Prosthetic modeling for femoral head based on ellipsoid fitting

A novel modeling method which can restore the shape of the femoral head with collapse induced by ischemic necrosis is proposed. First, sequential tomograms of the hip are obtained from a CT scan; secondly, an accurate and automatic method is used to extract the profile of the acetabulum; thirdly, a hybrid method is utilized to gather fiducial marks on the acetabulum; fourthly, bulky error sampling points are removed. Finally, an ellipsoid fitting method is used to fit the ellipsoid model of the femoral head. Two male sufferers with different necrosis extents are chosen as experimental subjects for contrastive simulation. Fifty cases of different ages （from 25 to 79 years old） are utilized for statistical comparisons of matching errors. The prosthetic models highly resemble the primary shape of the femoral head in health. This new method provides not only a theoretical model for accurate operation position fixing in an orthopaedics clinic, but it is also an innovative practical means for the individual manufacture of artificial femoral heads.

Objective Fitting Evaluation Model for Dressing Fit Based on Wrinkle Index of Dressing Image

An effective model(image to wrinkle, ITW) for garment fitting evaluation is presented. The proposed model is to improve the accuracy of garment fitting evaluation based on dressing image. The ITW model is an objective evaluation model of fitting based on the wrinkle index of dressing image. The ITW model consists of two main steps, the gray curve-fitting(GCF) threshold segmentation algorithm and Canny edge detection algorithm. In the ITW model, three types of wrinkle trends are defined. And the network dressing image is evaluated and simulated by three quantitative indexes: wrinkle number, wrinkle regularity and wrinkle unevenness. Finally, the fitness of three kinds of dress effects(tight, fit and loose) is quantified by objective fitting evaluation model.

A Robust Indoor Localization Algorithm Based on Polynomial Fitting and Gaussian Mixed Model

Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex environment.In this paper,a robust localization algorithm based on Gaussian mixture model and fitting polynomial is proposed to solve the problem of NLOS error.Firstly,fitting polynomials are used to predict the measured values.The residuals of predicted and measured values are clustered by Gaussian mixture model(GMM).The LOS probability and NLOS probability are calculated according to the clustering centers.The measured values are filtered by Kalman filter(KF),variable parameter unscented Kalman filter(VPUKF)and variable parameter particle filter(VPPF)in turn.The distance value processed by KF and VPUKF and the distance value processed by KF,VPUKF and VPPF are combined according to probability.Finally,the maximum likelihood method is used to calculate the position coordinate estimation.Through simulation comparison,the proposed algorithm has better positioning accuracy than several comparison algorithms in this paper.And it shows strong robustness in strong NLOS environment.

Analysis of reflected signal of quad rotor UAV based on model fitting in mobile communication system

In view of the many scenes of unmanned aerial vehicle(UAV)detection,a third-party signal source is used to design a receiver to monitor the UAV.It is of great significance to understand the reflection of the signal illuminating the UAV.Taking the communication base station(BS)signal as the third-party signal source,and considering the complete transmission link,reflection changes and loss fading of the communication signal,this study conducts model fitting for irregular UAV targets,simplifying complex targets into a combination of simple targets.Furthermore,the influence of the dielectric constant of the target surface and the signal irradiation angle on the signal reflection is analyzed.The analysis shows that the simulation results of this model fitting method are consistent with the results of other literature,which provides theoretical support for the detection of low and slow small targets such as UAVs.

Irregular surface seismic forward modeling by a body-fitted rotated–staggered-grid finite-difference method

Finite-difference(FD) methods are widely used in seismic forward modeling owing to their computational efficiency but are not readily applicable to irregular topographies. Thus, several FD methods based on the transformation to curvilinear coordinates using body-fitted grids have been proposed, e.g., stand staggered grid(SSG) with interpolation, nonstaggered grid, rotated staggered grid(RSG), and fully staggered. The FD based on the RSG is somewhat superior to others because it satisfies the spatial distribution of the wave equation without additional memory and computational requirements; furthermore, it is simpler to implement. We use the RSG FD method to transform the firstorder stress–velocity equation in the curvilinear coordinates system and introduce the highprecision adaptive, unilateral mimetic finite-difference(UMFD) method to process the freeboundary conditions of an irregular surface. The numerical results suggest that the precision of the solution is higher than that of the vacuum formalism. When the minimum wavelength is low, UMFD avoids the surface wave dispersion. We compare FD methods based on RSG, SEM, and nonstaggered grid and infer that all simulation results are consistent but the computational efficiency of the RSG FD method is higher than the rest.

Least squares fitting of coordinate parameters model

This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. The paper discusses the problem of least squares fitting of coordinate parameters model—parameters of deformation model. During discussion, the basic means of cubic B splines and two steps of multidimensional disorder datum fitting are adopted which can make fitting function calculated mostly approximate coordinate parameters model and it can make calculation easier.

Numerical Tidal Current Modeling Using Fine Boundary-Fitted Grids for Tidal Flats

Fine grids with small spacing in boundary-fitted coordinates are normally used to treat the computation of fluid dynamics for estuarine areas and tidal flats. However, the adoption of Cartesian components of velocity vectors in this kind of non-orthogonal coordinates will definitely result in a difficulty in solving implicitly the transformed momentum equations, and also complicate the wet-dry point judgement used for flood areas. To solve this problem, equations in terms of generalized contravariant velocity vectors in curvilinear coordinates are derived in the present study, by virtue of which, an Alternative-Direction-Implicit numerical scheme in non-orthogonal grids would then be easily obtained, and wet-dry point judgement would as well be largely simplified. A comparison is made between the explicit scheme and implicit scheme, showing that the present model is accurate and numerically stable for computations of fluid dynamics for estuarine areas and tidal flats.

Facial model fitting algorithm based on active appearance model

Active appearance model（AAM） is an efficient useful for the subsequent work such as face detection and method for the localization of facial feature points, which is also facial expression recognition. In this paper, we mainly discuss the AAMs based on principal component analysis （PCA）. We also propose an efficient facial fitting algorithm, which is named inverse compositional image alignment （ICIA）, to eliminate a considerable amount of computation resulting from traditional gradient descent fitting algorithm. Finally, 3D facial curvature is used to initialize the location of facial feature, which helps select the parameters of initial state for the improved AAM.

Comprehensive two-dimensional river ice model based on boundary-fitted coordinate transformation method

River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal processes, and they are also influenced by weather and hydrologic conditions. Because natural rivers are serpentine, with bends, narrows, and straight reaches, the commonly-used one-dimensional river ice models and two-dimensional models based on the rectangular Cartesian coordinates are incapable of simulating the physical phenomena accurately. In order to accurately simulate the complicated river geometry and overcome the difficulties of numerical simulation resulting from both complex boundaries and differences between length and width scales, a two-dimensional river ice numerical model based on a boundary-fitted coordinate transformation method was developed. The presented model considers the influence of the frazil ice accumulation under ice cover and the shape of the leading edge of ice cover during the freezing process. The model is capable of determining the velocity field, the distribution of water temperature, the concentration distribution of frazil ice, the transport of floating ice, the progression, stability, and thawing of ice cover, and the transport, accumulation, and erosion of ice under ice cover. A MacCormack scheme was used to solve the equations numerically. The model was validated with field observations from the Hequ Reach of the Yellow River. Comparison of simulation results with field data indicates that the model is capable of simulating the river ice process with high accuracy.

Asymptomatic Distribution of Goodness-of-Fit Tests in Logistic Regression Model

The logistic regression model has been become commonly used to study the association between a binary response variable;it is widespread application rests on its easy application and interpretation. The subject of assessment of goodness-of-fit in logistic regression model has attracted the attention of many scientists and researchers. Goodness-of-fit tests are methods to determine the suitability of the fitted model. Many of methods proposed and discussed for assessing goodness-of fit in logistic regression model, however, the asymptotic distribution of goodness-of-fit statistics are less examine, it is need more investigated. This work, will focus on assessing the behavior of asymptotic distribution of goodness-of-fit tests, also make comparison between global goodness-of-fit tests, and evaluate it by simulation.

Modelling Three-Dimensional Winds on a NW Pacific Region of Mexico Using Boundary-Fitted Grids

In this study, the momentum equations describing an atmospheric flow over a NW Pacific region of Mexico are solved numerically. In order to capture the complex flow-topography interactions with detail, a combination of a numerical wind model in full 3D curvilinear coordinates, along with a high resolution boundary-fitted grid is used. Boundary conditions were obtained from ten years (2002-2012) of measured offshore wind data. Prevailing winds from April to September during that period of observations were selected for the simulations. For the cases analyzed, it was found that at the points of the study region (PSS, PSM, PM), wind speed increased about 10% to 20% of its offshore values, while inland they decreased about 86% to 96%. This spatial behavior agreed very well with the observed local winds. A coastal jet (CJ), 35 km long with speeds about 1.5 - 2 m/s, emanating from PSS was found for NNW winds. Modeled winds were also used to compute wind stresses, wind stress curl, and CUI fields. Wind stress values agreed very well to those reported in the literature. High values of wind stress curl, and CUI were found at the lee of the points (PSS, PSM, PM). Indirect estimations of sea surface currents were about 15 - 20 cm/s offshore and 5 - 10 cm/s at the coast.

Determination of Material Parameters of EVA Foam under Uniaxial Compressive Testing Using Hyperelastic Models

The objective of this research was to determine the mechanical parameter from EVA foam and also investigate its behavior by using Blatz-Ko,Neo-Hookean,Mooney model and experimental test.The physical characteristic of EVA foam was also evaluated by scanning electron microscopy(SEM).The results show that Blatz-Ko and Neo-Hookean model can fit the curve at 5%and 8%strain,respectively.The Mooney model can fit the curve at 50%strain.The modulus of rigidity evaluated from Mooney model is 0.0814±0.0027 MPa.The structure of EVA foam from SEM image shows that EVA structure is a closed cell with homogeneous porous structure.From the result,it is found that Mooney model can adjust the data better than other models.This model can be applied for mechanical response prediction of EVA foam and also for reference value in engineering application.

Path-dependent speciation in dynamic fitness landscapes

Species is a fundamental concept in evolutionary biology and biodiversity.However,existing species definitions are often influenced by artificial factors or are challenging in practical application,leading to confusion in species classification.Due to uncertain environmental changes and random genetic drift,the fitness expectations of a population may shift,causing species to evolve to a new evolutionary state based on their current instantaneous fitness within a dynamic fitness landscape.This contrasts with the classic static fitness landscape,where fitness expectations are constant.In a dynamic fitness landscape,speciation may exhibit path dependence,where the evolution of traits follows a probabilistic path,creating feedback that shapes evolutionary trajectories.The path-dependent evolutionary mechanism suggests that species survival within an ecosystem is not directly determined by their fitness but by the probability of their evolutionary pathways.This model also indicates that species can coexist with varying probabilities under limited environmental pressures.Consequently,new species,cryptic species,or sympatric species may emerge via path-dependent evolutionary processes.Within this framework,we developed a mathematical species concept,which may guide future species classification methodologies.

基于GLUE和标准Bayesian方法对TOPMODEL模型的参数不确定性分析

目前,水文模型不确定性的量化问题在水文研究中受到很大关注,在一些文章中提到了许多不确定性量化的方法,其中,GLUE方法和标准Bayesian方法是两种最常用的方法。主要讨论这两种方法在研究TOPMODEL模型时计算有效性和不同之处.通过用GLUE和标准Bayesian方法估计TOPMODEL模型参数的不确定性和模拟的不确定性,对这两种方法的结果进行评价,并讨论产生不同的原因,研究的主要结果为:(1)由Bayesian方法得到的参数后验分布比GLUE方法得到的离散型小。(2)给定GLUE中阈值(=0.8)的情况下,由Bayesian方法得到模拟流量的不确定性置信区间与GLUE方法得到的很接近。

成年人身体活动变化阶段与健康变量的关系:对FIT模型理论的检验

从无活动到保持活动的四步骤模型(Four Steps from Inactivity to Activity,FIT模型)将个体的身体活动变化过程划分为六个阶段:前考虑期,考虑期,准备期,探索期,波动期和保持期。其中前三个阶段为不活动期,后三个阶段为活动期。本研究基于FIT模型,采用横断性研究设计,考查了1206名成年人(27～55岁)身体活动变化阶段与健康变量(身体体质、积极/消极主观良好感、健康满意度、不适感和BMI)之间的关系。研究结果表明,除BMI之外,健康变量在身体活动变化阶段上的主效应均显著,处于活动阶段的个体健康水平均好于处于不活动阶段的个体;处于保持期(即长期保持规律性身体活动)的个体身体体质、积极主观良好感和健康满意度水平均高于探索期和波动期,其消极主观良好感和身体不适感均低于探索期和波动期。此外,性别、年龄和教育程度不同程度调节了变化阶段与健康变量之间的关系。本研究验证了FIT模型中成年人身体活动变化阶段与健康变量之间的相关关系,为今后运用FIT模型诊断成年人身体活动变化阶段及其相应健康状况提供了实证性依据。

身体活动阶段理论的阶段有效性评估:以“从无活动到保持活动的四步骤(FIT)模型”为例

本研究从阶段算法测量有效性和阶段特征两个方面,对"从无活动到保持活动的四步骤模型"(FIT模型)的阶段有效性进行全面评估。前者检验FIT模型的阶段算法是否可以将个体正确划分为"活动者"和"不活动者",后者检验社会心理学变量是否随身体活动阶段变化表现出非连续性模式和非线性趋势。本研究采用横断性研究设计,以中德两国2082名成年人为研究被试(年龄:M=38.7,SD=8.67;中国人:1206人,57.9%),采用敏感性、特异性、受试者工作特征曲线(ROC曲线)、曲线下面积值(AUC值)和卡方检验考察阶段算法测量有效性及其在人口统计学变量上的差异性。此外,采用先验对比检验和趋势检验对阶段特征进行考察。研究结果包括:(1)在阶段算法测量有效性方面,敏感性指标为92.8%,特异性指标为81.5%,AUC值为0.93,表明FIT模型的阶段算法在区分活动者和不活动者上,具有较高的判别力。此外,敏感性和特异性在年龄和性别上差异均不显著,但在国籍和受教育程度上有显著差异。(2)在先验对比检验中,社会心理学变量在阶段上的非连续性模式得到证实。它们在相邻阶段间关系的假设有67.4%得到验证。在趋势检验中,所有社会心理学变量均出现显著的二次方及以上趋势,其非线性趋势得到证实。本研究在一定程度上验证了FIT模型的阶段有效性,为今后基于FIT模型身体活动阶段分类,设计阶段匹配性干预,促进成年人参与和坚持身体活动提供了理论依据。

Study on Growth and Development Rules and Growth Curve Fitting of Minghua Black Minks

Growth curves of Minghua black minks at 0-180 days old were fitted and analyzed by using two growth models Logistic and Gompertz. The results showed that the growth curves of Minghua black minks could be fitted very well by Logistic model and Gompertz model （the degree of fitting FF≥0.99）, but Gompertz model was better at fitting and predicting their weight.

成年人身体活动变化阶段及其社会心理学相关因素——初步检验“从无活动到保持活动的四步骤(FIT)”模型

基于锻炼心理学领域中的"从无活动到保持活动的四步骤模型"(Four Steps from Inactivity to Ac tivity;FIT模型),以1 206名成年人为研究对象,通过横断性研究考查了6个身体活动变化阶段与10个社会心理学相关变量之间的关系。研究结果表明,被试在身体活动阶段上的分布为:前考虑期147(12.2%),考虑期273(22.6%),准备期148(12.3%),探索期144(11.9%),波动期201(16.7%)和保持期293(24.3%)。有关社会心理学相关变量在相邻阶段间的配对比较,37项假设关系中的22项得到了支持,假设符合率为59.5%。进一步回归分析表明,性别、受教育程度、主观障碍、自我效能、情感态度和社会支持共同解释了阶段方差变异的32.6%。该研究初步验证了FIT模型所涉及的重要社会心理学相关因素与身体活动变化阶段之间的相关关系,基本支持了FIT模型的理论建构。

函数系数自回归模型推广形式的Back-Fitting估计

文章针对时间序列中函数系数自回归模型给出其推广形式,借助向后拟合的思想介绍推广形式中函数系数部分和参数部分的估计,该方法可以得到模型中的常值系数估计量的精确表达式;并通过一个数值模拟表明所提出的估计方法具有可行性和稳定性。

线性测量误差模型的lack-of-fit检验

基于正态假设 ,提出了测量误差模型lack of fit检验的一种方法 .在原假设下 ,检验统计量渐近服从 χ2 分布 .还就该检验的势函数与权函数的选择进行了讨论 。