arXiv subjects

Di Wu

Publications and source records attributed to Di Wu.

At least 667 records · Page 37Linked to original sources

arXiv2018

Quantitative Measurements of Nanoscale Permittivity and Conductivity Using Tuning-fork-based Microwave Impedance Microscopy

We report quantitative measurements of nanoscale permittivity and conductivity using tuning-fork (TF) based microwave impedance microscopy (MIM). The system is operated under the driving amplitude modulation mode, which ensures satisfactory feedback stability on samples with rough surfaces. The demodulated MIM signals on a series of bulk dielectrics are in good agreement with results simulated by finite-element analysis. Using the TF-MIM, we have visualized the evolution of nanoscale conductance on back-gated $MoS_2$ field effect transistors and the results are consistent with the transport data. Our work suggests that quantitative analysis of mesoscopic electrical properties can be achieved by near-field microwave imaging with small distance modulation.

physics.app-ph↗

arXiv2018

Blow-up criterion and examples of global solutions of forced Navier-Stokes equations

In this paper we first show a blow-up criterion for solutions to the Navier-Stokes equations with a time-independent force by using the profile decomposition method. Based on the orthogonal properties related to the profiles, we give some examples of global solutions to the Navier-Stokes equations with a time-independent force, whose initial data are large.

math.AP↗

arXiv2018

Generalized Short Circuit Ratio for Multi Power Electronic based Devices Infeed Systems: Defi-nition and Theoretical Analysis

Short circuit ratio (SCR) is widely applied to analyze the strength of AC system and the small signal stability for single power elec-tronic based devices infeed systems (SPEISs). However, there still lacking the theory of short circuit ratio applicable for multi power electronic based devices infeed systems (MPEIS), as the complex coupling among multi power electronic devices (PEDs) leads to difficulties in stability analysis. In this regard, this paper firstly proposes a concept named generalized short circuit ratio (gSCR) to measure the strength of connected AC grid in a multi-infeed system from the small signal stability point of view. Generally, the gSCR is physically and mathematically extended from conven-tional SCR by decomposing the multi-infeed system into n inde-pendent single infeed systems. Then the operation gSCR (OgSCR) is proposed based on gSCR in order to take the variation of op-eration point into consideration. The participation factors and sensitivity are analyzed as well. Finally, simulations are conducted to demonstrate the rationality and effectiveness of the defined gSCR and OgSCR.

eess.SY↗

arXiv2018

Probing Primordial Gravitational Waves: Ali CMB Polarization Telescope

In this paper, we will give a general introduction to the project of Ali CMB Polarization Telescope (AliCPT), which is a Sino-US joint project led by the Institute of High Energy Physics (IHEP) and has involved many different institutes in China. It is the first ground-based Cosmic Microwave Background (CMB) polarization experiment in China and an integral part of China's Gravitational Waves Program. The main scientific goal of AliCPT project is to probe the primordial gravitational waves (PGWs) originated from the very early Universe. The AliCPT project includes two stages. The first stage referred to as AliCPT-1, is to build a telescope in the Ali region of Tibet with an altitude of 5,250 meters. Once completed, it will be the worldwide highest ground-based CMB observatory and open a new window for probing PGWs in northern hemisphere. AliCPT-1 telescope is designed to have about 7,000 TES detectors at 90GHz and 150GHz. The second stage is to have a more sensitive telescope (AliCPT-2) with the number of detectors more than 20,000. Our simulations show that AliCPT will improve the current constraint on the tensor-to-scalar ratio $r$ by one order of magnitude with 3 years' observation. Besides the PGWs, the AliCPT will also enable a precise measurement on the CMB rotation angle and provide a precise test on the CPT symmetry. We show 3 years' observation will improve the current limit by two order of magnitude.

astro-ph.CO↗

arXiv2018

IoT Security Techniques Based on Machine Learning

Internet of things (IoT) that integrate a variety of devices into networks to provide advanced and intelligent services have to protect user privacy and address attacks such as spoofing attacks, denial of service attacks, jamming and eavesdropping. In this article, we investigate the attack model for IoT systems, and review the IoT security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning. We focus on the machine learning based IoT authentication, access control, secure offloading and malware detection schemes to protect data privacy. In this article, we discuss the challenges that need to be addressed to implement these machine learning based security schemes in practical IoT systems.

cs.CR↗

arXiv2017

Machine Learning for Building Energy and Indoor Environment: A Perspective

Machine learning is a promising technique for many practical applications. In this perspective, we illustrate the development and application for machine learning. It is indicated that the theories and applications of machine learning method in the field of energy conservation and indoor environment are not mature, due to the difficulty of the determination for model structure with better prediction. In order to significantly contribute to the problems, we utilize the ANN model to predict the indoor culturable fungi concentration, which achieves the better accuracy and convenience. The proposal of hybrid method is further expand the application fields of machine learning method. Further, ANN model based on HTS was successfully applied for the optimization of building energy system. We hope that this novel method could capture more attention from investigators via our introduction and perspective, due to its potential development with accuracy and reliability. However, its feasibility in other fields needs to be promoted further.

cs.CY↗

arXiv2017

Learning-Based Computation Offloading for IoT Devices with Energy Harvesting

Internet of Things (IoT) devices can apply mobile-edge computing (MEC) and energy harvesting (EH) to provide the satisfactory quality of experiences for computation intensive applications and prolong the battery lifetime. In this article, we investigate the computation offloading for IoT devices with energy harvesting in wireless networks with multiple MEC devices such as base stations and access points, each with different computation resource and radio communication capability. We propose a reinforcement learning based computation offloading framework for an IoT device to choose the MEC device and determine the offloading rate according to the current battery level, the previous radio bandwidth to each MEC device and the predicted amount of the harvested energy. A "hotbooting" Q-learning based computation offloading scheme is proposed for an IoT device to achieve the optimal offloading performance without being aware of the MEC model, the energy consumption and computation latency model. We also propose a fast deep Q-network (DQN) based offloading scheme, which combines the deep learning and hotbooting techniques to accelerate the learning speed of Q-learning. We show that the proposed schemes can achieve the optimal offloading policy after sufficiently long learning time and provide their performance bounds under two typical MEC scenarios. Simulations are performed for IoT devices that use wireless power transfer to capture the ambient radio-frequency signals to charge the IoT batteries. Simulation results show that the fast DQN-based offloading scheme reduces the energy consumption, decreases the computation delay and the task drop ratio, and increases the utility of the IoT device in dynamic MEC, compared with the benchmark Q-learning based offloading.

cs.NI↗

arXiv2017

Cauchy problem for the incompressible Navier-Stokes equation with an external force

In this paper we focus on the Cauchy problem for the incompressible Navier-Stokes equation with a rough external force. If the given rough external force is small, we prove the local-in-time existence of this system for any initial data belonging to the critical Besov space $\dot{B}_{p,p}^{-1+\frac{3}{p}}$, where $3<p<\infty$. Moreover, We show the long-time behavior of the priori global solutins constructed by us. Also, we give three kinds of uniqueness results of the forced Navier-Stokes equations.

math.AP↗

arXiv2017

Observation of spin-orbit magnetoresistance in metallic thin films on magnetic insulators

A magnetoresistance effect induced by the Rashba spin-orbit interaction was predicted, but not yet observed, in bilayers consisting of normal metal and ferromagnetic insulator. Here, we present an experimental observation of this new type of spin-orbit magnetoresistance (SOMR) effect in a bilayer structure Cu[Pt]/Y3Fe5O12 (YIG), where the Cu/YIG interface is decorated with nanosize Pt islands. This new MR is apparently not caused by the bulk spin-orbit interaction because of the negligible spin-orbit interaction in Cu and the discontinuity of the Pt islands. This SOMR disappears when the Pt islands are absent or located away from the Cu/YIG interface, therefore we can unambiguously ascribe it to the Rashba spin-orbit interaction at the interface enhanced by the Pt decoration. The numerical Boltzmann simulations are consistent with the experimental SOMR results in the angular dependence of magnetic field and the Cu thickness dependence. Our finding demonstrates the realization of the spin manipulation by interface engineering.

cond-mat.mtrl-sci↗

arXiv2017

Tailoring Semiconductor Lateral Multi-junctions for Giant Photoconductivity Enhancement

Semiconductor heterostructures have played a critical role as the enabler for new science and technology. The emergence of transition metal dichalcogenides (TMDs) as atomically thin semiconductors has opened new frontiers in semiconductor heterostructures either by stacking different TMDs to form vertical heterojunctions or by stitching them laterally to form lateral heterojunctions via direct growth. In conventional semiconductor heterostructures, the design of multi-junctions is critical to achieve carrier confinement. Analogously, we report successful synthesis of monolayer WS2/WS2(1-x)Se2x/WS2 multi-junction lateral heterostructure via direct growth by chemical vapor deposition. The grown structures are characterized by Raman, photoluminescence, and annular dark-field scanning transmission electron microscopy to determine its lateral compositional profile. More importantly, using microwave impedance microscopy, we demonstrate that the local photoconductivity in the alloy region can be tailored and enhanced by 2 orders of magnitude over pure WS2. Finite element analysis confirms that this effect is due to the carrier diffusion and confinement into the alloy region. Our work exemplifies the technological potential of atomically thin lateral heterostructures in optoelectronic applications.

cond-mat.mtrl-sci↗

arXiv2017

Sorting with GPUs: A Survey

Sorting is a fundamental operation in computer science and is a bottleneck in many important fields. Sorting is critical to database applications, online search and indexing,biomedical computing, and many other applications. The explosive growth in computational power and availability of GPU coprocessors has allowed sort operations on GPUs to be done much faster than any equivalently priced CPU. Current trends in GPU computing shows that this explosive growth in GPU capabilities is likely to continue for some time. As such, there is a need to develop algorithms to effectively harness the power of GPUs for crucial applications such as sorting.

cs.DC↗

arXiv2017

Out-of-plane Piezoelectricity and Ferroelectricity in Layered $α$-In2Se3 Nano-flakes

Piezoelectric and ferroelectric properties in the two dimensional (2D) limit are highly desired for nanoelectronic, electromechanical, and optoelectronic applications. Here we report the first experimental evidence of out-of-plane piezoelectricity and ferroelectricity in van der Waals layered $α$-In2Se3 nano-flakes. The non-centrosymmetric R3m symmetry of the $α$-In2Se3 samples is confirmed by scanning transmission electron microscopy, second-harmonic generation, and Raman spectroscopy measurements. Domains with opposite polarizations are visualized by piezo-response force microscopy. Single-point poling experiments suggest that the polarization is potentially switchable for $α$-In2Se3 nano-flakes with thicknesses down to ~ 10 nm. The piezotronic effect is demonstrated in two-terminal devices, where the Schottky barrier can be modulated by the strain-induced piezopotential. Our work on polar $α$-In2Se3, one of the model 2D piezoelectrics and ferroelectrics with simple crystal structures, shows its great potential in electronic and photonic applications.

cond-mat.mtrl-sci↗

arXiv2017

A Bayesian Risk Approach to Data-driven Stochastic Optimization: Formulations and Asymptotics

A large class of stochastic programs involve optimizing an expectation taken with respect to an underlying distribution that is unknown in practice. One popular approach to addressing the distributional uncertainty, known as the distributionally robust optimization (DRO), is to hedge against the worst case over an uncertainty set of candidate distributions. However, it has been observed that inappropriate construction of the uncertainty set can sometimes result in over-conservative solutions. To explore the middle ground between optimistically ignoring the distributional uncertainty and pessimistically fixating on the worst-case scenario, we propose a Bayesian risk optimization (BRO) framework for parametric underlying distributions, which is to optimize a risk functional applied to the posterior distribution of an unknown distribution parameter. Of our particular interest are four risk functionals: mean, mean-variance, value-at-risk, and conditional value-at-risk. To unravel the implication of BRO, we establish the consistency of objective functions and optimal solutions, as well as the asymptotic normality of objective functions and optimal values. More importantly, our analysis reveals a hidden interpretation: the objectives of BRO can be approximately viewed as a weighted sum of posterior mean objective and the (squared) half-width of the true objective's confidence interval.

math.OC↗

arXiv2017

Kernalised Multi-resolution Convnet for Visual Tracking

Visual tracking is intrinsically a temporal problem. Discriminative Correlation Filters (DCF) have demonstrated excellent performance for high-speed generic visual object tracking. Built upon their seminal work, there has been a plethora of recent improvements relying on convolutional neural network (CNN) pretrained on ImageNet as a feature extractor for visual tracking. However, most of their works relying on ad hoc analysis to design the weights for different layers either using boosting or hedging techniques as an ensemble tracker. In this paper, we go beyond the conventional DCF framework and propose a Kernalised Multi-resolution Convnet (KMC) formulation that utilises hierarchical response maps to directly output the target movement. When directly deployed the learnt network to predict the unseen challenging UAV tracking dataset without any weight adjustment, the proposed model consistently achieves excellent tracking performance. Moreover, the transfered multi-reslution CNN renders it possible to be integrated into the RNN temporal learning framework, therefore opening the door on the end-to-end temporal deep learning (TDL) for visual tracking.

cs.CV↗

arXiv2017

A Survey on Monochromatic Connections of Graphs

The concept of monochromatic connection of graphs was introduced by Caro and Yuster in 2011. Recently, a lot of results have been published about it. In this survey, we attempt to bring together all the results that dealt with it. We begin with an introduction, and then classify the results into the following categories: monochromatic connection coloring of edge-version, monochromatic connection coloring of vertex-version, monochromatic index, monochromatic connection coloring of total-version.

math.CO↗

arXiv2017

Exploiting Massive D2D Collaboration for Energy-Efficient Mobile Edge Computing

In this article we propose a novel Device-to-Device (D2D) Crowd framework for 5G mobile edge computing, where a massive crowd of devices at the network edge leverage the network-assisted D2D collaboration for computation and communication resource sharing among each other. A key objective of this framework is to achieve energy-efficient collaborative task executions at network-edge for mobile users. Specifically, we first introduce the D2D Crowd system model in details, and then formulate the energy-efficient D2D Crowd task assignment problem by taking into account the necessary constraints. We next propose a graph matching based optimal task assignment policy, and further evaluate its performance through extensive numerical study, which shows a superior performance of more than 50% energy consumption reduction over the case of local task executions. Finally, we also discuss the directions of extending the D2D Crowd framework by taking into variety of application factors.

cs.NI↗

arXiv2017

Hierarchical Control Framework for Integrated Coordination between DERs and Demand Response

Demand response represents a significant but largely untapped resource that can greatly enhance the flexibility and reliability of power systems. This paper proposes a hierarchical control framework to facilitate the integrated coordination between distributed energy resources and demand response. The proposed framework consists of coordination and device layers. In the coordination layer, various resource aggregations are optimally coordinated in a distributed manner to achieve the system-level objectives. In the device layer, individual resources are controlled in real time to follow the optimal power dispatch signals received from the coordination layer. For practical applications, a method is presented to determine the utility functions of controllable loads by accounting for the real-time load dynamics and the preferences of individual customers. The effectiveness of the proposed framework is validated by detailed simulation studies.

math.OC↗

arXiv2016

Interfacial Control of Dzyaloshinskii Moriya Interaction in Heavy Metal_Ferromagnetic Metal Thin Film Heterostructures

The interfacial Dzyaloshinskii Moriya Interaction (DMI) in ultrathin magnetic thin film heterostructures provides a new approach for controlling spin textures on mesoscopic length scales. Here we investigate the dependence of the interfacial DMI constant D on a Pt wedge insertion layer in Ta_CoFeB_Pt(wedge)_MgO thin films by observing the asymmetric spin wave dispersion using Brillouin light scattering. Continuous tuning of D by more than a factor of three is realized by inserting less than one monolayer of Pt. The observations provide new insights for designing magnetic thin film heterostructures with tailored D for controlling skyrmions and magnetic domain wall chirality and dynamics.

cond-mat.mtrl-sci↗