10 resultados para Graded Quantum Yang-baxter Reflection Equation

em Instituto Politécnico do Porto, Portugal


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Until this day, the most efficient Cu(In,Ga)Se2 thin film solar cells have been prepared using a rather complex growth process often referred to as three-stage or multistage. This family of processes is mainly characterized by a first step deposited with only In, Ga and Se flux to form a first layer. Cu is added in a second step until the film becomes slightly Cu-rich, where-after the film is converted to its final Cu-poor composition by a third stage, again with no or very little addition of Cu. In this paper, a comparison between solar cells prepared with the three-stage process and a one-stage/in-line process with the same composition, thickness, and solar cell stack is made. The one-stage process is easier to be used in an industrial scale and do not have Cu-rich transitions. The samples were analyzed using glow discharge optical emission spectroscopy, scanning electron microscopy, X-ray diffraction, current–voltage-temperature, capacitance-voltage, external quantum efficiency, transmission/reflection, and photoluminescence. It was concluded that in spite of differences in the texturing, morphology and Ga gradient, the electrical performance of the two types of samples is quite similar as demonstrated by the similar J–V behavior, quantum spectral response, and the estimated recombination losses.

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We perform a comparison between the fractional iteration and decomposition methods applied to the wave equation on Cantor set. The operators are taken in the local sense. The results illustrate the significant features of the two methods which are both very effective and straightforward for solving the differential equations with local fractional derivative.

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The local fractional Burgers’ equation (LFBE) is investigated from the point of view of local fractional conservation laws envisaging a nonlinear local fractional transport equation with a linear non-differentiable diffusion term. The local fractional derivative transformations and the LFBE conversion to a linear local fractional diffusion equation are analyzed.

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Ian McEwan‘s novel Saturday deals with the complex issues of conflict and transformation in the age of terrorism. The plot presents one internal dilemma and several interpersonal altercations that occur within a mere twenty-four hours: a) Perowne (the protagonist) vs. himself, in face of his ambivalent thoughts regarding British military participation in the war in the Middle East; b) The protagonist vs. Baxter, a ruffian from East End, in the context of a car accident; c) Perowne vs. a fellow anaesthetist, Jay Strauss, during a squash game; d) Perowne‘s daughter, Daisy vs. her grandfather, John Grammaticus, both poets and rivals; e) Perowne‘s family vs. Baxter, who intrudes the protagonist‘s house. In this paper, I exemplify, analyse and discuss how: a) Understanding the causes of what we call evil constitutes an important step towards mutual understanding; b) Both science and arts (which Perowne considers, at first, irrelevant) are important elements in the process of transformation; c) Both personal and interpersonal conflicts are intrinsic to human nature — but they also propitiate healthy changes in behaviour and opinion, through reflection. In order to do so, I resort to Saturday, and to the work of several specialists in the field of conflict management.

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In this paper, we discuss the mathematical aspects of the Heisenberg uncertainty principle within local fractional Fourier analysis. The Schrödinger equation and Heisenberg uncertainty principles are structured within local fractional operators.

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Monitoring is a very important aspect to consider when developing real-time systems. However, it is also important to consider the impact of the monitoring mechanisms in the actual application. The use of Reflection can provide a clear separation between the real-time application and the implemented monitoring mechanisms, which can be introduced (reflected) into the underlying system without changing the actual application part of the code. Nevertheless, controlling the monitoring system itself is still a topic of research. The monitoring mechanisms must contain knowledge about “how to get the information out”. Therefore, this paper presents the ongoing work to define a suitable strategy for monitoring real-time systems through the use of Reflection.

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Traditional Real-Time Operating Systems (RTOS) are not designed to accommodate application specific requirements. They address a general case and the application must co-exist with any limitations imposed by such design. For modern real-time applications this limits the quality of services offered to the end-user. Research in this field has shown that it is possible to develop dynamic systems where adaptation is the key for success. However, adaptation requires full knowledge of the system state. To overcome this we propose a framework to gather data, and interact with the operating system, extending the traditional POSIX trace model with a partial reflective model. Such combination still preserves the trace mechanism semantics while creating a powerful platform to develop new dynamic systems, with little impact in the system and avoiding complex changes in the kernel source code.

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Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

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In this paper we present the operational matrices of the left Caputo fractional derivative, right Caputo fractional derivative and Riemann–Liouville fractional integral for shifted Legendre polynomials. We develop an accurate numerical algorithm to solve the two-sided space–time fractional advection–dispersion equation (FADE) based on a spectral shifted Legendre tau (SLT) method in combination with the derived shifted Legendre operational matrices. The fractional derivatives are described in the Caputo sense. We propose a spectral SLT method, both in temporal and spatial discretizations for the two-sided space–time FADE. This technique reduces the two-sided space–time FADE to a system of algebraic equations that simplifies the problem. Numerical results carried out to confirm the spectral accuracy and efficiency of the proposed algorithm. By selecting relatively few Legendre polynomial degrees, we are able to get very accurate approximations, demonstrating the utility of the new approach over other numerical methods.