Optimization of superelevation runoff model for cycling tracks

To improve the possible superelevation runoff models for the cycling track design,at first,two existing representative superelevation runoff models used in China were investigated and fitted. Then,an optimization methodology was proposed,which was focused on the track geometry itself,without the consideration of the physical characteristic of the cyclist,assuming that less vertical curvature values correspond to less riding time. The riding performance formulae were obtained with the variables of riding time,riding velocity and vertical curvature of cycling track. Finally,with the refined adjustment on the vertical curvatures with the help of cycling track design software and considering the effect of horizontal alignments,the optimized models were finalized. It is clearly seen that these optimized models take the form of quartic parabola and are verified to achieve 0.005-0.021 s improvement in the event of 200 m time trial.

Secured Vehicle Life Cycle Tracking Using Blockchain and Smart Contract

Life Cycle Tracking(LCT)involves continuous monitoring and analy-sis of various activities associated with a vehicle.The crucial factor in the LCT is to ensure the validity of gathered data as numerous supply chain phases are involved and the data is assessed by multiple stakeholders.Frauds and swindling activities can be prevented if the history of the vehicles is made available to the interested parties.Blockchain provides a way of enforcing trustworthiness to the supply chain participants and the data associated with the various actions per-formed.Machine learning techniques when combined decentralized nature of blockchains can be used to develop a robust Vehicle LCT model.In the proposed work,Harmonic Optimized Gradient Descent andŁukasiewicz Fuzzy(HOGD-LF)Vehicle Life Cycle Tracking in Cloud Environment is proposed and it involves three stages.First,the Progressive Harmonic Optimized User Registra-tion and Authentication model is designed for computationally efficient registra-tion and authentication.Next,for the authentic user,the Gradient Descent Blockchain-based SVM Data Encryption model is designed with minimum CPU utilization.Finally,Łukasiewicz Fuzzy Smart Contract Verification is per-formed with encrypted data to ensure accurate and precise fraudulent activity deduction.The experimental analysis shows that the proposed method achieves significant performance in terms of life cycle’s prediction time,overhead,and accuracy for a different number of users.

Simulation research of discrete sliding mode control for active power filter

Because of the widely-used nonlinear loads, the problems of harmonics and low power factor in power systems are becoming more and more serious. In view of the above problems, a shunt three-phase active power filter （SAPF） based on discrete sliding mode control to suppress the harmonics was designed and the power factor improved. First, built the mathematical model of SAPF. Then, controlled the switch through analyzing the harmonic current that was controlled signal using discrete sliding mode control. Through simulation using MATLAB, verified the validity of the algorithm. By the simulation waveforms, it can be found that after the load current containing a large number of harmonics passes the active power filter, the waveform of the power current approximately becomes a sine wave and the harmonics is significantly reduced. As a result, it plays a good role in purifying power systems. Moreover, from the waveforms of harmonic current and power current, it can be found that the algorithm has a faster tracking speed. The waveform can fect.