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.

基于螺栓预紧力监测土工离心机不平衡力的方法研究

研究了一种基于监测地脚螺栓轴向预紧力变化的土工离心机动态不平衡力在线测量方法。首先,通过理论推导了不同的不平衡力状态下,地脚螺栓的轴向预紧力变化模型,证明了间接测试离心机不平衡力的可行性。其次,在TLJ-500型离心机上开展试验,获得了动态不平衡力矩随配重变化的规律,并对测点轴向力变化进行拟合,建立了测点轴向力与不平衡质量及离心机运行重力加速度g值的关系。最后,对一个地脚螺栓的预紧力变化进行测量,通过响应面拟合可建立地脚螺栓轴向预紧力的变化与离心机运行加速度和配重质量的关联。研究表明,通过监测地脚螺栓预紧力变化获得的离心机运行不平衡力的方法具有一定可行性,试验中应保持不同配重的质心一致;根据拟合式计算使转臂平衡的配重质量时,应尽量采用较大的加速度以降低离心机未甩平带来的误差。

不同林型橡胶林土壤水分入渗特征及影响因子

[目的]探究不同林型橡胶林土壤入渗特征及其影响因子,为高效、可持续橡胶林的构建提供数据支撑。[方法]以单一橡胶林(SR)、人工雨林橡胶林(AF)、橡胶-益智复合林(AR)、橡胶-可可复合林(RC)、橡胶-茶树复合林(RT)对入渗过程进行拟合和评价。[结果]纵观0-100 cm土壤剖面,SR容重最大,孔隙度、田间持水量和饱和持水量最小;SR初始入渗速率(0.03 cm/min)、平均入渗速率(0.009 cm/min)、稳定入渗速率(0.005 cm/min)均显著低于橡胶复合林;通过拟合发现Horton模型对胶农复合林入渗过程拟合较好且拟合参数具有物理意义;除非毛管孔隙度外,土壤物理性质与初始入渗速率有极显著相关关系(p<0.01),与总累积入渗量、稳定入渗速率有显著相关关系(p<0.05),但与平均入渗速率无显著相关性(p>0.05),而稳渗前累积入渗量受土壤持水性能的影响显著(p<0.01)。[结论]结合田间入渗过程,采用初始入渗速率、稳定入渗速率和稳渗前累积入渗量来评估不同林型橡胶林土壤水分入渗和储存性能;SR土壤持水能力、渗透性均低于橡胶复合林,其中RC土壤持水能力最好,RT土壤入渗性能最好,因此间作茶树和可可对改善土壤结构及水文特性有重要作用。

嗜热链球菌JM108发酵动力学模型的建立

本研究以嗜热链球菌JM108的生长和代谢为研究对象,以建立随时间变化模型,模拟细菌的生长、产物合成以及底物消耗的动力学变化。在M17培养基中接种嗜热链球菌JM108,每隔2 h对发酵体系内的嗜热链球菌JM108活菌数、乳酸含量以及葡萄糖含量进行测定,采用3种经典模型Logistic模型、Boltzmann模型和SGompertz模型对实验值进行非线性拟合。非线性拟合结果表明,Logistic模型最适合用于描述细菌生长动力学、乳酸生成动力学和葡萄糖消耗动力学,其R2值分别为0.9974、0.9947和0.9964,均大于0.99,拟合值与实验值的误差均小于15%,拟合良好,表明所建立的动力学模型能够较好地预测发酵过程的动态变化。嗜热链球菌JM108生长量动力学方程为:y=8.59+-2:39/1+(x/2.32)^(0.02);乳酸生成量动力学方程为:y=1.05+-1:061+(x/3.67)^(3.23);葡萄糖消耗量动力学方程为:y=0.02+0.151+(x/3.47)^(3.90)。建立嗜热链球菌JM108的发酵动力学模型,为描述发酵的动力学特征提供了理论支持。

基于病例组合指数校正抗菌药物使用强度的模型拟合研究

目的:探究病例组合指数与抗菌药物使用强度之间的关联关系,并对抗菌药物使用的评价进行调整,对其综合考量。方法:收集安徽省某三甲医院2021-2023年病例组合指数与抗菌药物相关指标,首先通过线性模型、二次曲线等8种模型拟合探索病例组合指数与抗菌药物相关指标之间的关系,随后通过秩和比综合评价法对不同科室间抗菌药物的使用情况重新评价。结果:病例组合指数与抗菌药物使用强度之间关联性较弱,但病例组合指数与同期出院人数的乘积与抗菌药物使用累积数存在较强关联,以此为基础进行的秩和比综合评价结果前后出现较大波动。结论:病例组合指数与抗菌药物使用强度之间存在间接关联,在后续抗菌药物使用的模型运算时应考虑校正,以增强评价结果的真实性。

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。

我国优秀女子铁人三项运动员专项体能特征及结构模型构建

目的:对比不同竞技水平运动员专项体能测试结果,探究我国优秀女子铁人三项运动员专项体能特征与结构。方法:对优秀组(n=7人),普通组(n=25人)进行专项体能测试,使用相关统计方法分析数据并构建模型。结果:(1)优秀组体脂百分比、克托莱指数、疲劳指数显著低于普通组(p<0.01),中胚型因子、最大摄氧量持续平台时间、相对峰值无氧功率、肺活量/体重指数显著较高(p<0.01);CSS、bFTP、rFTP、MaxR30min、4×bMaxP30sec、5×400米跑显著较优(p<0.01);(2)准则层序列:跑步素质>身体机能>游泳素质>自行车素质>身体形态>辅助素质;(3)内容层序列:rFTP>3000米跑>相对最大摄氧量>200米跑>相对峰值无氧功率>CSS>400米游>100米游>疲劳指数>bFTP>bMaxP5min>bMaxP30sec>克托莱指数>垂直纵跳>体脂百分比>反臂体前屈>身高臂展指数。结论:(1)女子优秀运动员机体瘦高线性、骨骼肌发达程度较高,呈均衡中胚型体型;长时间高强度持续有氧、无氧供能与做功能力强;各子项专项耐力、速度耐力与反复冲刺能力较优。(2)铁人三项专项体能结构由6项准则层指标、17项内容层指标构成。(3)跑步多项竞速能力是影响竞技表现的决定性指标,机体有氧、无氧供能能力发挥重要作用;游、骑多项竞速能力是有力支撑;充实度与力量素质发挥基础作用;柔韧性与肢体比例是保障性指标。