Arm-Root Curve Fitting Based on Body Surface Feature Points for Young Male

This paper is aiming to obtain an arm-root curve function performing the human arm-root size and shape realistically. A gypsum replica of upper arm for young male was made and scanned for extracting the 3D coordinates of 4 feature points of shoulder point, the anterior/posterior armpit point and the axillary point describing the real arm-root shape under the normalized definitions, and the 5 landmarks were confirmed additionally for improving the fitting precision. Then, the wholly and piecewise fitting of arm-root curve with 9 feature points and mark points in total were generated respectively based on least square polynomial fitting method. Comparing to the wholly fitting, the piecewise fitted function segmented by the line between anterior and posterior axillary points showed a high fitting degree of arm-root morphology with R-square of 1, the length difference between fitted curve and gypsum curve is 0.003 cm within error range. And it provided a basic curve model with standard feature points to simulate arm-root morphology realistically by curve fitting for accurate body measurement extraction.

Tensile stress-strain behavior of metallic alloys

Tensile stress-strain curves of five metallic alloys,i.e.,SKH51,STS316L,Ti-6Al-4V,Al6061and Inconel600were analyzed to investigate the working hardening behavior.The constitutive parameters of three constitutive equations,i.e.,the Hollomon,Swift and Voce equations,were compared by using different methods.A new working hardening parameter was proposed to characterize the working hardening behavior in different deformation stages.It is found that Voce equation is suitable to describe stress-strain curves in large strain region.Meanwhile,the predicting accuracy of ultimate tensile strength by Voce equation is the best.The working hardening behavior of SKH51is different from the other four metallic alloys.

Methods of de-noising the low frequency electromagnetic data

The quality of the low frequency electromagnetic data is affected by the spike and the trend noises.Failure in removal of the spikes and the trends reduces the credibility of data explanation.Based on the analyses of the causes and characteristics of these noises,this paper presents the results of a preset statistics stacking method(PSSM)and a piecewise linear fitting method(PLFM)in de-noising the spikes and trends,respectively.The magnitudes of the spikes are either higher or lower than the normal values,which leads to distortion of the useful signal.Comparisons have been performed in removing of the spikes among the average,the statistics and the PSSM methods,and the results indicate that only the PSSM can remove the spikes successfully.On the other hand,the spectrums of the linear and nonlinear trends mainly lie in the low frequency band and can change the calculated resistivity significantly.No influence of the trends is observed when the frequency is higher than a certain threshold value.The PLSM can remove effectively both the linear and nonlinear trends with errors around 1% in the power spectrum.The proposed methods present an effective way for de-noising the spike and the trend noises in the low frequency electromagnetic data,and establish a research basis for de-noising the low frequency noises.

Improved Baseline Correction Method Based on Polynomial Fitting for Raman Spectroscopy

Raman spectrum, as a kind of scattering spectrum, has been widely used in many fields because it can characterize the special properties of materials. However, Raman signal is so weak that the noise distorts the real signals seriously. Polynomial fitting has been proved to be the most convenient and simplest method for baseline correction. It is hard to choose the order of polynomial because it may be so high that Runge phenomenon appears or so low that inaccuracy fitting happens. This paper proposes an improved approach for baseline correction, namely the piecewise polynomial fitting （PPF）. The spectral data are segmented, and then the proper orders are fitted, respectively. The iterative optimization method is used to eliminate discontinuities between piecewise points. The experimental results demonstrate that this approach improves the fitting accuracy.

An Improved Power Flow Method to Cope with Non-smooth Constraints of Integrated Energy Systems

Integrated energy system applications can significantly improve energy efficiency.In this paper,we establish an integrated energy system containing heat,electricity and gas.The existing power flow(PF)calculation method applied to integrated energy systems(IESs)does not consider non-smooth constraints,such as the piecewise pipeline friction coefficient and generator buses reactive power limits,etc.Mixed integer nonlinear programming(MINLP)is conventionally used to deal with piecewise pipeline friction coefficients in gas network parts,but it is both complex and inefficient.Hence,we develop a piecewise linear function-based fitting method that can reduce the number of integer variables and enhanced the computational efficiency.In the electric network part,if the reactive power of the PV bus violates limits,it will be converted into a PQ bus,which is a non-differentiable and non-smooth constraint.Mixed complementarity problems are conventionally introduced to represent the PV-PQ buses type switching relationship and are addressed by the Newton-Raphson(NR)method.However,the above method is sensitive to the initial point.Here,we introduce a robust projected Levenberg-Marquardt(PLM)algorithm to cope with this issue.We demonstrate the advantages of our method and validate it both in a small-scale system and largescale network test cases.