arXiv subjects

Yang Cheng

Publications and source records attributed to Yang Cheng.

60 records · Page 4Linked to original sources

arXiv2019

Symmetry-breaking Actuation Mechanism for Soft Robotics and Active Metamaterials

Magnetic-responsive composites that consist of soft matrix embedded with hard-magnetic particles have recently been demonstrated as robust soft active materials for fast-transforming actuation. However, the deformation of the functional components commonly attains only a single actuation mode under external stimuli, which limits their capability of achieving tunable properties. To greatly enhance the versatility of soft active materials, we exploit a new class of programmable magnetic-responsive composites incorporated with a multifunctional joint design that allows asymmetric multimodal actuation under an external stimulation. We demonstrate that the proposed asymmetric multimodal actuation enables a plethora of novel applications ranging from the basic 1D/2D active structures with asymmetric shape-shifting to biomimetic crawling and swimming robots with efficient dynamic performance as well as 2D metamaterials with tunable properties. This new asymmetric multimodal actuation mechanism will open new avenues for the design of next-generation multifunctional soft robots, biomedical devices, and acoustic metamaterials.

physics.app-ph↗

arXiv2019

Band Structure Engineering of Interfacial Semiconductors Based on Atomically Thin Lead Iodide Crystals

To explore new constituents in two-dimensional materials and to combine their best in van der Waals heterostructures, are in great demand as being unique platform to discover new physical phenomena and to design novel functionalities in interface-based devices. Herein, PbI2 crystals as thin as few-layers are first synthesized, particularly through a facile low-temperature solution approach with the crystals of large size, regular shape, different thicknesses and high-yields. As a prototypical demonstration of flexible band engineering of PbI2-based interfacial semiconductors, these PbI2 crystals are subsequently assembled with several transition metal dichalcogenide monolayers. The photoluminescence of MoS2 is strongly enhanced in MoS2/PbI2 stacks, while a dramatic photoluminescence quenching of WS2 and WSe2 is revealed in WS2/PbI2 and WSe2/PbI2 stacks. This is attributed to the effective heterojunction formation between PbI2 and these monolayers, but type I band alignment in MoS2/PbI2 stacks where fast-transferred charge carriers accumulate in MoS2 with high emission efficiency, and type II in WS2/PbI2 and WSe2/PbI2 stacks with separated electrons and holes suitable for light harvesting. Our results demonstrate that MoS2, WS2, WSe2 monolayers with very similar electronic structures themselves, show completely distinct light-matter interactions when interfacing with PbI2, providing unprecedent capabilities to engineer the device performance of two-dimensional heterostructures.

cond-mat.mes-hall↗

arXiv2017

Object Recognition by Using Multi-level Feature Point Extraction

In this paper, we present a novel approach for object recognition in real-time by employing multilevel feature analysis and demonstrate the practicality of adapting feature extraction into a Naive Bayesian classification framework that enables simple, efficient, and robust performance. We also show the proposed method scales well as the number of level-classes grows. To effectively understand the patches surrounding a keypoint, the trained classifier uses hundreds of simple binary features and models class posterior probabilities. In addition, the classification process is computationally cheap under the assumed independence between arbitrary sets of features. Even though for some particular scenarios, this assumption can be invalid. We demonstrate that the efficient classifier nevertheless performs remarkably well on image datasets with a large variation in the illumination environment and image capture perspectives. The experiment results show consistent accuracy can be achieved on many challenging dataset while offer interactive speed for large resolution images. The method demonstrates promising results that outperform the state-of-the-art methods on pattern recognition.

cs.CV↗

arXiv2016

Hawking Radiation of Vector Particles via Tunneling From 4-Dimensional And 5-Dimensional Black Holes

Using Proca equation and WKB approximation, we investigate Hawking radiation of vector particles via tunneling from 4-dimensional Kerr-de Sitter black hole and 5-dimensional Schwarzschild-Tangherlini black hole. The results show that the tunneling rates and Hawking temperatures are depended on the properties of spacetime (event horizon, mass and angular momentum). Besides, our results are the same as scalars and fermions tunneling from 4-dimensional Kerr-de Sitter black hole and 5-dimensional Schwarzschild-Tangherlini black hole.

hep-th↗

arXiv2016

Virtual Reality based Learning Systems

This article is based on studies of the existing literature, focusing on the states-of-the-arts on virtual reality (VR) and its potential uses in learning. Different platforms have been used to improve the learning effects of VR that offers exciting opportunities in various fields. As more and more students want in a distance, part-time, or want to continue their education, VR has attracted considerable attention in learning, training, and traditional education. VR based learning enables operators to bring together all disciplinary resources in a common playground. The VR base multimedia platform has successfully demonstrated great potential of education and training. In this paper, we will discuss existing systems and their uses and address the technical challenges and future directions.

cs.CY↗

arXiv2011

Comparison of SCIPUFF Plume Prediction with Particle Filter Assimilated Prediction for Dipole Pride 26 Data

This paper presents the application of a particle filter for data assimilation in the context of puff-based dispersion models. Particle filters provide estimates of the higher moments, and are well suited for strongly nonlinear and/or non-Gaussian models. The Gaussian puff model SCIPUFF, is used in predicting the chemical concentration field after a chemical incident. This model is highly nonlinear and evolves with variable state dimension and, after sufficient time, high dimensionality. While the particle filter formalism naturally supports variable state dimensionality high dimensionality represents a challenge in selecting an adequate number of particles, especially for the Bootstrap version. We present an implementation of the Bootstrap particle filter and compare its performance with the SCIPUFF predictions. Both the model and the Particle Filter are evaluated on the Dipole Pride 26 experimental data. Since there is no available ground truth, the data has been divided in two sets: training and testing. We show that even with a modest number of particles, the Bootstrap particle filter provides better estimates of the concentration field compared with the process model, without excessive increase in computational complexity.

stat.AP↗