• Title/Summary/Keyword: least-squares methods

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Development and application of GLS OD matrix estimation with genetic algorithm for Seoul inner-ringroad (유전알고리즘을 이용한 OD 추정모형의 개발과 적용에 관한 연구 (서울시 내부순환도로를 대상으로))

  • 임용택;김현명;백승걸
    • Journal of Korean Society of Transportation
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    • v.18 no.4
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    • pp.117-126
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    • 2000
  • Conventional methods for collecting origin-destination trips have been mainly relied on the surveys of home or roadside interview. However, the methods tend to be costly, labor intensive and time disruptive to the trip makers, thus the methods are not considered suitable for Planning applications such as routing guidance, arterial management and information Provision, as the parts of deployments in Intelligent Transport Systems Motivated by the problems, more economic ways to estimate origin-destination trip tables have been studied since the late 1970s. Some of them, which have been estimating O-D table from link traffic counts are generally Entropy maximizing, Maximum likelihood, Generalized least squares(GLS), and Bayesian inference estimation etc. In the Paper, with user equilibrium constraint we formulate GLS problem for estimating O-D trips and develop a solution a1gorithm by using Genetic Algorithm, which has been known as a g1oba1 searching technique. For the purpose of evaluating the method, we apply it to Seoul inner ringroad and compare it with gradient method proposed by Spiess(1990). From the resu1ts we fond that the method developed in the Paper is superior to other.

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Locally adaptive intelligent interpolation for population distribution modeling using pre-classified land cover data and geographically weighted regression (지표피복 데이터와 지리가중회귀모형을 이용한 인구분포 추정에 관한 연구)

  • Kim, Hwahwan
    • Journal of the Korean association of regional geographers
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    • v.22 no.1
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    • pp.251-266
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    • 2016
  • Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.

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Comparison of In Vitro, Ex Vivo, and In Vivo Antibacterial Activity Test Methods for Hand Hygiene Products (손 위생 제품에 대한 in vitro, ex vivo, in vivo 항균 시험법 비교)

  • Daeun Lee;Hyeonju Yeo;Haeyoon Jeong
    • Journal of Food Hygiene and Safety
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    • v.39 no.1
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    • pp.35-43
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    • 2024
  • Numerous methods have been applied to assess the antibacterial effectiveness of hand hygiene products. However, the different results obtained through various evaluation methods have complicated our understanding of the real efficacy of the products. Few studies have compared test methods for assessing the efficacy of hand hygiene products. In particular, reports on ex vivo pig skin testing are limited. This study aimed to compare and characterize the methodologies applied for evaluating hand hygiene products, involving in vitro, ex vivo, and in vivo approaches, applicable to both leave-on sanitizers and wash-off products. Our further aim was to enhance the reliability of ex vivo test protocols by identifying influential factors. We performed an in vitro method (EN1276) and an in vivo test (EN1499 and ASTM2755) with at least 20 participants, against Serratia marcescens or Escherichia coli and Staphylococcus aureus. For the ex vivo experiment, we used pig skin squares prepared in the same way as those used in the in vivo test method and determined the optimal treated sample volumes for sanitizers and the amount of water required to wash off the product. The hand sanitizers showed at least a 5-log reduction in bacterial load in the in vitro test, while they showed little antibacterial activity in the in vivo and ex vivo tests, particularly those with a low alcohol content. For the hand wash products, the in vitro test was limited because of bubble formation or the high viscosity of the products and it showed low antibacterial activity of less than a 1-log reduction against E. coli. In contrast, significantly higher log reductions were observed in ex vivo and in vivo tests, consistently demonstrating these results across the two methods. Our findings revealed that the ex vivo and in vivo tests reflect the two different antibacterial mechanisms of leave-on and wash-off products. Our proposed optimized ex vivo test was more rapid and more precise than the in vitro test to evaluate antibacterial results.

Compensation of Light Scattering Method for Real-Time Monitoring of Particulate Matters in Subway Stations (지하역사 내 미세먼지 실시간 모니터링을 위한 광산란법 보정)

  • Kim, Seo-Jin;Kang, Ho-Seong;Son, Youn-Suk;Yoon, Sang-Lyeor;Kim, Jo-Chun;Kim, Gyu-Sik;Kim, In-Won
    • Journal of Korean Society for Atmospheric Environment
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    • v.26 no.5
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    • pp.533-542
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    • 2010
  • The $PM_{10}$ concentrations in the underground should be monitored for the health of commuters on the underground subway system. Seoul Metro and Seoul Metropolitan Rapid Transit Corporation are measuring several air pollutants regularly. As for the measurement of $PM_{10}$ concentrations, instruments based on $\beta$-ray absorption method and gravimetric methods are being used. But the instruments using gravimetric method give us 20-hour-average data and the $\beta$-ray instruments can measure the $PM_{10}$ concentration every one hour. In order to keep the $PM_{10}$ concentrations under a healthy condition, the air quality of the underground platform and tunnels should be monitored and controlled continuously. The $PM_{10}$ instruments using light scattering method can measure the $PM_{10}$ concentrations every less than one minute. However, the reliability of the instruments using light scattering method is still not proved. The purpose of this work is to study the reliability of the instruments using light scattering method to measure the $PM_{10}$ concentrations continuously in the underground platforms. One instrument using $\beta$-ray absorption method and two different instruments using light scattering method (LSM1, LSM2) were placed at the platform of the Jegi station of Seoul metro line Number 1 for 10 days. The correlation between the $\beta$-ray instrument and the LSM2 ($r^2$=0.732) was higher than that between the $\beta$-ray instrument and the LSM1 ($r^2$=0.393). Thus the LSM2 was chosen for further analysis. Three different regression analysis methods were tested: Linear regression analysis, Nonlinear regression analysis and Orthogonal regression analysis. When the instruments using light scattering method were used, the data measured these instruments have to be converted to actual $PM_{10}$ concentrations using some factors. With these analyses, the factors could be calculated successfully as linear and nonlinear forms with respect to the data. And the orthogonal regression analysis was performed better than the ordinary least squares method by 28.45% reduction of RMSE. These findings propose that the instruments using light scattering method light scattering method can be used to measure and control the $PM_{10}$ concentrations of the underground subway stations.

Determination of individual sugars in different varieties of persian grape using Near Infrared spectroscopy

  • Kargosha, Kazem;Azad, Jila;Lary, Abas Motamed
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1527-1527
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    • 2001
  • Glucose, fructose and sucrose being the main sugars that can be found in natural fruit juice. Many instrumental methods, such as GC, LC, electrochemical or spectrometric methods provide information about both the total content of sugars and the specific concentration of each carbohydrate[1]. The simplicity of sample handling and measurement in the near IR(NIR) wavelength region, which allows the use of long pathlength, optical glass cells and optical fibers, makes NIR a good alternative for sugar determination [2]. In the present study, six varieties of persian grapes were harvested at intervals through august to october and analysed for sugars by NIR. The results were processed by principal component regression (PCR) and partial least squares (PLS) analysis. Sample juice was prepared by squeezing through gauze from crashed grape. This solution was treated by zinc ferrocyanide prior to analysis in order to eliminate colored compounds and all optically active nonsugar substances. For glucose and fructose the most characteristic wavelengths were 1456nm corresponding to the first harmonic O-H stretching and the second at 2062nm corresponding to O-H stretching and deformation; secondary characteristic combination bands were also seen at 2265 nm (O-H and C-C stretching) and at 2240 nm (C-H and C-C stretching). However these spectra were taken over a wavelength range from 1100-2500nm at room temperature of 25-$30^{\circ}C$. To test the accuracy of the described procedure, samples of six varieties of grape were analysed by the proposed NIR and a standard method[2]. Good agreement were found between these two sets of the results. To perform the recovery studies , samples of grape juices previously analysed by the proposed method, were spiked with known amounts of each individual sugars and then analysed again. Relative standard deviations varied from 1.4 to 1.8% for six independent measurements of individual and total sugar concentration. In the analysis of real and synthetic samples, precise and accurate results were obtained , providing accuracy errors lower than 1.9% in all cases. Average recoveries of ${97}{\pm}{4%}$ for total sugar and between ${95}{\pm}{5%}$ and ${99}{\pm}{2%}$ for sing1e sugars demonstrate the applicability of the methodology developed to the direct analysis of grape Juice.

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COMPARISON OF LINEAR AND NON-LINEAR NIR CALIBRATION METHODS USING LARGE FORAGE DATABASES

  • Berzaghi, Paolo;Flinn, Peter C.;Dardenne, Pierre;Lagerholm, Martin;Shenk, John S.;Westerhaus, Mark O.;Cowe, Ian A.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1141-1141
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    • 2001
  • The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.

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Yield Prediction of Chinese Cabbage (Brassicaceae) Using Broadband Multispectral Imagery Mounted Unmanned Aerial System in the Air and Narrowband Hyperspectral Imagery on the Ground

  • Kang, Ye Seong;Ryu, Chan Seok;Kim, Seong Heon;Jun, Sae Rom;Jang, Si Hyeong;Park, Jun Woo;Sarkar, Tapash Kumar;Song, Hye young
    • Journal of Biosystems Engineering
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    • v.43 no.2
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    • pp.138-147
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    • 2018
  • Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

Application of Chiu's Two Dimensional Velocity Distribution Equations to Natural Rivers (Chiu가 제안한 2차원 유속분포식의 자연하천 적용성 분석)

  • Lee, Chan-Joo;Seo, Il-Won;Kim, Chang-Wan;Kim, Won
    • Journal of Korea Water Resources Association
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    • v.40 no.12
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    • pp.957-968
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    • 2007
  • It is essential to obtain accurate and highly reliable streamflow data for quantitative management for water resources. Thereafter such real-time streamflow gauging methods as ultrasonic flowmeter and index-velocity are introduced recently. Since these methods calculate flowrate through entire cross-section by measuring partial velocities of it, rational and theoretical basis are necessary for accurate estimation of discharge. The purpose of the present study lies in analysis on the applicability of Chiu#s(1987, 1988) two dimensional velocity distribution equations by applying them to natural rivers and by comparing simulated velocity distributions with observed ones obtained with ADCP. Maximum and mean velocities are calculated from observed data to estimate entropy parameter M. Such isovel shape parameters as h and $\beta_i$ are estimated by object function based on least squares criterion. In case optimized parameters are applied, Chiu#s velocity distributions fairly well simulate observed ones. By using 14 simulated data sets which have relatively high correlation coefficients, properties of parameters are analyzed and h, $\beta_i$ are estimated for velocity-unknown river sections. When estimated parameters are adopted for verification, simulated velocity distributions well reproduce real ones. Finally, calculated discharges display rough agreement with measured data. The results of the present study mean that if parameters related are properly estimated, Chiu#s velocity distribution is likely to reproduce the real one of natural rivers.

The Crystal and Molecular Structure of Sulfadiazine (Sulfadiazine의 結晶 및 分子構造)

  • Shin Hyun So;Ihn Gwon Shik;Kim Hoon Sup;Koo Chung Hoe
    • Journal of the Korean Chemical Society
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    • v.18 no.5
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    • pp.329-340
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    • 1974
  • Sulfadiazine, $C_{10}H_{10}N_4O_2S$, forms monoclinic crystals of space group $P21}c$ from a mixture of acetone and ethanol with $a=13.71{\pm}0.04,\;b=5.84{\pm}0.03,\;c=15.11{\pm}0.05{\AA},\;{\beta}=115.0{\pm}0.3^{\circ}$, and four molecules per cell. Three dimensional photographic data were collected with $CuK\alpha$ radiation. The structure was determined using Patterson and Fourier synthesis methods and refined by block diagonal least-squares methods with isotropic thermal parameter for all non-hydrogen atoms. The final R value was 0.15 for the 1517 observed independent reflections. The dihedral angle between the planes through the benzene ring and the pyrimidine ring is $76^{\circ}$. The conformational angle formed by the projection of the S-C(5) bond with that of N(1)-C(1) where the projection is taken along the S-N(1) bond is $77^{\circ}$. The imino nitrogen atom, N(1), and pyrimidine nitrogen atom, N(3), form intermolecular $N-H{\cdots}N$ hydrogen bond between the molecules related by center of symmetry. Amino nitrogen atom, N(4), forms two intermolecular $N-H{\cdots}O$ hydrogen bonds, with O(1) and O(2) atoms of different molecules separated by b. A two dimensional network of hydrogen bonds form infinite molecular sheets parallel to the (100) plane. Adjacent sheets are bound together by van der Waals forces.

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Comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) on the fungicial activity of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against phytophthora blight fungus (고추역병균에 대한 2-N-benzyl-5-Phenoxy-3-isothiazolone 유도체의 살균활성에 관한 비교분자 유사성 지수분석(CoMSIA)과 홀로그램 구조-활성 관계(HQSAR))

  • Sung, Nack-Do;Kim, Ki-Hyun
    • The Korean Journal of Pesticide Science
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    • v.6 no.3
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    • pp.209-217
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    • 2002
  • Two different QSAR methods, the comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) are studied for the fungicidal activities ($pI_{50}$) of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against sensitive (SPC: 95CC7105) and resisitive (RPC: 95CC7303) phytophthora blight fungus (Phytaphthora capsici). According to the findings from these QSAR investigation, the cross-validation value, $q^2$ and Pearson correlation coefficient, $r^2$ in the two methods were CoMSIA: RPC; $q^2=0.675,\;r^2=0.942$, SPC; $q^2=0.350,\;r^2=0.876$ and HQSAR: RPC; $q^2=0.519,\;r^2=0.869$, SPC; $q^2=0.483,\;r^2=0.990$, respectively. Therefore, the two models of comparative statistical significance were obtained. From the CoMSIA contour maps, the important factors for selective fungicidal activity against RPC are to be expected that the lower hydrophobic and not bulkiness substituent as hydrogen bonding acceptor have to introduce to meta and para-position (C1-C6) on the phenoxy moiety. And the results of prediction suggest that HQSAR method showed higher fungicidal activity than CoMSIA method.