Parameterization Transfer for a Planar Computational Domain in Isogeometric Analysis

In this paper,we propose a parameterization transfer algorithm for planar domains bounded by B-spline curves,where the shapes of the planar domains are similar.The domain geometries are considered to be similar if their simplified skeletons have the same structures.One domain we call source domain,and it is parameterized using multi-patch B-spline surfaces.The resulting parameterization is C1 continuous in the regular region and G1 continuous around singular points regardless of whether the parameterization of the source domain is C1/G1 continuous or not.In this algorithm,boundary control points of the source domain are extracted from its parameterization as sequential points,and we establish a correspondence between sequential boundary control points of the source domain and the target boundary through discrete sampling and fitting.Transfer of the parametrization satisfies C1/G1 continuity under discrete harmonic mapping with continuous constraints.The new algorithm has a lower calculation cost than a decomposition-based parameterization with a high-quality parameterization result.We demonstrate that the result of the parameterization transfer in this paper can be applied in isogeometric analysis.Moreover,because of the consistency of the parameterization for the two models,this method can be applied in many other geometry processing algorithms,such as morphing and deformation.

Securing Healthcare Data in IoMT Network Using Enhanced Chaos Based Substitution and Diffusion

Patient privacy and data protection have been crucial concerns in Ehealthcare systems for many years.In modern-day applications,patient data usually holds clinical imagery,records,and other medical details.Lately,the Internet of Medical Things(IoMT),equipped with cloud computing,has come out to be a beneficial paradigm in the healthcare field.However,the openness of networks and systems leads to security threats and illegal access.Therefore,reliable,fast,and robust security methods need to be developed to ensure the safe exchange of healthcare data generated from various image sensing and other IoMT-driven devices in the IoMT network.This paper presents an image protection scheme for healthcare applications to protect patients’medical image data exchanged in IoMT networks.The proposed security scheme depends on an enhanced 2D discrete chaotic map and allows dynamic substitution based on an optimized highly-nonlinear S-box and diffusion to gain an excellent security performance.The optimized S-box has an excellent nonlinearity score of 112.The new image protection scheme is efficient enough to exhibit correlation values less than 0.0022,entropy values higher than 7.999,and NPCR values around 99.6%.To reveal the efficacy of the scheme,several comparison studies are presented.These comparison studies reveal that the novel protection scheme is robust,efficient,and capable of securing healthcare imagery in IoMT systems.

Symmetrical dynamics of peak current-mode and valley current-mode controlled switching dc-dc converters with ramp compensation

The discrete iterative map models of peak current-mode (PCM) and valley current-mode (VCM) controlled buck converters,boost converters,and buck-boost converters with ramp compensation are established and their dynamical behaviours are investigated by using the operation region,parameter space map,bifurcation diagram,and Lyapunov exponent spectrum.The research results indicate that ramp compensation extends the stable operation range of the PCM controlled switching dc-dc converter to D > 0.5 and that of the VCM controlled switching dc-dc converter to D < 0.5.Compared with PCM controlled switching dc-dc converters with ramp compensation,VCM controlled switching dc-dc converters with ramp compensation exhibit interesting symmetrical dynamics.Experimental results are given to verify the analysis results in this paper.