• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.426-439
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• 2018

Purpose: To continuously monitor soil and climatic properties, a data acquisition system (DAQ) was developed and tested in plum farms (Gyewol-ri and Haechang-ri, Suncheon, Korea). Methods: The DAQ consisted of a Raspberry-Pi processor, a modem, and an ADC board with multiple sensors (soil moisture content (SEN0193), soil temperature (DS18B20), climatic temperature and humidity (DHT22), and rainfall gauge (TR-525M)). In the laboratory, various tests were conducted to calibrate SEN0193 at different soil moistures, soil temperatures, depths, and bulk densities. For performance comparison of the SEN0193 sensor, two commercial moisture sensors (SMS-BTA and WT-1000B) were tested in the field. The collected field data in Raspberry-Pi were transmitted and stored on a web server database through a commercial communications wireless network. Results: In laboratory tests, it was found that the SEN0193 sensor voltage reading increased significantly with an increase in soil bulk density. A linear calibration equation was developed between voltage and soil moisture content depending on the farm soil bulk density. In field tests, the SEN0193 sensor showed linearity (R = 0.76 and 0.73) between output voltage and moisture content; however, the other two sensors showed no linearity, indicating that site-specific calibration is important for accurate sensing. In the long-term monitoring results, it was observed that the measured climate temperature was almost the same as website information. Soil temperature information was higher than the values measured by DS18B20 during spring and summer. However, the local rainfall measured using TR 525M was significantly different from the values on the website. Conclusion: Based on the test results obtained using the developed monitoring system, it is thought that the measurement of various parameters using one device would be helpful in monitoring plum growth. Field data from the local farm monitoring system can be coupled with website information from the weather station and used more efficiently.

• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• Journal of the Korean Institute of Gas
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• v.24 no.2
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• pp.44-49
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• 2020

In this paper, a measuring circuit is designed through analyzing manufacture specification of the sensor based on MOS. And the best input-output polynomial are induced that really gas sensors are used in gas safety management industrial fields. Response characteristics of a MOS gas sensor is analysed by through sensor's output voltages are measured after standard gases with six kinds of concentrations are manufactured and are injected to the sensor. A lookup table is created by relations of sensor's output voltages by injecting gases with other concentrations. Because data of the formed lookup table are equal interval, a polynomial can be induced of method of approximation function. So the 5th polynomial of input-output for a sensor is defined, coefficients are calculated by using least squares method, and the 5th polynomial is completed for representing characteristics of the sensor. If the proposed polynomial is applied to gas leak detectors, an inverse transformation of polynomial and programing of array codes are recreated. In this research, polynomial is implemented with array types that intervals of values of a lookup table are one-fifth sampled and interpolated. The performance of proposed 5th calibration equation is verified that errors are reduced than a linear expression when tests are performed by measurement of concentrations against injection of standard gases.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.3
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• pp.301-307
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• 2013

This study was evaluated high end research grade Near Infrared Reflectance Spectrophotometer (NIRS) to field grade multiple Near Infrared Reflectance Spectrophotometer (NIRS) for rapid analysis at fresh rice leaf at sight with 238 samples of fresh rice leaf during year 2012, collected Jeollabuk-do for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with 400 nm ~ 2500 nm during from year 2003 to year 2009, seven years collected fresh rice leaf database then trim and fit to field grade NIRS with 1200 nm ~ 2400 nm then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.005% differences, rapidly analysis for chemical constituents, Total nitrogen in fresh rice leaf within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless last during more than 8 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of fresh rice leaf analysis with NIRS at sight. Especially the agriculture products such as rice will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods global distance (GD) and neighbour distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1457-1468
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• 2018

The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.4
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• pp.1-10
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• 2010

In this study, two estimation equations for preparing stream data for distributed storm runoff model were developed by analyzing the nonlinear relation between upstream flow-length and stream width, and between upstream flow-length and stream bed-slope. The equations for stream cell were tested in Chungjudam watershed (6,661 $km^2$) using KIMSTORM. Six storm events occurring between 2003 and 2008 were selected for the model calibration and verification before the test of equations. The average values of the Nash-Sutcliffe model efficiency (ME), the volume conservation index (VCI), the relative error of peak runoff rate (EQp), and the difference of time to peak runoff (DTp) were 0.929, 1.035, 0.037, and -0.406 hr for the calibrated four storm events and 0.956, 0.939, 0.055, and 0.729 hr for the two verified storm events respectively. The estimation equations were tested to the storm events, and compared the flood hydrograph. The test result showed that the estimation equation of stream width reduced the peak runoff and delaying the time to peak runoff, and the estimation equation of stream bed-slope showed the opposite results.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.538-543
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• 2020

Boric acid is used as a coolant for pressurized-water reactors, and the degree of burnup is controlled by the concentration of boric acid. Therefore, accurate measurement of the concentration of boric acid is an important factor in reactor safety. An improved system was proposed for the accurate determination of boron concentration. A new boron-concentration measurement technique, called multisensitive detection, was developed to improve the measurement accuracy of boron meters. In previous studies, laboratory-scale experiments were performed based on different sensitivity detectors, confirming a 65% better accuracy than conventional single-detector boron meters. Based on these experimental results, an experimental system simulating the coolant-circulation environment in the reactor was constructed; accuracy analysis of the boron meter with a multisensitivity detector was performed at the actual coolant pressure and temperature. In this study, the boron concentration conversion equation was derived from the calibration test, and the accuracy of the boron concentration conversion equation was examined through a repeatability test. Through the experiment, it was confirmed that the accuracy was up to 87.5% higher than the conventional single-detector boron meter.

• Journal of the Mineralogical Society of Korea
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• v.29 no.4
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• pp.191-198
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• 2016

Pyromorphite($Pb_{4.85}(P_{1.02}O_4)_3Cl_{1.04}$) which belongs to the apatite group was compressed up to 33.4 GPa for its equation of state at ambient temperature. High pressure experiment was performed with symmetrical diamond anvil cell employing the angle dispersive X-ray diffraction method. Pressure was determined by ruby fluorescence calibration method. No phase transition were observed and bulk modulus was determined to be 80(7) GPa when $K{_0}^{\prime}=13(2)$. Employing the normalized pressure-normalized strain analysis, reliability check of the compressible behavior was conducted.

• Journal of Korea Water Resources Association
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• v.34 no.3
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• pp.209-216
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• 2001

Universal Soil Loss Equation(USLE) was developed for the estimation of the annual average soil loss from farm land. But, USLE has been applied in estimation of the sediment yield due to the construction activities in Korea without any calibration for last couple of years. Therefore, applicability and the limitation of the MUSLE(modified USLE), which was developed for the estimation of the sediment yield due to single rainfall event, is examined by application of MUSLE into several construction sites and comparing the estimated sediment yields with the actual ones. It is found that MUSLE could be applied in Korea as long as the concentration time, runoff volume and the peak flow rate are estimated with appropriate methods. Comparisons between the applicability of RUSLE and MUSLE are also carried out.

• Water Engineering Research
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• v.2 no.1
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• pp.49-61
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• 2001

A grid-based KIneMatic wave soil-water EROsion and deposition Model(KIMEROM) that predicts temporal variation and spatial distribution of sediment transport in a watershed was developed. This model uses ASCII-formatted map data supported from the regular gridded map of GRASS (U.S. Army CERL, 1993)-GIS(Geographic Information Systems), and generates the distributed results by ASCII-formatted map data. For hydrologic process, the kinematic wave equation and Darcy equation were used to simulated surface and subsurface flow, respectively (Kim, 1998; Kim et al., 1998). For soil erosion process, the physically-based soil erosion concept by Rose and Hairsine (1988) was used to simulate soil-water erosion and deposition. The model adopts single overland flowpath algorithm and simulates surface and subsurface water depth, and sediment concentration at each grid element for a given time increment. The model was tested to a 162.3 $\textrm{km}^2$ watershed located in the tideland reclaimed ares of South Korea. After the hydrologic calibration for two storm events in 1999, the results of sediment transport were presented for the same storm events. The results of temporal variation and spatial distribution of overland flow and sediment areas are shown using GRASS.