• Korean Journal of Soil Science and Fertilizer
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• v.39 no.2
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• pp.109-115
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• 2006

Understanding characteristics of claypan soils has long been an issue for researchers and farmers because the high-clay subsoil has a pronounced effect on grain crop productivity. The claypan restricts water infiltration and storage within the crop root zone, but these effects are not uniform within fields. Conventional techniques of identifying claypan soil characteristics require manual probing and analysis which can be quite expensive; an expense most farmers are unwilling to pay. On the other hand, farmers would be very interested if this information could be obtained with easy-to-use field sensors. Two examples of sensors that show promise for helping in claypan soil characterization are soil profile strength sensing and bulk soil apparent electrical conductivity (ECa). Little has been reported on claypan soils relating the combined information from these two sensors with grain crop yield. The objective of this research was to identify the relationships of sensed profile soil strength and soil EC with nine years of crop yield (maize and soybean) from a claypan soil field in central Missouri. A multiple-probe (five probes on 19-cm spacing) cone penetrometer was used to measure soil strength and an electromagnetic induction sensor was used to measure soil EC at 55 grid site locations within a 4-ha research field. Crop yields were obtained using a combine equipped with a yield monitoring system. Soil strength at the 15 to 45 cm soil depth were significantly correlated to crop yield and ECa. Estimated crop yields from apparent electrical conductivity and soil strength were validated with an independent data set. Using measurements from these two sensors, standard error rates for estimating yield ranged from 9 to 16%. In conclusion, these results showed that the sensed profile soil strength and soil EC could be used as a measure of the soil productivity for grain crop production.

• Membrane and Water Treatment
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• v.11 no.1
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• pp.79-85
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• 2020

A single-stage deammonification with a sequencing batch reactor (SBR) that simultaneous nitritation, anaerobic ammonia oxidation (anammox), and denitrification (SNAD) occur in one reactor has been widely applied for sidestream of wastewater treatment plant. For the stable and well-balanced SNAD, a feeding strategy of influent wastewater is one of the most important operating factors in the single-stage deammonification SBR. In this study, single-stage deammonification SBR (working volume 30L) was operated to treat a high-strength ammonium wastewater (1200 mg NH₄⁺-N/L) with different feeding strategies (single feeding and nine-step feeding) under the condition without COD. Each cycle of the step feeding involved 6 sub-cycles consisted of aerobic and anoxic periods for partial nitritation (PN) and anammox, respectively. Contrary to unstable performance in the single feeding, the step feeding showed better deammonification performance (0.565 kg-N/m³/day). Under the condition with COD, however, the nitrogen removal rate (NRR) decreased to 0.403 kg-N/m³/day when the Nine-step feeding strategies had an additional denitrification period before sub-cycles for PN and anammox. The NRR was recovered to 0.518 kg-N/m³/day by introducing an enhanced multiple-step feeding strategy. The strategy had 50 cycles consisted of feed, denitrification, PN, and anammox, instead of repeated sub-cycles for PN and anammox. The multiple-step feeding strategy without sub-cycle showed the most stable and excellent deammonification performance: high nitrogen removal efficiency (98.6%), COD removal rate (0.131 kg-COD/m³/day), and COD removal efficiency (78.8%). This seemed to be caused by that the elimination of the sub-cycles might reduce COD oxidation during aerobic condition but increase the COD utilization for denitrification period. In addition, among various sensor values, the ORP pattern appeared to be applicable to monitor and control each reaction step for deammonification in the multiple-step feeding strategy without sub-cycle. Further study to optimize the number of multiple-step feeding is still needed but these results show that the multiple-step feeding strategy can contribute to a well-balanced SNAD for deammonification when treating high-strength ammonium wastewater with COD in the single-stage deammonification SBR.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.145-157
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• 2017

Currently, the height of ships that can pass under Busan Harbor Bridge is limited to 60m or shorter, so that large-sized ships of 60m or taller cannot use Busan Harbor international passenger terminal. Accordingly, this study has developed a service which measures continuously the change of bridge height by water level changes and provides such in real-time for safe bridge passage of large-sized ships of 60m or taller. The measurement system comprised of high-precision laser distance measurement device, GPS sensor, optical module, and damping structure is used to measure the bridge height change according to tide level changes, and the measured information is provided in real-time through cloud-based mobile app. Also, in order to secure objective bridge height data for changes to height limits and navigation supports, the observation data was analyzed and forecast model was drawn. As a result, it became an objective evidence to revise the passage height rules of the Busan Port Bridge from 60 meters to 63 meters.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.17-24
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• 2020

This study examined the spectral information and reflectance of cracks of an embankment with drone-based hyperspectral imagery for crack detection. A Nano-Hyperspec mounted on a drone was used as a sensor, and hyperspectral videos of different intensities of illumination of the cracks on the embankment located in the downstream of Andong-Dam were obtained. An analysis of the data value of the illumination and peak data-value, the coefficients of determination were calculated to be 0.9864 of the uncracked areas and 0.9851 of the cracked area. The reflectance of each area showed a similar value and pattern, regardless of the intensity of illumination. This result may have occurred because the reference values of the white reference as the calculation criteria of reflectance varied according to the intensity of illumination. The reflectance at the cracked area was 5.65% lower in visible light and 4.58% lower in near-infrared light than that at the uncracked area. The detection of cracks may offer more precise results in further studies when the gimbal direction and camera angles of the drone are calibrated. Because hyperspectral imagery enables the detection of crack depths and types of clay minerals, which are difficult to identify in general RGB imagery, it can serve as a preemptive measure for evaluating the embankment stability.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.15-26
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• 2003

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This paper describes an alternative approach which uses the least mean square (LMS) method and expectation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximization (SAGE) algorithm In conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of Plant Biotechnology
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• v.43 no.1
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• pp.21-29
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• 2016

Remote Sensing (RS) is a technique to obtain necessary information in a non-contact and non-destructive method by using various sensors on the surface, water or atmospheric phenomena. These techniques combine elements such as sensors, and platform and information communication technology (ICT) for mounting the sensor. ICT has contributed significantly to the success of smart agriculture through quantification and measurement of environmental factors and information such as weather, crop and soil management to distribution and consumption stage, as well as the production stage by the cloud computer. Remote sensing techniques, including non-destructive non-contact bioimaging (remote imaging) is required to measure the plant function. In addition, bioimaging study in plant science is performed at the gene, cellular and individual plant level. Recently, bioimaging technology is considered the latest phenomics that identifies the relationship between the genotype and environment for distinguishing phenotypes. In this review, trends in remote sensing in plants, plants diagnostics and response to environment and status of plants phonemics research were presented.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.41-48
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• 2009

Natural magnetic fields are attenuated by electrically conductive water. For that reason, marine magnetotelluric surveys have collected data at long periods (1000-100 000 s). The mantle structure has been the main target of seafloor magnetotelluric measurements. To ascertain crustal structure, however, electromagnetic data at shorter periods are important, e.g. in investigations of megathrust earthquake zones, or in natural resource surveys. To investigate of the former, for example, electromagnetic data for periods of less than 1000 s are necessary. Because no suitable ocean bottom electromagnetometer (OBEM) has been available, we have developed a small OBEM and ocean bottom electrometer (OBE) system with a high sample rate, which has an arm-folding mechanism to facilitate assembly and recovering operations. For magnetic observation, we used a fluxgate sensor. Field observations were undertaken to evaluate the field performance of our instruments. All instruments were recovered and their electromagnetic data were obtained. Results of the first experiment show that our system functioned well throughout operations and observations. Results of other field experiments off Tottori support the claim that the electromagnetic data obtained using the new OBEM and OBE system are of sufficient quality for the survey target. These results suggest that this device removes all instrumental obstacles to measurement of electromagnetic fields on the seafloor.

• Korean Journal of Food Science and Technology
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• v.32 no.1
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• pp.9-16
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• 2000

Aroma of various extracts of Agastache rugosa O. Kuntze was analyzed by electronic nose with 32 conducting polymer sensor arrays. The 57 extracts were prepared by extraction solvents (hot water, ethanol and NaCl solution), extraction temperatures $(100,\;80\;and\;60^{\circ}C)$, solvent mixture ratios of solvent (10 times 35 times) and parts of Agastache rugosa O. Kuntze(flower, leaf and stem). Aroma pattern of Agastache rugosa O. Kuntze extracts showed big difference in normalized pattern and odor intensity with extraction temperatures and parts, but showed no difference with extraction solvents. Especially in the case of ethanol extracts, because odor of ethanol itself was very strong, difference in aroma of extracts with extraction temperatures and parts did not show through the electronic nose. The organoleptic characteristics such as mint odor, grassy odor, mint taste, medicinal herb taste and sweetness for Agastache rugosa O. Kuntze extracts were determined by the profile test and the result of sensory evaluation by quantitative descriptive analysis was explained to QDA diagram. In correlation with the result of aroma analysis by electronic nose and the sensory evaluation, difference in aroma pattern among the extracts concretely brought to light definite characteristics such as mint odor and mint taste.

• Journal of the Korean earth science society
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• v.30 no.2
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• pp.234-246
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• 2009

Characteristics of speckle errors of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-${\alpha}$ concentration were analyzed, and its causes were investigated by using SeaWiFS data in the East Sea from September 1997 to December 2007. The speckles with anomalously high concentrations were randomly distributed and showed remarkably high bias of greater than $10mg/m^3$, compared with their neighboring pixels. The speckles tended to appear frequently in winter, which might be related to cloud distribution. Ten-year averaged cloudiness of winter was much higher over the southeastern part, with frequent speckles, than the northwestern part of the East Sea. Statistical analysis results showed that the number of the speckles was increased as cloudiness increased. Normalized water-leaving radiance of the speckle pixel was considerably low at the short wavelengths (443, 490, and 510 nm), whereas the radiance at 555 nm band was normal. These low measurements produced extraordinarily high concentration from the chlorophyll-${\alpha}$ estimation formula. This study presented the speckle errors of SeaWiFS chlorophyll-${\alpha}$ concentration in the East Sea and suggested that more reliable chlorophyll-${\alpha}$ data based on appropriate ocean color remote sensing techniques should be used for the oceanic application researches.