reflects the light, but also on the crop nitrogen content which is closely related to the greenness of plant leaves. The vegetation index has been related to crop variables such as biomass, leaf nitrogen, plant cover, and chlorophyll in cereals. The objective of this study was to investigate the correlation between GNDVI and NDVI values, and grain protein content at different dates and to estimate the grain protein content using G(NDVI) values. We measured Green normalized difference vegetation index [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$] and [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$] by using two different active sensors. The study was conducted during the rice growing season for three years from 2005 through 2007 at the experimental plots of National Institute of Agricultural Science and Technology. The experiments were carried out by randomized complete block design with the application of four levels of nitrogen fertilizers(0, 70, 100, 130kg N/ha) and the same amount of phosphorous and potassium content of the fertilizers. After heading stage, relationships between GNDVI of rice canopy and grain protein content showed the highly positive correlation at different dates for three years. GNDVI values showed higher correlation coefficients than that of NDVI during growing season in 2005-07. The correlation between GNDVI values at different dates and grain protein contents was highly correlated at early July. We attempted to estimate the grain protein content at harvesting stage using GNDVI values from early July for three years. The determination coefficients of the linear model by GNDVI values were 0.9l and the measured and estimated grain protein content at harvesting stage using GNDVI values highly correlated($R^2=0.96^{***}$). Results from this study show that GNDVI appeared very effective to estimate leaf nitrogen and grain protein content of rice canopy.