• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.2
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• pp.189-195
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• 2003

The objective of this study is to improve the optical sensitivity of laser fluorescence for detection of incipient enamel caries. An incipient carious lesion was formed in various stages by placing an enamel specimen of a bovine tooth in STPP demineralization solution. After measuring the optical density of the lesion surface by laser fluorescence induced by argon laser and various alter of yellow(500-520nm), amber(520-540nm), orange(540-560nm), and red(560-580nm), the specimen was cut vertically to measure the depth of the lesion using a polarizing microscope. SAS statistical program was used to analyze the relationship between the optical density of the lesion suface and the depth of the lesion. The results were as follows: 1. The optical density of early carious lesion, measured by laser fluorescence with amber and orange filter, and lesion depth observed by polarizing microscope, were increased as demineralization time increased. 2. The correlation coefficient between optical density of the lesion surface and the histological depth of the lesion was the highest in orange filter(r=0.49), followed by amber(r=0.32), yellow(r=0.13) and red(0.01). 3. Regression analysis showed that the most linear relationship between the optical density and the lesion depth was existed in orange filter group. In regard above results, laser fluorescence could be considered to be reliable for optical diagnosis of dental caries.

• Korean Journal of Construction Engineering and Management
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• v.1 no.1 s.1
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• pp.87-94
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• 2000

Crack sealing, a routine and necessary part of pavement maintenance, is a dangerous, costly, and labor-intensive operation. Within the North America, about ${\$}200$ million is spent annually on crack sealing, with the Texas Department of Transportation (TxDOT) spending about ${\$}7$ million annually (labor alone accounts for over 50 percent of these costs). Prompted by concerns of safety and cost, the University of Texas at Austin, in cooperation with TxDOT and the Federal Highway Administration (FHWA) has developed a unique computer-guided Automated Road Maintenance Machine (ARMM) for pavement crack sealing. In 1999, successful field tests have been undertaken in 8 States around the U.S. This paper first describes significance of the automated crack sealing and technical advances in automated crack sealers including the ARMM, developed in the U.S. It then discusses the ARMM's field implementation and performance evaluation results, and improvements and modifications suggested through the technology evaluation during the field trials. Current research efforts and future work plans in its further development are also presented in this paper.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1709-1718
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• 2021

The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Journal of the Korean earth science society
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• v.22 no.3
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• pp.186-194
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• 2001

The operational meso-scale short range NWP system was developed for Cheju Regional Meteorological Office located at Cheju island, Korea. The Central Meteorological Service Center, KMA has reported the information on numerical weather prediction every 12 hours. But this information is not enough to determine the detail forecast for the regional meteorological office because the terrain of the Korean peninsula is very complex and the resolution of the numerical model provided by KMA headquarter is too coarse to resolve the local severe weather system such as heavy rainfall. LAPS and MM5 models were chosen for three-dimentional data assimilation and numerical weather prediction tools respectively. LAPS was designed to provide the initial data to all regional numerical prediction models including MM5. Synoptic observational data from GTS, satellite brightness temperature data from GMS-5 and the composite reflectivity data from 5 radar sites were used in the LAPS data assimilation for producing the initial data. MM5 was performed on PC-cluster based on 16 pentium CPUs which was one of the cheapest distributed parallel computer in these days. We named this system as Halla Short Range Prediction System (HSRPS). HSRPS was verified by heavy rainfall case in July 9, 1999, it showed that HSRPS well resolved local severe weather which was not simulated by 30 km MM5/KMA. Especially, the structure of rainfall amount was very close to the corresponding observation. HSRPS will be operating every 6 hours in the Cheju Regional Meteorological Office from April 2000.

• Korean Journal of Environmental Agriculture
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• v.31 no.2
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• pp.170-174
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• 2012

BACKGROUND: Inappropriate discharge of wastewaters and industrial effluents are becoming detrimental to the aquatic environment. The presence of toxic substances on wastewaters can be detected by physicochemical and biological methods. However, physicochemical methods do not give any information about biological toxicity. Therefore, in this study we tried to detect the presence of toxic substance on waters using sulfur-oxidizing bacteria (SOB) as a bioassay. MATERIALS AND RESULTS: The SOB biosensor was first stabilized using synthetic stream water and operated in both continuous and semi-continuous mode. When the SOB biosensor was operated in continuous mode, the effluent electrical conductivity (EC) stabilized at~1.72 dS/m. While in the case of semi-continuous, the EC stabilized at~0.6 dS/m. The SOB system was also operated at different reaction times to ascertain the shortest reaction time for monitoring the toxicity. Finally, the SOB biosensor was fed with nitrite as toxic substance. When 5 mg/L of nitrite was added to the SOB system, the EC decreased immediately. However, the EC recovered after few cycle. CONCLUSION: This study shows that the SOB biosensor can be used as warning system to protect aquatic environment from hazardous materials. Although SOB biosensor can not give specific information about the toxic substances, it can assess whether the water is toxic or not.

• Geophysics and Geophysical Exploration
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• v.9 no.2
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• pp.163-170
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• 2006

The shortage of proven hydrocarbon reserves has resulted in exploration progressing from the offshore into progressively deeper water of the continental shelf. Despite the success of seismic acquisition at ever greater depths, there are marine geological terrenes in which the interpretation of seismic data is difficult, such regions dominated by scattering or high reflectivity that is characteristic of carbonate reefs, volcanic cover and submarine permafrost. A marine controlled-source electromagnetic (CSEM) method has recently been applied to the oil and gas exploration thanks to its high-resistivity characteristics of the hydrocarbon. In particular, this method produces better results in terms of sensitivity under the deep water environment rather than the shallow water. Only in the last five years has the relevance of CSEM been recognized by oil companies who now use it to help them make exploration drilling decisions. Initial results are most promising and several contractors now offer magnetotelluric and CSEM services.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1055-1066
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• 2018

Vegetation indices on the basis of optical characteristics of vegetation can represent various conditions such as canopy biomass and physiological activity. Those have been mostly developed with the large-scaled applications of multi-band optical sensors on-board satellites. However, the sensitivity of vegetation indices for detecting vegetation features will be different depending on the spatial scales. Therefore, in this study, the investigation of photochemical reflectance index (PRI), known as one of useful vegetation indices for detecting photosynthetic ability and vegetation stress, under the three spatial scales was conducted using multi-spectral camera installed in unmanned aerial vehicle (UAV),field spectrometer, and leaf reflectometer. In the leaf scale, diurnal PRI had minimum values at different local-time according to the compass direction of leaf face. It meant that each leaf in some moment had the different degree of light use efficiency (LUE). In early growth stage of crop, $PRI_{leaf}$ was higher than $PRI_{stands}$ and $PRI_{canopy}$ because the leaf scale is completely not governed by the vegetation cover fraction.In the stands and canopy scales, PRI showed a large spatial variability unlike normalized difference vegetation index (NDVI). However, the bias for the relationship between $PRI_{stands}$ and $PRI_{canopy}$ is lower than that in $NDVI_{stands}$ and $NDVI_{canopy}$. Our results will help to understand and utilize PRIs observed at different spatial scales.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.138-149
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• 2023

In geoscience and engineering the geological characteristics of sediment strata is crucial and possible if reliable borehole logging and seismic data are available. To investigate the characteristics of the shallow strata in the Korea Strait, laboratory sonic logs were obtained from deep borehole data and seismic section. In this study, we integrated and analyzed the sonic log data obtained from the drilling core (down to a depth of 200 m below the seabed) and multichannel seismic section. The correlation value was increased from 15% to 45% through time-depth conversion. An initial model of P-wave impedance was set, and the results were compared by performing model-based, band-limited, and sparse-spike inversions. The derived P-impedance distributions exhibited differences between sediment-dominant and unconsolidated layers. The P-impedance inversion process can be used as a framework for an integrated analysis of additional core logs and seismic data in the future. Furthermore, the derived P-impedance can be used to detect shallow gas-saturated regions or faults in the shallow sediment. As domestic deep drilling is being performed continuously for identifying the characteristics of carbon dioxide storage candidates and evaluating resources, the applicability of the integrated inversion will increase in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.