• Title/Summary/Keyword: normal distribution curve

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Size Distribution and Temperature Dependence of Magnetic Anisotropy Constant in Ferrite Nanoparticles

  • Yoon, Sunghyun
    • Proceedings of the Korean Magnestics Society Conference
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    • 2012.11a
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    • pp.104-105
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    • 2012
  • The temperature dependence of the effective magnetic anisotropy constant K(T) of ferrite nanoparticles is obtained based on the measurements of SQUID magnetometry. For this end, a very simple but intuitive and direct method for determining the temperature dependence of anisotropy constant K(T) in nanoparticles is introduced in this study. The anisotropy constant at a given temperature is determined by associating the particle size distribution f(r) with the anisotropy energy barrier distribution $f_A(T)$. In order to estimate the particle size distribution f(r), the first quadrant part of the hysteresis loop is fitted to the classical Langevin function weight-averaged with the log?normal distribution, slightly modified from the original Chantrell's distribution function. In order to get an anisotropy energy barrier distribution $f_A(T)$, the temperature dependence of magnetization decay $M_{TD}$ of the sample is measured. For this measurement, the sample is cooled from room temperature to 5 K in a magnetic field of 100 G. Then the applied field is turned off and the remanent magnetization is measured on stepwise increasing the temperature. And the energy barrier distribution $f_A(T)$ is obtained by differentiating the magnetization decay curve at any temperature. It decreases with increasing temperature and finally vanishes when all the particles in the sample are unblocked. As a next step, a relation between r and $T_B$ is determined from the particle size distribution f(r) and the anisotropy energy barrier distribution $f_A(T)$. Under the simple assumption that the superparamagnetic fraction of cumulative area in particle size distribution at a temperature is equal to the fraction of anisotropy energy barrier overcome at that temperature in the anisotropy energy barrier distribution, we can get a relation between r and $T_B$, from which the temperature dependence of the magnetic anisotropy constant was determined, as is represented in the inset of Fig. 1. Substituting the values of r and $T_B$ into the $N{\acute{e}}el$-Arrhenius equation with the attempt time fixed to $10^{-9}s$ and measuring time being 100 s which is suitable for conventional magnetic measurement, the anisotropy constant K(T) is estimated as a function of temperature (Fig. 1). As an example, the resultant effective magnetic anisotropy constant K(T) of manganese ferrite decreases with increasing temperature from $8.5{\times}10^4J/m^3$ at 5 K to $0.35{\times}10^4J/m^3$ at 125 K. The reported value for K in the literatures is $0.25{\times}10^4J/m^3$. The anisotropy constant at low temperature region is far more than one order of magnitude larger than that at 125 K, indicative of the effects of inter?particle interaction, which is more pronounced for smaller particles.

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Disease vector occurrence and ecological characteristics of chiggers on the chestnut white-bellied rat Niviventer fulvescens in Southwest China between 2001 and 2019

  • Yan-Ling Chen;Xian-Guo Guo;Wen-Yu Song;Tian-Guang Ren;Lei Zhang;Rong Fan;Cheng-Fu Zhao;Zhi-Wei Zhang;Wen-Ge Dong;Xiao-Bin Huang;Dao-Chao Jin
    • Parasites, Hosts and Diseases
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    • v.61 no.3
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    • pp.272-281
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    • 2023
  • Chigger mites are the vector of scrub typhus. This study estimates the infestation status and ecological characteristics of chiggers on the chestnut white-bellied rat Niviventer fulvescens in Southwest China between 2001 and 2019. Chiggers were identified under the microscope, and infestation indices were calculated. The Preston's log-normal model was used to fit the curve of species abundance distribution. A total of 6,557 chiggers were collected in 136 of 342 N. fulvescens rats, showing high overall infestation indices (prevalence=39.8%, mean abundance=19.2, mean intensity=48.2) and high species diversity (S=100, H'=3.0). Leptotrombidium cangjiangense, Neotrombicula japonica, and Ascoschoengastia sifanga were the three dominant chigger species (constituent ratio=42.9%; 2,736/6,384) and exhibited an aggregated distribution among different rat individuals. We identified 100 chigger species, with 3 of them (Leptotrombidium scutellare, Leptotrombidium wenense, and Leptotrombidium deliense) as the main vectors of scrub typhus in China and nine species as potential vectors of this disease. Disease vector occurrence on N. fulvescens may increase the risk of spreading scrub typhus from rats to humans. Chigger infestation on N. fulvescens varied significantly in different environments. The species abundance distribution showed a log-normal distribution pattern. The estimated number of chigger species on N. fulvescens was 126 species.

A Study on Developing the Optimal Sizing System for Ready-to-wear - Based on Elementary School Girls - (기성복의 최적 사이즈 시스템 개발을 위한 연구 - 학령기 여아를 중심으로 -)

  • Kim Ran-do;Lee Sang-youl;Kim Seon-young;Nam Yun-ja
    • Journal of the Korean Society of Clothing and Textiles
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    • v.29 no.8 s.145
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    • pp.1102-1113
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    • 2005
  • The propose of this study is to develop the optimal sizing system of ready-to-wear f3r elementary school girls using a newly invented statistical technique. The body measurements was classified by the method that equalizes the distribution of the subjects using the probability density function, to theoretically systemize a method to determine a size range of ready-to-wear for elementary school girls between 6 to 12 years old. The statistical method were 1) The total of 11 height groups, which size interval from one another is 6 cm that is an average height gap between each age. 2) In order to determine an approximate figure (m ${\times}$ n) to establish the appropriate sizes far each height group that fit to the combinations of bust and hip girth, which based on their means and standard deviations on the probability density curve to produce the standard normal distribution. 3) m and n were aligned by 4cm -the grading increments used for patterns making- and determined the size ranges by confirming the approximate figures of m and n. 4) The representative values were determined by an area ratio calculated by dividing the area determined from the range of bust and hip girth with the representative value. Considering the characteristics of subjects' distribution, the area ratios was used. 5) Weight was calculated by seeking a growth exponent for each age and multiplying it by the number of girls that fit to each size range. As sections that show the highest weight are more likely sought by the consumers, these sections were determined as the optimal size standards. 6) This optimal sizing system consists of sizes determined by the optimal size standards and its sizes are marked with height, bust and hip girth.

Curve Estimation among Citation and Centrality Measures in Article-level Citation Networks (문헌 단위 인용 네트워크 내 인용과 중심성 지수 간 관계 추정에 관한 연구)

  • Yu, So-Young
    • Journal of the Korean Society for information Management
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    • v.29 no.2
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    • pp.193-204
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    • 2012
  • The characteristics of citation and centrality measures in citation networks can be identified using multiple linear regression analyses. In this study, we examine the relationships between bibliometric indices and centrality measures in an article-level co-citation network to determine whether the linear model is the best fitting model and to suggest the necessity of data transformation in the analysis. 703 highly cited articles in Physics published in 2004 were sampled, and four indicators were developed as variables in this study: citation counts, degree centrality, closeness centrality, and betweenness centrality in the co-citation network. As a result, the relationship pattern between citation counts and degree centrality in a co-citation network fits a non-linear rather than linear model. Also, the relationship between degree and closeness centrality measures, or that between degree and betweenness centrality measures, can be better explained by non-linear models than by a linear model. It may be controversial, however, to choose non-linear models as the best-fitting for the relationship between closeness and betweenness centrality measures, as this result implies that data transformation may be a necessary step for inferential statistics.

Estimation of Coefficient of Consolidation Using Piezocone Dissipation Test in Normally Consolidated Clays (정규압밀점토에서의 피에조 콘 소산시험을 이용한 수평압밀계수의 산정)

  • 임형덕;이우진;김대규
    • Journal of the Korean Geotechnical Society
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    • v.19 no.5
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    • pp.145-154
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    • 2003
  • In this study, the variation in excess pore pressure during dissipation is estimated by using successive cavity expansion theory and finite difference technique based on axisymmetric uncoupled linear consolidation theory with separate consideration of magnitude and initial distribution $\Delta{u}_{oct}$induced by changes of octahedral normal stress, and $\Delta{u}_{shear}$ induced by changes of octahedral shear stress. The coefficient of consolidation is also estimated by trial and error procedure until the predicted dissipation curve matches the measured curve at a typical degree of dissipation. The proposed method is applied to the results of miniature piezocone tests at Louisiana State University calibration chamber system. Based on the results of interpretation and the comparison with experimental measurements and those from other solutions, the prediction dissipation curves show a good match with those measured during dissipation tests and the values of coefficient of consolidation estimated by proposed method are more close to the range of laboratory measurements than those of other theories.

Fast Axis Estimation from 3D Axially-Symmetric Object's Fragment (3차원 회전축 대칭 물체 조각의 축 추정 방법)

  • Li, Liang;Han, Dong-Jin;Hahn, Hern-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.6
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    • pp.748-754
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    • 2010
  • To reduce the computational cost required for assembling vessel fragments using surface geometry, this paper proposes a fast axis estimation method. Using circular constraint of pottery and local planar patch assumption, it finds the axis of the symmetry. First, the circular constraint on each cylinder is used. A circular symmetric pot can be thought of unions of many cylinders with different radii. It selects one arbitrary point on the pot fragment surface and searches a path where a circumference exists on that point. The variance of curvature will be calculated along the path and the path with the minimum variance will be selected. The symmetric axis will pass through the center of that circle. Second, the planar patch assumption and profile curve is used. The surface of fragment is divided into small patches and each patch is assumed as plane. The surface normal of each patch will intersects the axis in 3D space since each planar patch faces the center of the pot. A histogram method and minimization of the profile curve error are utilized to find the probability distribution of the axis location. Experimental results demonstrate the improvement in speed and robustness of the algorithms.

Electricity Price Forecasting in Ontario Electricity Market Using Wavelet Transform in Artificial Neural Network Based Model

  • Aggarwal, Sanjeev Kumar;Saini, Lalit Mohan;Kumar, Ashwani
    • International Journal of Control, Automation, and Systems
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    • v.6 no.5
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    • pp.639-650
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    • 2008
  • Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

Forest Structure and Composition in the Vicinity of Srinagar Hydroelectric Power Project in Alaknanda Valley, Garhwal Himalaya, India

  • Ballabha, Radha;Kuniyal, Archana;Tiwari, Prabhawati;Tiwari, Jay Krishan
    • Journal of Forest and Environmental Science
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    • v.36 no.2
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    • pp.78-90
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    • 2020
  • We studied forest structure and composition in the vicinity of Srinagar Hydroelectric Power Project in Alaknanda Valley, Garhwal Himalaya, India to provide baseline data for the management of forests. Eight sites were selected in the vicinity of power project based on elevation and species composition. Density varied from 650 to 340 ind ha-1 for trees and from 4,360 to 6,480 ind ha-1 for shrubs. TBC ranged from 35.02 to 54.02 ㎡ ha-1 for trees and from 0.875 to 2.628 ㎡ ha-1 for shrubs. On the basis of density and IVI, Pinus roxburghii was found dominant tree species in most of the sites, whereas among the shrubs, Carissa opaca was dominant. Dominance of Pinus roxburghii in most of the sites is an indication towards possible threat to associated species in the area. The dominance-diversity curve of trees showed a geometric distribution, whereas the shrubs displayed log-normal curves. The forest has rich and diverse species composition however; habitat degradation caused by the construction of Power Project might lead to reduction of plant species from the area. The information obtained from this study will be helpful in predicting possible changes in the forest ecosystem properties in near future after completion of the power project.

Size characteristics of the Korean Shelf Sediments (한국근해 퇴적물의 입도분포 특성)

  • 공영세;김승우
    • 한국해양학회지
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    • v.26 no.1
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    • pp.38-46
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    • 1991
  • size data of 1,044 surface sediments from Korean shelf area were compiled and reexamined. Size distribution curves of the sediments are unimodal (31% of the total number), bimodal (54%), or multimodal 915%), Size curves of the sediments and modal subpopulations of the mixed sediments show resemblance to normal curve in shape. The modal mean value shows systematic change along a direction inside the Recent mud belts of the southeastern Yellow Sea and west of Korea Strait. It was found that the areas covered by unimodal sand are minimal value areas of heavy metal and suspended sediment-concentration in the southeastern Yellow Sea and northern East China transport processes during Recent time. It was also found that the mode analysis is useful method to extract information from sediment size data.

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Weighted Interpolation Method Using Supplementary Filter (보조필터를 이용한 가중치 보간방법)

  • Jang, In-Gul;Lee, Jae-Kyung;Chung, Jin-Gyun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.3
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    • pp.119-124
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    • 2011
  • Interpolation filters are widely used in many communication and multimedia applications. Polynomial interpolation computes the coefficients of the polynomial according to the input information to obtain the interpolated value. Recently, FIR interpolation method using supplementary filters was proposed to improve the performances of polynomial interpolation methods. In this paper, by combining a weighting factor approach with the supplementary filter method, we propose a weighted interpolation method which can be efficiently used to compute the maximum or minimum values of a given curve using only a restricted number of sample values. With application to the interpolation of normal distribution curves used in XRF systems, it is shown that the proposed approach exhibits improved performances compared with conventional interpolation methods.