• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.11-19
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• 2016

Two representative residual static methods of traveltime decomposition and stack-power maximization are discussed in terms of application to land seismic data. For the model data with synthetic shot/receiver statics (time shift) applied and random noises added, continuities of reflection event are much improved by stack-power maximization method, resulting the derived time-shifts approximately equal to the synthetic statics. Optimal parameters (maximum allowable shift, correlation window, iteration number) for residual statics are effectively chosen with diagnostic displays of CSP (common shot point) stack and CRP (common receiver point) stack as well as CMP gather. In addition to removal of long-wavelength time shift by refraction statics, prior to residual statics, processing steps of f-k filter, predictive deconvolution and time variant spectral whitening are employed to attenuate noises and thereby to minimize the error during the correlation process. The reflectors including horizontal layer of reservoir are more clearly shown in the variable-density section through repicking the velocities after residual statics and inverse NMO correction.

• Toxicological Research
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• v.30 no.1
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• pp.7-11
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• 2014

Malondialdehyde (MDA), used as an oxidative stress marker, is commonly assayed by measuring the thiobarbituric acid reactive substances (TBARS) using HPLC, as an indicator of the MDA concentration. Since the HPLC method, though highly specific, is time-consuming and expensive, usually it is not suitable for the rapid test in large-scale environmental epidemiologic surveys. The purpose of this study is to develop a simple and rapid method for estimating TBARS levels by using a multiple regression equation that includes TBARS levels measured with a microplate reader as an independent variable. Twelve hour urine samples were obtained from 715 subjects. The concentration of TBARS was measured at three different wavelengths (fluorescence: ${\lambda}-_{ex}$ 530 nm and ${\lambda}-_{em}$ 550 nm; ${\lambda}-_{ex}$ 515 nm and ${\lambda}-_{em}$ 553 nm; and absorbance: 532 nm) using microplate reader as well as HPLC. 500 samples were used to develop a regression equation, and the remaining 215 samples were used to evaluate the validity of the regression analysis. The induced multiple regression equation is as follows: TBARS level (${\mu}M$) = -0.282 + 1.830 ${\times}$ (TBARS level measured with a microplate reader at the fluorescence wavelengths ${\lambda}-_{ex}$ 530 nm and ${\lambda}-_{em}$ 550 nm, ${\mu}M$) -0.685 ${\times}$ (TBARS level measured with a microplate reader at the fluorescence wavelengths ${\lambda}-_{ex}$ 515 nm and ${\lambda}-_{em}$ 553 nm, ${\mu}M$) + 0.035 ${\times}$ (TBARS level measured with a microplate reader at the absorbance wavelength 532 nm, ${\mu}M$). The estimated TBARS levels showed a better correlation with, and are closer to, the corresponding TBARS levels measured by HPLC compared to the values obtained by the microplate method. The TBARS estimation method reported here is simple and rapid, and that is generally in concordance with HPLC measurements. This method might be a useful tool for monitoring of urinary TBARS level in environmental epidemiologic surveys with large sample sizes.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.116-121
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• 2017

In this paper, a Raman spectrometer is designed to detect chemicals contaminating the ground. The system is based on Raman spectroscopy, which is spectral analysis of scattered light from chemicals, induced by a laser. The system consists of a transmitting-optics module with a laser to induce Raman-scattered light from the sample, a receiving-optics module to collect the scattered light, and a spectrograph to separate the collected light into a wavelength spectrum. The telescope, a part of the receiving-optics module, is designed to produce a focal spot in the same position for variable measurement distances using the code V simulator, considering the distance change between the system and the road. The Raman spectra of 12 chemicals on a glass surface and on a concrete sample were measured. Intensity differences between the Raman spectra acquired on a glass surface and on a concrete sample were observed, but the characteristics of the spectra according to the chemicals on them were similar. Additionally, the Raman spectrum of PTFE (polytetrafluoroethylene) was measured at various distances. The measured and simulated optical throughputs were similar. In conclusion, it is confirmed that with this system the Raman spectrum can be measured, irrespective of the distance change.

• Economic and Environmental Geology
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• v.57 no.4
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• pp.353-362
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• 2024

This study examined the spectral characteristics of sediments according to moisture content using an unmanned aerial vehicle (UAV)-based hyperspectral sensor and evaluated the efficiency of moisture content detection at different flight altitudes. For this purpose, hyperspectral images in the 400-1000nm wavelength range were acquired and analyzed at altitudes of 40m and 80m for sediment samples with various moisture contents. The reflectance of the sediments generally showed a decreasing trend as the moisture content increased. Correlation analysis between moisture content and reflectance showed a strong negative correlation (r < -0.8) across the entire 400-900nm range. The moisture content detection model constructed using the Random Forest technique showed detection accuracies of RMSE 2.6%, R² 0.92 at 40m altitude and RMSE 2.2%, R² 0.95 at 80m altitude, confirming that the difference in accuracy between altitudes was minimal. Variable importance analysis revealed that the 600-700nm band played a crucial role in moisture content detection. This study is expected to be utilized in efficient sediment moisture management and natural disaster prediction in the field of environmental monitoring in the future.

• Korean Journal of Food Science and Technology
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• v.40 no.6
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• pp.603-610
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• 2008

The principal objective of current study was to evaluate the potential of near infrared reflectance spectroscopy (NIRS) as a non-destructive method for the prediction of the amylose and protein contents of un-hulled and brown rice in broad-based calibration models. The average amylose and protein content of 75 rice accessions were 20.3% and 7.1%, respectively. Additionally, the range of amylose and protein content were 16.6-24.5% and 3.8-9.3%, respectively. In total, 79 rice germplasms representing a wide range of chemical characteristics, variable physical properties, and origins were scanned via NIRS for calibration and validation equations. The un-hulled and brown rice samples evidenced distinctly different patterns in a wavelength range from 1,440 nm to 2,400 nm in the original NIR spectra. The optimal performance calibration model could be obtained by MPLS (modified partial least squares) using the first derivative method (1:4:4:1) for un-hulled rice and the second derivative method (2:4:4:1) for brown rice. The correlation coefficients $(r^2)$ and standard error of calibration (SEC) of protein and amylose contents for the un-hulled rice were 0.86, 2.48, and 0.84, 1.13, respectively. The $r^2$ and SEC of protein and amylose content for brown rice were 0.95, 1.09 and 0.94, 0.42, respectively. The results of this study suggest that the NIRS technique could be utilized as a routine procedure for the quantification of protein and amylose contents in large accessions of un-hulled rice germplasms.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.353-365
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• 1998

Light absorption coefficient per unit mass of particles, i.e., specific absorption coefficient, is important as one of the main parameters in developing algorithms for ocean color remote sensing. Specific absorption coefficient of chlorophyll ($a^*_{ph}$) and suspended sediment ($a^*_{ss}$) were analyzed with a spectrophotometer using the "wet filter technique" and "Kishino method" for the seawater collected in the Yellow and Mediterranean Sea. An improved data-recovery method for the filter technique was also developed using spectrum slopes. This method recovered the baselines of spectrum that were often altered in the original methods. High $a^*_{ph}({lambda})$ values in the oligotrophic Mediterranean Sea and low values in the Yellow Sea were observed, ranging 0.01 to 0.12 $m^2$/mg at the chlorophyll maximum absorption wavelength of 440 nm. The empirical relationship between $a^*_{ph}$(440nm) and chlorophyll concentrations () was found to fit a power function ($a^*_{ph}$=0.039 $^{-0.369}$), which was similar to Bricaud et al. (1995). Absorption specific coefficients for suspended sediment ($a^*_{ss}$) did not show any relationship with concentrations of suspended sediment. However, an average value of $a^*_{ss}$ ranging 0.005 - 0.08 $m^2$/g at 440nm, was comparable to the specific absorption coefficient of soil (loess) measured by Ahn (1990). The morepronounced variability of $a^*_{ss}$ than $a^*_{ph}$ was determined from the variable mixing ratio values between particulate organic matter and mineral. It can also be explained by a wide size-distribution range for SS which were determined by their specific gravity, bottom state, depth and agitation of water mass by wind in the sea surface.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.