Density Functional Theory Study on the Electrical Properties of α-CsPbX3 (X=I, Cl, Br)

All-inorganic perovskite solar cells have become more important in the commercialization of the photovoltaic devices. In this study the structural, electronic properties of inorganic metal halide cubic perovskites CsPbX3 (X = I, Br, Cl) for perovskite solar cells are simulated using first-principles Density Functional Theory (DFT). The newly adjusted parameters make the calculations more accurate. These compounds are semiconductors with direct band gap energy. Results suggest that the α-CsPbX3 (X=I, Cl, Br) have a wide bandgap adjustment range with potential application in solar cells and other optoelectronic energy devices. On the basis of the electronic properties, one can expect that the α-CsPbI3 would be a better used to perovskite solar cell. α -CsPbCl3 and α-CsPbBr3 better suitable for others photovoltaic device

A Novel Model of Working Set Selection for SMO Decomposition Methods

In the process of training Support Vector Machines (SVMs) by decomposition methods, working set selection is an important technique, and some exciting schemes were employed into this field. To improve working set selection, we propose a new model for working set selection in sequential minimal optimization (SMO) decomposition methods. In this model, it selects B as working set without reselection. Some properties are given by simple proof, and experiments demonstrate that the proposed method is in general faster than existing methods.Comment: 8 pages, 12 figures, it was submitted to IEEE International conference of Tools on Artificial Intelligenc

On the Dynamical Wilf-Zeilberger Problem

In this paper, we give an algorithmic solution to a dynamical analog of the problem of certifying combinatorial identities by Wilf-Zeilberger pairs. Given two sequences generated in a dynamical setting, we calculate an upper bound N ≥ 1 such that whenever the first N terms of the two sequences agree pairwise, the two sequences agree term-by-term. Then, we give an algorithm that can be used to check whether two such sequences agree term-by-term. Our methods are mainly based on the theory of Chow rings of algebraic varieties

MEET: Mobility-Enhanced Edge inTelligence for Smart and Green 6G Networks

Edge intelligence is an emerging paradigm for real-time training and inference at the wireless edge, thus enabling mission-critical applications. Accordingly, base stations (BSs) and edge servers (ESs) need to be densely deployed, leading to huge deployment and operation costs, in particular the energy costs. In this article, we propose a new framework called Mobility-Enhanced Edge inTelligence (MEET), which exploits the sensing, communication, computing, and self-powering capabilities of intelligent connected vehicles for the smart and green 6G networks. Specifically, the operators can incorporate infrastructural vehicles as movable BSs or ESs, and schedule them in a more flexible way to align with the communication and computation traffic fluctuations. Meanwhile, the remaining compute resources of opportunistic vehicles are exploited for edge training and inference, where mobility can further enhance edge intelligence by bringing more compute resources, communication opportunities, and diverse data. In this way, the deployment and operation costs are spread over the vastly available vehicles, so that the edge intelligence is realized cost-effectively and sustainably. Furthermore, these vehicles can be either powered by renewable energy to reduce carbon emissions, or charged more flexibly during off-peak hours to cut electricity bills.Comment: This paper has been accepted by IEEE Communications Magazin