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.

Optimization of multi-color laser waveform for high-order harmonic generation

With the development of laser technologies,multi-color light-field synthesis with complete amplitude and phase control would make it possible to generate arbitrary optical waveforms.A practical optimization algorithm is needed to generate such a waveform in order to control strong-field processes.We review some recent theoretical works of the optimization of amplitudes and phases of multi-color lasers to modify the single-atom high-order harmonic generation based on genetic algorithm.By choosing different fitness criteria,we demonstrate that：（i） harmonic yields can be enhanced by 10 to 100 times,（ii） harmonic cutoff energy can be substantially extended,（iii） specific harmonic orders can be selectively enhanced,and（iv） single attosecond pulses can be efficiently generated.The possibility of optimizing macroscopic conditions for the improved phase matching and low divergence of high harmonics is also discussed.The waveform control and optimization are expected to be new drivers for the next wave of breakthrough in the strong-field physics in the coming years.

EMF Waveform Optimization using the Permanent Magnet Volume-Integration Method

The emf expression can be derived with the PM volume-integration method,allowing easier optimization and prediction of the emf harmonic content.An analytical expression is developed for predicting the electromotive force(emf)waveforms and flux linkage resulting from the motion of permanent magnets(PM)in the case of two cylinders,where the outer cylinder carries a surface-mounted winding and the inner cylinder carries the PMs.The expressions are based on the PM Volume-Integration Method,which uses a volume integral calculated over the magnet volume,rather than the usual surface integral over the coil surface.The specific case of surface-mounted arc PM with radial magnetization is analyzed.An outer cylinder with infinitely thin winding distribution on its inner surface is considered.The chording factor,slot factor and spread factor are included in the analytical expression.The emf waveform and related harmonics are predicted analytically and validated by comparing with a finite element analysis and with experiment.

A Novel Approach for Mitigating Power Quality Issues in a PV Integrated Microgrid System Using an Improved Jelly Fish Algorithm

A two-step methodology was used to address and improve the power quality concerns for the PV-integrated microgrid system. First, partial shading was included to deal with the real-time issues. The Improved Jelly Fish Algorithm integrated Perturb and Obserb (IJFA-PO) has been proposed to track the Global Maximum Power Point (GMPP). Second, the main unit-powered via DC–AC converter is synchronised with the grid. To cope with the wide voltage variation and harmonic mitigation, an auxiliary unit undergoes a novel series compensation technique. Out of various switching approaches, IJFA-based Selective Harmonic Elimination (SHE) in 120° conduction gives the optimal solution. Three switching angles were obtained using IJFA, whose performance was equivalent to that of nine switching angles. Thus, the system is efficient with minimised higher-order harmonics and lower switching losses. The proposed system outperformed in terms of efficiency, metaheuristics, and convergence. The Total Harmonic Distortion (THD) obtained was 1.32%, which is within the IEEE 1547 and IEC tolerable limits. The model was developed in MATLAB/Simulink 2016b and verified with an experimental prototype of grid-synchronised PV capacity of 260 W tested under various loading conditions. The present model is reliable and features a simple controller that provides more convenient and adequate performance.