• Journal of Environmental Science International
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• v.18 no.12
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• pp.1369-1381
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• 2009

The simultaneous determination of residual pesticides was developed using a gas chromatography. In this study, a simple and reliable methodology was improved to detect 175 kinds of residual pesticides by a liquid-liquid extraction procedure, followed by chromatographic analysis by gas chromatography. The 175 kinds of residual pesticides was classified into 4 groups according to the chemical structure, column type, resolution and sensitivity. The soybean sample selected for recovery experiment was not detected any pesticides. The recovery rates were ranged from 70.6% to 119.7% in most pesticides. The relative standard deviation (RSD 0.3~5.6%) was lower than 5.6% in all cases. The limits of detection (LOD) was lower than the maximum residue levels established by Korean legislations. The method has been successfully applied to the analysis of approximately 130 real samples.

• Bulletin of the Korean Chemical Society
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• v.24 no.11
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• pp.1571-1574
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• 2003

This paper describes an inductively coupled plasma emission spectrometric method for the analysis of Fe in rat plasma. Calibration curves were obtained in the range of 0.125-1.50 ${\mu}g{\cdot}mL^{-1}$. The relative standard deviation ranges from 5.93% to 6.80%, and accuracy was between 87.6 and 102.0%. Dilution with water had no influence on the performance of the method, which could then be used to quantify Fe concentration in plasma up to 0.50 ${\mu}g{\cdot}mL^{-1}$. The limit of quantification was 0.10 ${\mu}g{\cdot}mL^{-1}$. At this level, the average relative standard deviation was 6.8%. The results indicate that the method meets the accuracy and precision requirements for the pharmacokinetic studies. The Fe concentration in rat plasma was measured and the main pharmacokinetic parameters were calculated by Topfit 2.0 (GmbH. Shering AG, Godecke AG, Germany).

• MALSORI
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• no.46
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• pp.103-115
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• 2003

In this paper, we proposed Background Model Set algorithm used in the speaker verification to improve calculating confidence measure(CM) in speech recognition. CM is to display relative likelihood between recognized models and antiphone models. In previous method calculating of CM, we calculated probability and standard deviation using all phonemes in composition of antiphone models. At this process, antiphone CM brought bad recognition result. Also, recognition time increases. In order to solve this problem, we studied about method to reconstitute average and standard deviation using BMS algorithm in CM calculation.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.79-82
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• 2003

In this paper, we proposed Backgorund Model Set algorithm for the speaker verification to improve the shortcoming of calculating process in conventional confidence measure(CM). CM is to display relative likelihood between recognized models and unrecognized models. Unrecognized models is known as antiphone models. Calculate probability and standard deviation using all phonemes at process that compose antiphone model. At this process, antiphone CM brought bad result. Also, recognition time increases. In order problem, we studied about method to reconstitute average and standard deviation taking BMS algorithm using antiphoneme that near phoneme of CM calculation.

• Analytical Science and Technology
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• v.13 no.2
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• pp.179-188
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• 2000

Trace elements in air samples artificially loaded on filters with urban dust and the bulk material of urban dust as an environmental sample were determined non-destructively using instrumental neutron activation analysis. Standard reference material (Urban Dust, SRM 1648) of the National Institute of Standard and Technology was used for the analytical quality control. The relative error for 37 elements was less than 15% and the standard deviation was less than 10%. 29 elements in the urban dust and 21 elements in the loaded filter sample were determined respectively. To evaluate the proficiency and reliability of the measurement, data intercomparison was performed and 39 analytical laboratories participated in the analysis using different analytical methods; neutron activation analysis, particle induced X-ray emission analysis, X-ray fluorescence analysis and atomic absorption spectrometry. Z-scores were calculated using the standard deviation of the laboratorie's mean as target standard deviation, and a good result was obtained that the values fall between -1 and +1 except some elements.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.3
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• pp.268-273
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• 1999

To measure the precision of Soiltek$^{(R)}$ KA-1 spectrophotometric measurement of soil available phosphate, standard deviation, C;V, and relative sensitivity were investigated, comparing to Lancaster method. Available phosphate concentration measured by Soiltek$^{(R)}$ KA-1 spectrophotometric method was highly correlated with Lancaster method($r=0.998^{***}$) and the slop of regression equation was close to 1.0. There were no differences in standard deviation. CV, and relative sensitivity for soil available phosphate concentrations measured by two methods. Regarding to convenience of experimental procedure and instrumental operation, and time saving analysis, Soiltek$^{(R)}$ KA-1 spectrophotometric measurement for soil available phosphate is highly recommended.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.575-581
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• 2002

This study evaluates the variation of estimation error of area-average rainfall due to rainfall seasonality. Both the cases considering and not considering the spatial correlation are compared to derive the characteristics of estimation error. Similar cases with different accumulation time without considering the rainfall seasonality are also investigated. This study was applied to the Geum-river basin with total 28 rain gauge measurements haying more than 30 years of daily rainfall measurements. As results of the study we found that: (1) The absolute estimation error of monthly area-average rainfall show strong seasonality like the total rainfall amount. However, the relative estimation error normalized by its mean was estimated to have similar values about 5 to 8% except January and December. (2) The relative estimation error of annual area-average rainfall estimated was found to have the estimation error about 3% of its annual mean. (3) However, the relative estimation error normalized by the standard deviation remains almost the same for both monthly and annual rainfall amounts, which was estimated about 11% of its standard deviation. (4) Finally, the estimation error without considering the spatial correlation was found to become almost twice the estimation error with considering the spatial correlation.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.4
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• pp.495-503
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• 1999

Airborne particulate matter $(PM_{10})$ collected using high volume air sampler and silica fiber filter were analyzed by Instrumental Neutron Activation Analysis(INAA), Inductively Coupled Plasma Atomic Emission Spectrometry(ICP-AES) and Atomic Absorption Spectrometry(AAS), and the results were compared with each other. 30~40 trace elements in environmental standard reference materials(NIST SRM 1648 and NIES CRM No.8) were analyzed for the analytical quality control. The relative error for two-third of elements detected was less than 10%, and the standard deviation was less than 15%. During the sampling period for 24 hours, the mass concentration of total suspended particulate was 36.1$\mu\textrm{g}$/㎥ and the value is lower than the critical level in Korea. In the results of NAA, the elements of Al, As, Ba, Fe, La, Mg, Na, Sb, Zn were well agreed with those of other methods. In statistical estimation between different methods, the deviation of Al, Ba, Cr, Fe was less than 10% and quite reliable.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.6
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• pp.864-873
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• 2013

In developing countries, biogas energy production is seen as a technology that can provide clean energy in poor regions and reduce pollution caused by animal manure. Laboratories in these countries have little access to advanced gas measuring equipment, which may limit research aimed at improving local adapted biogas production. They may also be unable to produce valid estimates of an international standard that can be used for articles published in international peer-reviewed science journals. This study tested and validated methods for measuring total biogas and methane ($CH_4$) production using batch fermentation and for characterizing the biomass. The biochemical methane potential (BMP) ($CH_4$ NL $kg^{-1}$ VS) of pig manure, cow manure and cellulose determined with the Moller and VDI methods was not significantly different in this test (p>0.05). The biodegradability using a ratio of BMP and theoretical BMP (TBMP) was slightly higher using the Hansen method, but differences were not significant. Degradation rate assessed by methane formation rate showed wide variation within the batch method tested. The first-order kinetics constant k for the cumulative methane production curve was highest when two animal manures were fermented using the VDI 4630 method, indicating that this method was able to reach steady conditions in a shorter time, reducing fermentation duration. In precision tests, the repeatability of the relative standard deviation (RSDr) for all batch methods was very low (4.8 to 8.1%), while the reproducibility of the relative standard deviation (RSDR) varied widely, from 7.3 to 19.8%. In determination of biomethane concentration, the values obtained using the liquid replacement method (LRM) were comparable to those obtained using gas chromatography (GC). This indicates that the LRM method could be used to determine biomethane concentration in biogas in laboratories with limited access to GC.

• Journal of Forest and Environmental Science
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• v.32 no.3
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• pp.280-290
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• 2016

Stem diameter variability is an essential inventory result that provides useful information in forest management decisions. Little has been done to explore the modelling potentials of standard deviation (SDD) and coefficient of variation (CVD) of diameter at breast height (dbh). This study, therefore, was aimed at developing and testing models for predicting SDD and CVD in stands of Pinus caribaea Morelet (pine) in south west Nigeria. Sixty temporary sample plots of size $20m{\times}20m$, ranging between 15 and 37 years were sampled, covering the entire range of pine in south west Nigeria. The dbh (cm), total and merchantable heights (m), number of stems and age of trees were measured within each plot. Basal area ($m^2$), site index (m), relative spacing and percentile positions of dbh at $24^{th}$, $63^{rd}$, $76^{th}$ and $93^{rd}$ (i.e. $P_{24}$, $P_{63}$, $P_{76}$ and $P_{93}$) were computed from measured variables for each plot. Linear mixed model (LMM) was used to test the effects of locations (fixed) and plots (random). Six candidate models (3 for SDD and 3 for CVD), using three categories of explanatory variables (i.e. (i) only stand size measures, (ii) distribution measures, and (iii) combination of i and ii). The best model was chosen based on smaller relative standard error (RSE), prediction residual sum of squares (PRESS), corrected Akaike Information Criterion ($AIC_c$) and larger coefficient of determination ($R^2$). The results of the LMM indicated that location and plot effects were not significant. The CVD and SDD models having only measures of percentiles (i.e. $P_{24}$ and $P_{93}$) as predictors produced better predictions than others. However, CVD model produced the overall best predictions, because of the lower RSE and stability in measuring variability across different stand developments. The results demonstrate the potentials of CVD in modelling stem diameter variability in relationship with percentiles variables.