Two dimensional representation of the Dirac equation in Non associative algebra

In this note a simple extension of the complex algebra to higher dimension is proposed. Using the postulated algebra a two dimensional Dirac equation is formulated and its solution is calculated. It is found that there is a sub-algebra where the associative nature can be recovered

Complexity Factor For Anisotropic Source in Non-minimal Coupling Metric f(R)f(R) Gravity

In this outline we recognize the idea of complexity factor for static anisotropic self-gravitating source with generalized $f(R)$ metric gravity theory. In present consideration, we express the Einstein field equations, hydrostatic equilibrium equation, the mass function and physical behavior of $f(R)$ model by using some observational data of well known compact stars like $4U~1820-30, SAX~J1808.4-3658$ and $Her~X-1$. We define the scalar functions through the orthogonal splitting of the Reimann-Christofell tensor and then find the vanishing complexity condition for self-gravitating system with the help of these scalars. It has been found that the vanishing condition for the complexity are pressure anisotropy and energy density inhomogeneity must cancel each other. Moreover, we study the momentous results of an astral object for the vanishing of complexity factor. Finally, these solutions reduced to previous investigation about complexity factor in General Relativity by taking $\lambda=0$.Comment: 20 pages, 5 Figures, 1 Table, Accepted for Publication in Eur. Physical Journal

Hybrid Coding Technique for Pulse Detection in an Optical Time Domain Reflectometer

The paper introduces a novel hybrid coding technique for improved pulse detection in an optical time domain reflectometer. The hybrid schemes combines Simplex codes with signal averaging to articulate a very sophisticated coding technique that considerably reduces the processing time to extract specified coding gains in comparison to the existing techniques. The paper quantifies the coding gain of the hybrid scheme mathematically and provide simulative results in direct agreement with the theoretical performance. Furthermore, the hybrid scheme has been tested on our self-developed OTDR

Epistemologi Santai: Epistemologi Jepang Masa Tokugawa

Pengetahuan merupakan kebutuhan kodrati manusia

Decentralized Greedy-Based Algorithm for Smart Energy Management in Plug-in Electric Vehicle Energy Distribution Systems

Variations in electricity tariffs arising due to stochastic demand loads on the power grids have stimulated research in finding optimal charging/discharging scheduling solutions for electric vehicles (EVs). Most of the current EV scheduling solutions are either centralized, which suffer from low reliability and high complexity, while existing decentralized solutions do not facilitate the efficient scheduling of on-move EVs in large-scale networks considering a smart energy distribution system. Motivated by smart cities applications, we consider in this paper the optimal scheduling of EVs in a geographically large-scale smart energy distribution system where EVs have the flexibility of charging/discharging at spatially-deployed smart charging stations (CSs) operated by individual aggregators. In such a scenario, we define the social welfare maximization problem as the total profit of both supply and demand sides in the form of a mixed integer non-linear programming (MINLP) model. Due to the intractability, we then propose an online decentralized algorithm with low complexity which utilizes effective heuristics to forward each EV to the most profitable CS in a smart manner. Results of simulations on the IEEE 37 bus distribution network verify that the proposed algorithm improves the social welfare by about 30% on average with respect to an alternative scheduling strategy under the equal participation of EVs in charging and discharging operations. Considering the best-case performance where only EV profit maximization is concerned, our solution also achieves upto 20% improvement in flatting the final electricity load. Furthermore, the results reveal the existence of an optimal number of CSs and an optimal vehicle-to-grid penetration threshold for which the overall profit can be maximized. Our findings serve as guidelines for V2G system designers in smart city scenarios to plan a cost-effective strategy for large-scale EVs distributed energy management