The Coordinated Development of Secondary Vocational School Specialty Clusters and Industry Clusters: Citing Longgang No.2 Vocational and Technical School of Shenzhen as a Case Study

With the implementation of the state’s Plan of Constructing High-Level Vocational Schools and Specialties with Chinese Characteristics, the construction of specialty clusters has become a hot topic. They are critical tools for improving the educational quality of vocational schools by promoting vocational education transformation, upgrading, and innovation. To maximize the effectiveness of specialty cluster development in secondary vocational school curriculum reform, we must first identify the rationale for multi-agency involvement in the development of specialty clusters and then formulate action plans. This article examines the definitions and connotations of specialty clusters and discusses the contexts in which specialty clusters emerged. It examines strategies for developing specialty clusters using Shenzhen’s Longgang No. 2 Vocational and Technical School as an example

Patch-based Progressive 3D Point Set Upsampling

We present a detail-driven deep neural network for point set upsampling. A high-resolution point set is essential for point-based rendering and surface reconstruction. Inspired by the recent success of neural image super-resolution techniques, we progressively train a cascade of patch-based upsampling networks on different levels of detail end-to-end. We propose a series of architectural design contributions that lead to a substantial performance boost. The effect of each technical contribution is demonstrated in an ablation study. Qualitative and quantitative experiments show that our method significantly outperforms the state-of-the-art learning-based and optimazation-based approaches, both in terms of handling low-resolution inputs and revealing high-fidelity details.Comment: accepted to cvpr2019, code available at https://github.com/yifita/P3

Quantum Algorithms for Identifying Hidden Strings with Applications to Matroid Problems

In this paper, we explore quantum speedups for the problem, inspired by matroid theory, of identifying a pair of $n$-bit binary strings that are promised to have the same number of 1s and differ in exactly two bits, by using the max inner product oracle and the sub-set oracle. More specifically, given two string $s, s'\in\{0, 1\}^n$ satisfying the above constraints, for any $x\in\{0, 1\}^n$ the max inner product oracle $O_{max}(x)$ returns the max value between $s\cdot x$ and $s'\cdot x$, and the sub-set oracle $O_{sub}(x)$ indicates whether the index set of the 1s in $x$ is a subset of that in $s$ or $s'$. We present a quantum algorithm consuming $O(1)$ queries to the max inner product oracle for identifying the pair $\{s, s'\}$, and prove that any classical algorithm requires $\Omega(n/\log_{2}n)$ queries. Also, we present a quantum algorithm consuming $\frac{n}{2}+O(\sqrt{n})$ queries to the subset oracle, and prove that any classical algorithm requires at least $n+\Omega(1)$ queries. Therefore, quantum speedups are revealed in the two oracle models. Furthermore, the above results are applied to the problem in matroid theory of finding all the bases of a 2-bases matroid, where a matroid is called $k$-bases if it has $k$ bases

Development of Graphene Based Nanocomposite for Supercapacitor Applications

The aim of this work is to provide a systematic study on exploring graphene-based nanocomposite electrodes with enhanced electrochemical performance for the applications of energy storage. At the first stage, a series of commercial graphene samples were carefully examined through a number of structural characterisation methods including TEM, XPS, Raman, and FTIR. It has been found that most of the industry –grade graphene has high degree of defects. Such defects have significant impact on electrochemical performance of supercapacitors. Based on the above study, a series of graphene-based nanocomposites, including graphene/metal oxide, graphene/metal sulfide, and graphene/silver nanowire have been developed to overcome some intrinsic disadvantage of graphene. The electrochemical properties of these nanocomposites have been optimized through engineering the composition and microstructure during electrodeposition process, which will provide important insights for future development of nanocomposite electrodes. In detail, metal oxide materials (CeO2) have been synthesized by two different methods, including hydrothermal and electrodeposition and their supercapacitor properties have been investigated. Although CeO2 has advantages of chemical stability, the resulting capacitance is quite low (~43 F/g at 200 mV/s). Therefore, metal sulfide has been fabricated which has better conductivity compared with metal oxide in order to improve capacitance. However, metal sulfide is unstable in the air and thus metal sulfide/oxide nanocomposites with superior performance have been developed. For example, the capacitance of CoxSy electrode achieves such high capacitance of 802.4 F/g while CeO2@ CoxSy composite electrode reaches 277.13 F/g. Finally, graphene/metal sulfide nanocomposite has been designed. As a result, a nanocomposite with high capacitance 295 F/g at 0.5 A/g was successfully prepared

Jamming precoding in AF relay-aided PLC systems with multiple eavessdroppers

Enhancing information security has become increasingly significant in the digital age. This paper investigates the concept of physical layer security (PLS) within a relay-aided power line communication (PLC) system operating over a multiple-input multiple-output (MIMO) channel based on MK model. Specifically, we examine the transmission of confidential signals between a source and a distant destination while accounting for the presence of multiple eavesdroppers, both colluding and non-colluding. We propose a two-phase jamming scheme that leverages a full-duplex (FD) amplify-and-forward (AF) relay to address this challenge. Our primary objective is to maximize the secrecy rate, which necessitates the optimization of the jamming precoding and transmitting precoding matrices at both the source and the relay while adhering to transmit power constraints. We present a formulation of this problem and demonstrate that it can be efficiently solved using an effective block coordinate descent (BCD) algorithm. Simulation results are conducted to validate the convergence and performance of the proposed algorithm. These findings confirm the effectiveness of our approach. Furthermore, the numerical analysis reveals that our proposed algorithm surpasses traditional schemes that lack jamming to achieve higher secrecy rates. As a result, the proposed algorithm offers the benefit of guaranteeing secure communications in a realistic channel model, even in scenarios involving colluding eavesdroppers

Nanostructured Metal Oxides-Based Electrode in Supercapacitor Applications

To overcome the obstacle of low energy density, one of the most intensive approaches is the development of new materials for supercapacitor electrodes. Most explored materials today are carbon particle materials, which have high surface areas for charge storage. But in spite of these large specific surface areas, the charges physically stored on the carbon particles in porous electrode layers are unfortunately limited. Regarding advanced supercapacitor electrodes, metal oxides are considered the most promising material for the next generation of supercapacitors owing to their unique physical and chemical properties. In this chapter, the rational design and fabrication of metal oxide nanostructures for supercapacitor applications are addressed