• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• Nutrition Research and Practice
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• v.16 no.5
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• pp.646-657
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• 2022

BACKGROUND/OBJECTIVES: The doubly labeled water (DLW) method is the gold standard for estimating total energy expenditure (TEE) and is also useful for verifying the validities of dietary evaluation tools. In this study, we compared the accuracy of total energy intakes (TEI) estimated by the 24-h diet recall method with TEE obtained using the doubly labeled water method. SUBJECTS/METHODS: This study involved 71 subjects aged 20-49 yrs. Over a 14-day period, three 24-h diet recalls per subject (2 weekdays and 1 weekend day) were used to estimate energy intakes, while TEE was measured using the DLW method. The paired t-test was used to determine the significance of differences between TEI and TEE results, and the accuracy of the 24-h recall method was determined by accuracy predictions percentage, root mean square error, and bias. RESULTS: Average study subject age was 33.4 ± 8.6 yrs. The association between TEI and TEE was positive and significant (r = 0.463, P < 0.001), and the difference between TEI (2,084.3 ± 684.2 kcal/day) and TEE (2,401.7 ± 480.3 kcal/day) was also significant (P < 0.001). In all study subjects, mean TEI was 12.0% (307.5 ± 629.3 kcal/day) less than mean TEE, and 12.2% (349.4 ± 632.5 kcal/day) less in men and 11.8% (266.7 ± 632.5 kcal/day) less in women. Rates of TEI underprediction for all study subjects, men, and women, were 60.5%, 51.4%, and 66.7%, respectively. CONCLUSIONS: This study shows that 24-h diet recall underreports energy intakes. More research is needed to corroborate our findings and evaluate the accuracy of 24-h recall with respect to additional demographics.

• Journal of Food Hygiene and Safety
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• v.24 no.3
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• pp.232-237
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• 2009

This study was conducted to develop a model for describing the effect of storage temperature (4, 10, 15, 20, 25, 30 and $35^{\circ}C$) on the growth of Escherichia coli O157 : H7 in ready-to-eat (RTE) lettuce treated with or without (control) alkaline electrolyzed water (AIEW). The growth curves were well fitted with the Gompertz equation, which was used to determine the specific growth rate (SGR) and lag time (LT) of E. coli O157 : H7 ($R^2$ = 0.994). Results showed that the obtained SGR and LT were dependent on the storage temperature. The growth rate increased with increasing temperature from 4 to $35^{\circ}C$. The square root models were used to evaluate the effect of storage temperature on the growth of E. coli O157 : H7 in lettuce samples treated without or with AIEW. The coefficient of determination ($R^2$), adjusted determination coefficient ($R^2_{Adj}$), and mean square error (MSE) were employed to validate the established models. It showed that $R^2$ and $R^_{Adj}$ were close to 1 (> 0.93), and MSE calculated from models of untreated and treated lettuce were 0.031 and 0.025, respectively. The results demonstrated that the overall predictions of the growth of E. coli O157: H7 agreed with the observed data.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.721-732
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• 2016

The accuracy and error characteristics of microwave Sea Surface Temperature (SST) measurements in the Northwest Pacific were analyzed by utilizing 162,264 collocated matchup data between GCOM-W1/AMSR2 data and oceanic in-situ temperature measurements from July 2012 to August 2016. The AMSR2 SST measurements had a Root-Mean-Square (RMS) error of about $0.63^{\circ}C$ and a bias error of about $0.05^{\circ}C$. The SST differences between AMSR2 and in-situ measurements were caused by various factors, such as wind speed, SST, distance from the coast, and the thermal front. The AMSR2 SST data showed an error due to the diurnal effect, which was much higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. In addition, the RMS error tended to be large in the winter because the emissivity of the sea surface was increased by high wind speeds and it could induce positive deviation in the SST retrieval. Low sensitivity at colder temperature and land contamination also affected an increase in the error of AMSR2 SST. An analysis of the effect of the thermal front on satellite SST error indicated that SST error increased as the magnitude of the spatial gradient of the SST increased and the distance from the front decreased. The purpose of this study was to provide a basis for further research applying microwave SST in the Northwest Pacific. In addition, the results suggested that analyzing the errors related to the environmental factors in the study area must precede any further analysis in order to obtain more accurate satellite SST measurements.

• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.130-139
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• 2011

Three modes of VIS/NIR spectroscopic measurement (interactance and two modes of transmission) were compared for their ability to estimate soluble solids content (SSC) of 'Shingo' pear non-destructively. The two transmission modes are named as full- and semi-transmission, where full-transmission stands for passing of light through abdomen of pear and semi-transmission is for transit of light mainly through flesh of pear. For comparison of the modes, prediction models developed from the collected spectroscopic data by the three modes were developed and tested for comparison of their performance. Partial least square regression (PSLR) was used to develop the models and various pre-processing methods were applied to develop models of high accuracy. The experiment was repeated three times with pears produced in different regions. The experiments resulted that selection of pre-processing is very important to attain accurate models, and multiplicative scatter correction (MSC) was selected as a pre-processor of high accuracy for the three modes of spectroscopic measurement in every experiment. Except for MSC, different group of pre-processing methods were selected for the three modes of measurement in every experiment without any tendency to the tested modes of measurement and pears of different produced region. Root-mean-square error of prediction (RMSEP) of prediction models of the three modes of measurement using prepreocessor of MSC were compared for their ability to estimate SSC. The models resulted in ranges of $0.37{\sim}0.57^{\circ}Brix$, $0.65{\sim}0.72^{\circ}Brix$, $0.39{\sim}0.51^{\circ}Brix$ for interactance, full- and semi-transmission, respectively. As shown, modes of semi-transmission and interactance resulted about the same level of prediction accuracy and were noted as modes of high performance to predict SSC.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.314-322
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• 2017

Purpose: This study was conducted to investigate the hot air drying characteristics of squash slices depending on the drying conditions (input air velocity, input air temperature, and sample thickness). Methods: The developed drying system was equipped with a controllable air blower and electric finned heater, drying chamber, and ventilation fan. Squash (summer squash called Korean zucchini) samples were cut into slices of two different thicknesses (5 and 10 mm). These were then dried at two different input air temperatures (60 and $70^{\circ}C$) and air velocities (5 and 7 m/s). Six well-known drying models were tested to describe the experimental drying data. A non-linear regression analysis was applied to determine model constants and statistical indices such as the coefficient of determination ($R^2$), reduced chi-square (${\chi}^2$), and root mean square error (RMSE). In addition, the effective moisture diffusivity ($D_{eff}$) was estimated based on the curve of ln(MR) versus drying time. Results: The results clearly showed that drying time decreased with an increase in input air temperature. Slice thickness also affected the drying time. Air velocity had a greater influence on drying time at $70^{\circ}C$ than at $60^{\circ}C$ for both thicknesses. All drying models accurately described the drying curve of squash slices regardless of slice thickness and drying conditions; the Modified Henderson and Pabis model had the best performance with the highest R2 and the lowest RMSE values. The effective moisture diffusivity ($D_{eff}$) changes, obtained from Fick's diffusion method, were between $1.67{\times}10^{-10}$ and $7.01{\times}10^{-10}m^2/s$. The moisture diffusivity was increased with an increase in input air temperature, velocity, and thickness. Conclusions: The drying time of squash slices varied depending on input temperature, velocity, and thickness of slices. The further study is necessary to figure out optimal drying condition for squash slices with retaining its original quality.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.271-280
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• 2017

This study presents the application of satellite laser ranging (SLR) to orbit determination (OD) of high-Earth-orbit (HEO) satellites. Two HEO satellites are considered: the Quasi-Zenith Satellite-1 (QZS-1), a Japanese elliptical-inclinedgeosynchronous-orbit (EIGSO) satellite, and the Compass-G1, a Chinese geostationary-orbit (GEO) satellite. One week of normal point (NP) data were collected for each satellite to perform the OD based on the batch least-square process. Five SLR tracking stations successfully obtained 374 NPs for QZS-1 in eight days, whereas only two ground tracking stations could track Compass-G1, yielding 68 NPs in ten days. Two types of station bias estimation and a station data weighting strategy were utilized for the OD of QZS-1. The post-fit root-mean-square (RMS) residuals of the two week-long arcs were 11.98 cm and 10.77 cm when estimating the biases once in an arc (MBIAS). These residuals were decreased significantly to 2.40 cm and 3.60 cm by estimating the biases every pass (PBIAS). Then, the resultant OD precision was evaluated by the orbit overlap method, yielding three-dimensional errors of 55.013 m with MBIAS and 1.962 m with PBIAS for the overlap period of six days. For the OD of Compass-G1, no station weighting strategy was applied, and only MBIAS was utilized due to the lack of NPs. The post-fit RMS residuals of OD were 8.81 cm and 12.00 cm with 49 NPs and 47 NPs, respectively, and the corresponding threedimensional orbit overlap error for four days was 160.564 m. These results indicate that the amount of SLR tracking data is critical for obtaining precise OD of HEO satellites using SLR because additional parameters, such as station bias, are available for estimation with sufficient tracking data. Furthermore, the stand-alone SLR-based orbit solution is consistently attainable for HEO satellites if a target satellite is continuously trackable for a specific period.

• Journal of the Korean Chemical Society
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• v.53 no.6
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• pp.717-726
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• 2009

Multivariate models were developed for the simultaneous spectrophotometric determination of copper (II), nickel (II) and zinc (II) in water with 1-(2-thiazolylazo)-2-naphthol as chromogenic reagent in the presence of Triton X-100. To overcome the drawback of spectral interferences, principal component regression (PCR) and partial least square (PLS) multivariate calibration approaches were applied. Performances were validated with several test sets, and their results were then compared. In general, no significant difference in analytical performance between PLS and PCR models. The root mean square error of prediction (RMSEP) using three components for $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ were 0.018, 0.010, 0.011 ppm, respectively. Figures of merit such as sensitivity, analytical sensitivity, limit of detection (LOD) were also estimated. High reliability was achieved when the proposed procedure was applied to simultaneous determination of $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ in synthetic mixture and tap water.

• Food Science and Preservation
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• v.24 no.1
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• pp.145-152
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• 2017

In this study, near infrared (NIR) spectroscopy known as a non-destructive analysis technique was applied to investigate peptide cleavage and consequent release of amino acids in soybean lumps as affected by its moisture content and incubation time during fermentation at 25 for 3 weeks. The NIR spectra of the soybean lump semi-dried and soaked in saline water showed that absorption intensity around 1,400 nm originating from hydrogen bonds of water decreased and absorption band shifted to 1,430 nm as moisture content decreased during incubation at 25 for 3 weeks. In addition, absorption around 2,050 nm which was assigned to amino groups increased as incubation time increased. NIR spectra data from 1,000 to 2,250 nm showed higher accuracy in the discriminant analysis between outside and inside parts of fermented soybean lumps than visible spectra result. NIR spectroscopy for the amino acid and moisture contents in traditional fermented soybean lumps showed relatively good accuracy with the multiple correlation coefficient ($R^2$) of 0.91 and 0.81, respectively, and root mean square error of cross validation (RMSECv) of 0.23 and 0.83%, respectively, in partial least square regression (PLSR). These results indicate that NIR spectral observations could be applicable to control the fermentation process for preparation of soybean products.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.535-544
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• 2017

UAVs (Unmanned Aerial Vehicle) are generally classified into fixed-wing and rotary-wing type, and both have very different flight characteristics each other during photographing. These can greatly effect on the quality of images and their productions. In this paper, the change of the camera rotation angle at the moment of photographing was compared and analyzed by calculating orientation angles of each image taken by both types of payload. Study materials were acquired at an altitude of 130m and 260m with fixed-wing, and at an altitude of 130m with rotary-wing UAV over an agricultural land. In addition, an accuracy comparison of boundary surveying methods between UAV photogrammetry and terrestrial cadastral surveying was conducted in two parcels of the study area. The study results are summarized as follows. The differences at rotation angles of images acquired with between two types of UAVs at the same flight height of 130m were significantly very large. On the other hand, the distance errors of parcel boundary surveying were not significant between them, but almost the same, about within ${\pm}0.075m$ in RMSE (Root Mean Square Error). The accuracy of boundary surveying with a fixed-wing UAV at 260m altitude was quite variable, $0.099{\sim}0.136m$ in RMSE. In addition, the error of area extracted from UAV-orthoimages was less than 0.2% compared with the results of the cadastral survey in the same two parcels used for the boundary surveying, In conclusion, UAV photogrammetry can be highly utilized in the field of cadastral surveying.