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.

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.

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.

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.

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.

Absolutely Direct Frequency Measurement of Two-Photon Transition Using Multi-Peak Fitting Approach

The optical frequency comb has been widely used in precision measurement. In this study, a multi-peak fitting approach is first proposed to fit the two-photon transition spectrum which overlaps with the neighboring transition in Rb-87. The multi-peak fitting approach is used to eliminate the frequency shift affected by the neighboring transition. With locking the carrier envelope offset frequency at 1/4 repetition frequency, the transition frequency is measured to be 770569132739.9 +/- 5.8 kHz, which agrees well with the previous result recommended by Comite International des Poids et Mesures.

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.

Facial model fitting algorithm based on active appearance model

Active appearance model(AAM)is an efficient method for the localization of facial feature points,which is also useful for the subsequent work such as face detection and 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.

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。

Dynamics and data fitting of a time-delayed SIRS hepatitis B model with psychological inhibition factor and limited medical resources

Hepatitis B is an infectious disease worthy of attention.Considering the incubation period,psychological inhibition factor,vaccine,limited medical resources and horizontal transmission,an SIRS model is proposed to describe hepatitis B transmission dynamics.In order to describe the behavior changes caused by people's psychological changes,the non-monotonic incidence rate is adopted in the model.We use the saturated treatment rate to describe the limited medical resources.Mathematical analysis shows the existence conditions of the equilibria,forward or backward bifurcation,Hopf bifurcation and the Bogdanov-Takens bifurcation.During the observation of the case data of hepatitis B in China,it is found that there are mainly three features,periodic outbreaks,aperiodic outbreaks,and periodic outbreaks turns to aperiodic outbreaks.According to the above features,we select three different representative regions,Jiangxi,Zhejiang province and Beijing,and then use our model to fit the actual monthly hepatitis B case data.The basic reproduction numbers that we estimated are 1.7712,1.4805 and 1.4132,respectively.The results of data fitting are consistent with those of theoretical analysis.According to the sensitivity analysis of Ro,we conclude that reducing contact,increasing treatment rate,strengthening vaccination and revaccinating can effectively prevent and control the prevalence of hepatitis B.

Comparative Study on Analysis and Fitting of Pudong Chicken Growth Curve

The objective of this paper was to study the growth and development laws of Pudong chicken. The growth curve of Pudong chicken （cock and hen） from 0 to 20 weeks was analyzed and fitted with three models（Gompertz, Logistic and Bertalanffy）. It was concluded that the growth curves were appropriately fitted with three models, and fitness degree （R2）in growth data of Pudong chicken were all above 0.992. The Bertalanffy model was the most effective with the highest R2 for cock （R^2=0.995） and hen （R^2=0.999）, respectively. With further analysis of fitted parameters for Logis- tic model of cock, 0-3 weeks＇ fitted values were significantly greater than measured values and 4-8 weeks＇ fitted values were lower than measured values. Compared with Logistic model, the values calculated by Gompertz model and Bertalanffy model were more coincident with the practical measuring values. For hens, 0-3 weeks＇ fitted values of Logistic model were significantly greater than measured values and 0-2 weeks＇ fitted values of Gompertz model were slightly greater than measured values, while the values calculated by Bertalanffy model best matched the observed values from actual measure. The results showed that Bertalanffy model used to estimate the growth weight of Pudong chicken was the best while Logistic model was the worst. So the fitness and analysis of growth curves of Pudong chicken are valid, which may be adopted to predict growth and development laws of Pudong chicken and provide reliable data for precise feeding and breeding.

A NEW APPROACH TO THE CURVE FITTING OF IN VITRO RADIOASSAYS BASED ON THE MASS ACTION LOW

A new curve fitting method with its mathematical models derived from the mass action law is presented which is applicable to several in vitro radioassays including RIA and RBA. Experiments revealed that the robustness of this method is better than the conventional methods like Woolf plot in RBA and 4- parameter logistic plot in RIA. However, the robustness of this method is only relative: in some cases of RIA and RBA, the bias of the results may still be too large to be acceptable. Further improvement is expected to be studied.

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.

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.

Fitting methods for relaxation modulus of viscoelastic materials

Based on viscoelastic theory, two new computational methods of solving linear equations and minimum value of the 1-norm were put forward for transforming Kohlrausch-William-Watts (KWW) function of viscoelastic materials to the generalized Maxwell model. The computational methods for the Maxwell model fitting were achieved in MATLAB software. It is found that fitting precision of the two methods is very high. The method of solving linear equations needs more fitting points and more numbers of Maxwell units. It makes the program of finite element analysis complex. While the method of solving minimum value of 1-norm can obtain very high precision only using less fitting points. These methods can fit not only experimental curve of KWW function, but also the experimental data directly.

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.

Optimal zero-crossing group selection method of the absolute gravimeter based on improved auto-regressive moving average model

An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. Data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.

半变系数模型的Back-Fitting估计

针对半变系数回归模型给出了一种后向拟合方法,该方法可得到模型中常值系数估计量的精确表达式;同时给出了实验设计方法和数值模拟结果,用于验证所提出的估计方法对估计常值系数具有满意的精度和稳定性.

水稻群体分蘖动态模型构建与应用

为定量分析水稻群体茎蘖数量动态变化过程及分蘖动态特征,该研究使用双Logistic模型分别描述分蘖发生与死亡过程,建立水稻群体分蘖动态模型;根据水稻分蘖过程的时序特征定义描述分蘖过程的特征指标,并推导出分蘖特征指标的计算式;基于不同基因型品种的种植方式、种植时期、种植密度下水稻分蘖动态数据集检验模型优度和适应性;并应用分蘖动态模型和指标探索分蘖动态对种植密度的响应规律。结果表明,所建模型对不同基因型水稻品种在不同种植方式、种植时期和种植密度下的分蘖动态数据拟合优度较好,标准均方根误差S_(RMSE)服从均值小于5%的Gamma分布,并且99%的S_(RMSE)小于10%。基于所建模型计算的分蘖特征指标(包括模型参数)对种植密度有很好的响应;留一法检验表明模型的预测性较好,观测值与模拟值的R^(2)=0.96。所建模型能够精确描述水稻茎蘖数量演变过程,具有很好的拟合优度、适应性和可解释性,可用于分析基因、环境、农艺措施对分蘖动态的影响,分蘖特征指标可望成为分析基因与环境互作的重要表型参数,对指导水稻精准栽培也有重要理论价值和实际意义。