arXiv subjects

Xiao Tang

Publications and source records attributed to Xiao Tang.

At least 73 records · Page 4Linked to original sources

arXiv2023

Robust Trajectory and Offloading for Energy-Efficient UAV Edge Computing in Industrial Internet of Things

Efficient data processing and computation are essential for the industrial Internet of things (IIoT) to empower various applications, which yet can be significantly bottlenecked by the limited energy capacity and computation capability of the IIoT nodes. In this paper, we employ an unmanned aerial vehicle (UAV) as an edge server to assist IIoT data processing, while considering the practical issue of UAV jittering. Specifically, we propose a joint design on trajectory and offloading strategies to minimize energy consumption due to local and edge computation, as well as data transmission. We particularly address the UAV jittering that induces Gaussian-distributed uncertainties associated with flying waypoints, resulting in probabilistic-form flying speed and data offloading constraints. We exploit the Bernstein-type inequality to reformulate the constraints in deterministic forms and decompose the energy minimization to solve for trajectory and offloading separately within an alternating optimization framework. The subproblems are then tackled with the successive convex approximation technique. Simulation results show that our proposal strictly guarantees robustness under uncertainties and effectively reduces energy consumption as compared with the baselines.

eess.SP↗

arXiv2023

Sparsity-Aware Intelligent Massive Random Access Control in Open RAN: A Reinforcement Learning Based Approach

Massive random access of devices in the emerging Open Radio Access Network (O-RAN) brings great challenge to the access control and management. Exploiting the bursting nature of the access requests, sparse active user detection (SAUD) is an efficient enabler towards efficient access management, but the sparsity might be deteriorated in case of uncoordinated massive access requests. To dynamically preserve the sparsity of access requests, a reinforcement-learning (RL)-assisted scheme of closed-loop access control utilizing the access class barring technique is proposed, where the RL policy is determined through continuous interaction between the RL agent, i.e., a next generation node base (gNB), and the environment. The proposed scheme can be implemented by the near-real-time RAN intelligent controller (near-RT RIC) in O-RAN, supporting rapid switching between heterogeneous vertical applications, such as mMTC and uRLLC services. Moreover, a data-driven scheme of deep-RL-assisted SAUD is proposed to resolve highly complex environments with continuous and high-dimensional state and action spaces, where a replay buffer is applied for automatic large-scale data collection. An actor-critic framework is formulated to incorporate the strategy-learning modules into the near-RT RIC. Simulation results show that the proposed schemes can achieve superior performance in both access efficiency and user detection accuracy over the benchmark scheme for different heterogeneous services with massive access requests.

cs.LG↗

arXiv2023

Robust Secrecy via Aerial Reflection and Jamming: Joint Optimization of Deployment and Transmission

Reconfigurable intelligent surfaces (RISs) are recognized with great potential to strengthen wireless security, yet the performance gain largely depends on the deployment location of RISs in the network topology. In this paper, we consider the anti-eavesdropping communication established through a RIS at a fixed location, as well as an aerial platform mounting another RIS and a friendly jammer to further improve the secrecy. The aerial RIS helps enhance the legitimate signal and the aerial cooperative jamming is strengthened through the fixed RIS. The security gain with aerial reflection and jamming is further improved with the optimized deployment of the aerial platform. We particularly consider the imperfect channel state information issue and address the worst-case secrecy for robust performance. The formulated robust secrecy rate maximization problem is decomposed into two layers, where the inner layer solves for reflection and jamming with robust optimization, and the outer layer tackles the aerial deployment through deep reinforcement learning. Simulation results show the deployment under different network topologies and demonstrate the performance superiority of our proposal in terms of the worst-case security provisioning as compared with the baselines.

eess.SP↗

arXiv2023

Parameterized shadowing for nonautonomous dynamics

For nonautonomous and nonlinear differential and difference equations depending on a parameter, we formulate sufficient conditions under which they exhibit $C^k$, $k\in \N$ shadowing with respect to a parameter. Our results are applicable to situations when the linear part is not hyperbolic. In the case when the linear part is hyperbolic, we obtain results dealing with parameterized Hyers-Ulam stability.

math.DS↗

arXiv2022

Smooth solutions of a class of iterative functional equations

Imposing some conditions on derivatives of the known functions, using the Fiber Contraction Theorem we prove the existence of $C^1$ solutions of a class of iterative functional equations which involves iterates of the unknown functions and a nonlinear term.

math.CA↗

arXiv2022

Incentivizing Proof-of-Stake Blockchain for Secured Data Collection in UAV-Assisted IoT: A Multi-Agent Reinforcement Learning Approach

The Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. In this paper, we propose to employ unmanned aerial vehicles (UAVs) to assist the clustered IoT data collection with blockchain-based security provisioning. In particular, the UAVs generate candidate blocks based on the collected data, which are then audited through a lightweight proof-of-stake consensus mechanism within the UAV-based blockchain network. To motivate efficient blockchain while reducing the operational cost, a stake pool is constructed at the active UAV while encouraging stake investment from other UAVs with profit sharing. The problem is formulated to maximize the overall profit through the blockchain system in unit time by jointly investigating the IoT transmission, incentives through investment and profit sharing, and UAV deployment strategies. Then, the problem is solved in a distributed manner while being decoupled into two layers. The inner layer incorporates IoT transmission and incentive design, which are tackled with large-system approximation and one-leader-multi-follower Stackelberg game analysis, respectively. The outer layer for UAV deployment is undertaken with a multi-agent deep deterministic policy gradient approach. Results show the convergence of the proposed learning process and the UAV deployment, and also demonstrated is the performance superiority of our proposal as compared with the baselines.

cs.NI↗

arXiv2021

Ferroelectric materials and their applications in green catalysis

The demand for renewable and environmentally friendly energy source has attracted extensive research on high performance catalysts. Ferroelectrics which are a class of materials with a switchable polarization are the unique and promising catalyst candidates due to the significant effects of polarization on surfaces physical and chemical properties. The band bending at the ferroelectric/semiconductor interface induced by the polarization flip promotes the charge separation and transfer, there by enhancing the photocatalytic performance. More importantly, the reactants can be selectively adsorbed on the surface of the ferroelectric materials depending on the polarization direction, which can effectively lift the basic limitations as imposed by Sabatier principle on catalytic activity. This review summarizes the latest developments of ferroelectric materials, and introduces the ferroelectric-related catalytic application. The possible research directions of 2D ferroelectric materials in chemical catalysis is discussed at the end. The review is expected to inspire the extensive research interests from physical, chemical and material science communities.

cond-mat.mtrl-sci↗

arXiv2021

A sufficient condition for existence of iterative roots of PM functions without the characteristic endpoints condition

For PM functions of height 1, the existence of continuous iterative roots of any order was obtained under the characteristic endpoints condition. This raises an open problem about iterative roots without this condition, called characteristic endpoints problem. This problem is solved almost completely when the number of forts is equal to or less than the order. In this paper, we study the case that the number of forts is greater than the order and give a sufficient condition for existence of continuous iterative roots of order $2$ with height 2, answering the characteristic endpoints problem partially.

math.CA↗

arXiv2021

Towards Accurate Alignment in Real-time 3D Hand-Mesh Reconstruction

3D hand-mesh reconstruction from RGB images facilitates many applications, including augmented reality (AR). However, this requires not only real-time speed and accurate hand pose and shape but also plausible mesh-image alignment. While existing works already achieve promising results, meeting all three requirements is very challenging. This paper presents a novel pipeline by decoupling the hand-mesh reconstruction task into three stages: a joint stage to predict hand joints and segmentation; a mesh stage to predict a rough hand mesh; and a refine stage to fine-tune it with an offset mesh for mesh-image alignment. With careful design in the network structure and in the loss functions, we can promote high-quality finger-level mesh-image alignment and drive the models together to deliver real-time predictions. Extensive quantitative and qualitative results on benchmark datasets demonstrate that the quality of our results outperforms the state-of-the-art methods on hand-mesh/pose precision and hand-image alignment. In the end, we also showcase several real-time AR scenarios.

cs.CV↗

arXiv2020

Epitaxial Growth of $β$-Ga$_2$O$_3$ Coated Wide Bandgap Semiconductor Tape for Flexible UV Photodetector

The epitaxial growth of technically-important $β$-Ga$_2$O$_3$ semiconductor thin films have not been realized on flexible substrates due to limitations by the high-temperature crystallization conditions and the lattice-matching requirements. In this report, for the first time single crystal $β$-Ga$_2$O$_3$(-201) thin films is epitaxially grown on the flexible CeO2 (001)-buffered hastelloy tape. The results indicate that CeO$_2$ (001) has a small bi-axial lattice mismatch with $β$-Ga$_2$O$_3$ (-201), thus inducing a simultaneous double-domain epitaxial growth. Flexible photodetectors are fabricated based on the epitaxial $β$-Ga$_2$O$_3$ coated tapes. Measurements show that the obtained photodetectors have a responsivity of 40 mA/W, with an on/off ratio reaching 1000 under 250 nm incident light and 5 V bias voltage. Such photoelectrical performance is already within the mainstream level of the $β$-Ga$_2$O$_3$ based photodetectors by using the conventional rigid single crystal substrates; and more importantly remained robust against more than 1000 cycles of bending tests. In addition, the epitaxy technique described in the report also paves the way for the fabrication of a wide range of flexible epitaxial film devices that utilize the materials with lattice parameters similar to $β$-Ga$_2$O$_3$, including GaN, AlN and SiC.

physics.app-ph↗

arXiv2020

GrabAR: Occlusion-aware Grabbing Virtual Objects in AR

Existing augmented reality (AR) applications often ignore occlusion between real hands and virtual objects when incorporating virtual objects in our views. The challenges come from the lack of accurate depth and mismatch between real and virtual depth. This paper presents GrabAR, a new approach that directly predicts the real-and-virtual occlusion, and bypasses the depth acquisition and inference. Our goal is to enhance AR applications with interactions between hand (real) and grabbable objects (virtual). With paired images of hand and object as inputs, we formulate a neural network that learns to generate the occlusion mask. To train the network, we compile a synthetic dataset to pre-train it and a real dataset to fine-tune it, thus reducing the burden of manual labels and addressing the domain difference. Then, we embed the trained network in a prototyping AR system that supports hand grabbing of various virtual objects, demonstrate the system performance, both quantitatively and qualitatively, and showcase interaction scenarios, in which we can use bare hand to grab virtual objects and directly manipulate them.

cs.GR↗

arXiv2020

Robust Magnetoelectric Effect in Decorated Graphene/In2Se3 Heterostructure

Magnetoelectric effect is a fundamental physics phenomenon that synergizes electric and magnetic degrees of freedom to generate distinct material responses like electrically tuned magnetism, which serves as a key foundation of the emerging field of spintronics. Here, we show by first-principles studies that ferroelectric (FE) polarization of an In2Se3 monolayer can modulate the magnetism of an adjacent transition-metal (TM) decorated graphene layer via an FE induced electronic transition. The TM nonbonding d-orbital shifts downward and hybridizes with carbon p states near the Fermi level, suppressing the magnetic moment, under one FE polarization, but on reversed FE polarization this TM d-orbital moves upward, restoring the original magnetic moment. This finding of robust magnetoelectric effect in TM decorated graphene/In2Se3 heterostructure offers powerful insights and a promising avenue for experimental exploration of FE controlled magnetism in 2D materials.

cond-mat.mtrl-sci↗

arXiv2019

Reversible Gas Sensing by Ferroelectric Switch and 2D Molecule Multiferroics in In2Se3 Monolayer

Two-dimensional ferroelectrics are important quantum materials which have found novel application in nonvolatile memories, however, the effects of reversible polarization on chemical reactions and interaction with environments are rarely studied despite of its importance. Here, based on the first-principles calculations, we found distinct gas adsorption behaviors on the surfaces of ferroelectric In2Se3 layer and the reversible gas caption and release controlled by ferroelectric switch. We rationalize the novel phenomena to the synergistic effect of the different electrostatic potential and electron transfer induced by band alignments between frontier molecular orbitals of gas and band edge states of substrate. Excitingly, the adsorption of paramagnetic gas molecules such as NO and NO2 can induce surface magnetism, which is also sensitive to ferroelectric polarization direction of In2Se3, indicating the application of In2Se3 as threshold magnetic sensors or switcher. Furthermore, it is suggested two NO molecules prefer to ferromagnetically couple with each other, the Curie temperature is polarization dependent which can reach up to 50K, leading to the long-sought 2D molecule multiferroics. The ferroelectric controllable adsorption behavior and molecule multiferroic feature will find extensive application in gas caption, selective catalytic reduction and spintronic device.

cond-mat.mtrl-sci↗

arXiv2018

Continuous solutions of a second order iterative equation

In this paper we study the existence of continuous solutions and their constructions for a second order iterative functional equation, which involves iterate of the unknown function and a nonlinear term. Imposing Lipschitz conditions to those given functions, we prove the existence of continuous solutions on the whole $\mathbb{R}$ by applying the contraction principle. In the case without Lipschitz conditions we hardly use the contraction principle, but we construct continuous solutions on $\mathbb{R}$ recursively with a partition of $\mathbb{R}$.

math.CA↗

arXiv2017

Ultrathin and highly passivating silica shells for luminescent and water-soluble CdSe/CdS nanorods

Microemulsion (water-in-oil) methods enable the encapsulation of individual nanoparticles into SiO2 spheres. The major drawbacks of this method, when applied for silica encapsulation of anisotropic nanorods (NRs), are a spatially unequal silica growth and long reaction times (24 h at least). In this work, various tetra-alkoxysilanes (tetramethyl orthosilicate (TMOS), tetraethyl orthosilicate (TEOS) and tetrapropyl orthosilicate (TPOS)) with different alkyl-chain lengths were used as the silica precursors in attempt to tune the silanization behavior of CdSe/CdS NRs in a microemulsion system. We find an enhanced spatial homogeneity of the silica growth with decreasing alkyl-chain length of the tetra-alkoxysilanes. In particular, by using TMOS as the precursor, NRs can be fully encapsulated in a continuous thin ($\le$ 5 nm) silica shell within only 1 h reaction time. Surprisingly, the thin silica shell showed a superior shielding ability to acidic environment even compared to the 30 nm thick shell prepared by using TEOS. Our investigations suggest that the lower steric hindrance of TMOS compared to TEOS or TPOS strongly promotes the homogeneous growth of the silica shells while its increased hydrolysis rate leads decreases the porosity of these shells.

physics.chem-ph↗

arXiv2013

A Low-Fluorine Solution with the F/Ba Mole Ratio of 2 for the Fabrication of YBCO Films

In the reported low-fluorine MOD-YBCO studies, the lowest F/Ba mole ratio of the precursor solution was 4.5. However, further lowering the F/Ba ratio is important according to the researches of YBCO thick film. On the other hand, the F/Ba ratio is necessary to be at least 2 for the full conversion of the Ba precursor to BaF_2 to avoid the formation of BaCO_3, which is detrimental to the superconducting performance. In this study, a novel solution with the F/Ba mole ratio of 2 was developed, in which the fluorine content was only about 10.3% of that used in the conventional TFA-MOD method. Attenuated total reflectance-Fourier transformed-infrared spectra(ATR-FT-IR) revealed that BaCO_3 was remarkably suppressed in the as-pyrolyzed film and eliminated at 700 Celsius degree. Thus YBCO films with a critical current density (J_c) over 5 MA cm^{-2} (77 K, 0 T, 200 nm thickness) could be obtained on LAO single crystal substrates. In-situ FT-IR spectra showed that no obvious fluorinated gaseous by-products were detected in the pyrolysis step, which indicated that all of the F atoms might remain in the film as fluorides. X-ray diffraction (XRD) θ/2θ-scan showed that BaF_2, but neither YF_3 nor CuF_2, was detected in the films quenched at 400 - 800 Celsius degree. The formation priority of BaF_2 over YF_3 and CuF_2 was interpreted by the chemical equilibrium of the potential reactions. Our study could enlarge the synthesis window of the precursor solution for MOD-YBCO fabrication and open a gate to study the fluorine content in the precursor solution continuously and systematically.

cond-mat.mtrl-sci↗

arXiv2013

Two-photon interference with continuous-wave multi-mode coherent light

We report two-photon interference with continuous-wave multi-mode coherent light. We show that the two-photon interference, in terms of the detection time difference, reveals two-photon beating fringes with the visibility $V = 0.5$. While scanning the optical delay of the interferometer, Hong-Ou-Mandel dips or peaks are measured depending on the chosen detection time difference. The HOM dips/peaks are repeated when the optical delay and the first-order coherence revival period of the multi-mode coherent light are the same.

quant-ph↗

arXiv2013

Conditions for two-photon interference with coherent pulses

We study the conditions for two-photon classical interference with coherent pulses. We find that the temporal overlap between optical pulses is not required for interference However, coherence within the same inputs is found to be essential for the interference.

quant-ph↗