arXiv subjects

Wei Lu

Publications and source records attributed to Wei Lu.

At least 271 records · Page 15Linked to original sources

arXiv2022

Blind Surveillance Image Quality Assessment via Deep Neural Network Combined with the Visual Saliency

The intelligent video surveillance system (IVSS) can automatically analyze the content of the surveillance image (SI) and reduce the burden of the manual labour. However, the SIs may suffer quality degradations in the procedure of acquisition, compression, and transmission, which makes IVSS hard to understand the content of SIs. In this paper, we first conduct an example experiment (i.e. the face detection task) to demonstrate that the quality of the SIs has a crucial impact on the performance of the IVSS, and then propose a saliency-based deep neural network for the blind quality assessment of the SIs, which helps IVSS to filter the low-quality SIs and improve the detection and recognition performance. Specifically, we first compute the saliency map of the SI to select the most salient local region since the salient regions usually contain rich semantic information for machine vision and thus have a great impact on the overall quality of the SIs. Next, the convolutional neural network (CNN) is adopted to extract quality-aware features for the whole image and local region, which are then mapped into the global and local quality scores through the fully connected (FC) network respectively. Finally, the overall quality score is computed as the weighted sum of the global and local quality scores. Experimental results on the SI quality database (SIQD) show that the proposed method outperforms all compared state-of-the-art BIQA methods.

cs.MM↗

arXiv2022

Deep Neural Network for Blind Visual Quality Assessment of 4K Content

The 4K content can deliver a more immersive visual experience to consumers due to the huge improvement of spatial resolution. However, existing blind image quality assessment (BIQA) methods are not suitable for the original and upscaled 4K contents due to the expanded resolution and specific distortions. In this paper, we propose a deep learning-based BIQA model for 4K content, which on one hand can recognize true and pseudo 4K content and on the other hand can evaluate their perceptual visual quality. Considering the characteristic that high spatial resolution can represent more abundant high-frequency information, we first propose a Grey-level Co-occurrence Matrix (GLCM) based texture complexity measure to select three representative image patches from a 4K image, which can reduce the computational complexity and is proven to be very effective for the overall quality prediction through experiments. Then we extract different kinds of visual features from the intermediate layers of the convolutional neural network (CNN) and integrate them into the quality-aware feature representation. Finally, two multilayer perception (MLP) networks are utilized to map the quality-aware features into the class probability and the quality score for each patch respectively. The overall quality index is obtained through the average pooling of patch results. The proposed model is trained through the multi-task learning manner and we introduce an uncertainty principle to balance the losses of the classification and regression tasks. The experimental results show that the proposed model outperforms all compared BIQA metrics on four 4K content quality assessment databases.

cs.MM↗

arXiv2022

Injection induced by coaxial laser interference in laser wakefield accelerators

A new injection scheme using the interference of two coaxial laser pulses is proposed for generating high quality beams in laser wakefield accelerators. In this scheme, a relatively loosely focused laser pulse drives the plasma wakefield, and a tightly focused laser pulse with similar intensity triggers interference ring pattern which creates onion-like multi sheaths in the plasma wakefield. Due to the wavefront curvature change after the focal position of the tightly focused laser, the innermost sheath of the wakefield expands, which slows down the effective phase velocity of the wakefield and triggers injection of plasma electrons. Particle-in-cell simulations show that high quality electron beams with low energy spread (a few per mill), high charge (hundred picocoulomb) and small emittance (sub millimeter milliradian) at the same time can be generated using moderate laser parameters for properly chosen phase differences between the two lasers.

physics.plasm-ph↗

arXiv2022

ADT-SSL: Adaptive Dual-Threshold for Semi-Supervised Learning

Semi-Supervised Learning (SSL) has advanced classification tasks by inputting both labeled and unlabeled data to train a model jointly. However, existing SSL methods only consider the unlabeled data whose predictions are beyond a fixed threshold (e.g., 0.95), ignoring the valuable information from those less than 0.95. We argue that these discarded data have a large proportion and are usually of hard samples, thereby benefiting the model training. This paper proposes an Adaptive Dual-Threshold method for Semi-Supervised Learning (ADT-SSL). Except for the fixed threshold, ADT extracts another class-adaptive threshold from the labeled data to take full advantage of the unlabeled data whose predictions are less than 0.95 but more than the extracted one. Accordingly, we engage CE and $L_2$ loss functions to learn from these two types of unlabeled data, respectively. For highly similar unlabeled data, we further design a novel similar loss to make the prediction of the model consistency. Extensive experiments are conducted on benchmark datasets, including CIFAR-10, CIFAR-100, and SVHN. Experimental results show that the proposed ADT-SSL achieves state-of-the-art classification accuracy.

cs.CV↗

arXiv2022

The Optimal Beam-loading in Two-bunch Nonlinear Plasma Wakefield Accelerators

Due to the highly nonlinear nature of the beam-loading, it is at present not possible to analytically determine the beam parameters needed in a two-bunch plasma wakefield accelerator for maintaining a low energy spread. Therefore in this paper, by using the Broyden-Fletcher-Goldfarb-Shanno algorithm for the parameter scanning with the code QuickPIC and the polynomial regression together with k-fold cross-validation method, we obtain two fitting formulas for calculating the parameters of tri-Gaussian electron beams when minimizing the energy spread based on the beam-loading effect in a nonlinear plasma wakefield accelerator. One formula allows the optimization of the normalized charge per unit length of a trailing beam to achieve the minimal energy spread, i.e. the optimal beam-loading. The other one directly gives the transformer ratio when the trailing beam achieves the optimal beam-loading. A simple scaling law for charges of drive beams and trailing beams is obtained from the fitting formula, which indicates that the optimal beam-loading is always achieved for a given charge ratio of the two beams when the length and separation of two beams and the plasma density are fixed. The formulas can also help obtain the optimal plasma densities for the maximum accelerated charge and the maximum acceleration efficiency under the optimal beam-loading respectively. These two fitting formulas will significantly enhance the efficiency for designing and optimizing a two-bunch plasma wakefield acceleration stage.

physics.plasm-ph↗

arXiv2022

Implicit N-grams Induced by Recurrence

Although self-attention based models such as Transformers have achieved remarkable successes on natural language processing (NLP) tasks, recent studies reveal that they have limitations on modeling sequential transformations (Hahn, 2020), which may prompt re-examinations of recurrent neural networks (RNNs) that demonstrated impressive results on handling sequential data. Despite many prior attempts to interpret RNNs, their internal mechanisms have not been fully understood, and the question on how exactly they capture sequential features remains largely unclear. In this work, we present a study that shows there actually exist some explainable components that reside within the hidden states, which are reminiscent of the classical n-grams features. We evaluated such extracted explainable features from trained RNNs on downstream sentiment analysis tasks and found they could be used to model interesting linguistic phenomena such as negation and intensification. Furthermore, we examined the efficacy of using such n-gram components alone as encoders on tasks such as sentiment analysis and language modeling, revealing they could be playing important roles in contributing to the overall performance of RNNs. We hope our findings could add interpretability to RNN architectures, and also provide inspirations for proposing new architectures for sequential data.

cs.CL↗

arXiv2022

High average power ultrafast laser technologies for driving future advanced accelerators

Large scale laser facilities are needed to advance the energy frontier in high energy physics and accelerator physics. Laser plasma accelerators are core to advanced accelerator concepts aimed at reaching TeV electron electron colliders. In these facilities, intense laser pulses drive plasmas and are used to accelerate electrons to high energies in remarkably short distances. A laser plasma accelerator could in principle reach high energies with an accelerating length that is 1000 times shorter than in conventional RF based accelerators. Notionally, laser driven particle beam energies could scale beyond state of the art conventional accelerators. LPAs have produced multi GeV electron beams in about 20 cm with relative energy spread of about 2 percent, supported by highly developed laser technology. This validates key elements of the US DOE strategy for such accelerators to enable future colliders but extending best results to date to a TeV collider will require lasers with higher average power. While the per pulse energies envisioned for laser driven colliders are achievable with current lasers, low laser repetition rates limit potential collider luminosity. Applications will require rates of kHz to tens of kHz at Joules of energy and high efficiency, and a collider would require about 100 such stages, a leap from current Hz class LPAs. This represents a challenging 1000 fold increase in laser repetition rates beyond current state of the art. This whitepaper describes current research and outlook for candidate laser systems as well as the accompanying broadband and high damage threshold optics needed for driving future advanced accelerators.

physics.acc-ph↗

arXiv2022

No-Reference Quality Assessment for 3D Colored Point Cloud and Mesh Models

To improve the viewer's Quality of Experience (QoE) and optimize computer graphics applications, 3D model quality assessment (3D-QA) has become an important task in the multimedia area. Point cloud and mesh are the two most widely used digital representation formats of 3D models, the visual quality of which is quite sensitive to lossy operations like simplification and compression. Therefore, many related studies such as point cloud quality assessment (PCQA) and mesh quality assessment (MQA) have been carried out to measure the visual quality degradations of 3D models. However, a large part of previous studies utilize full-reference (FR) metrics, which indicates they can not predict the quality level with the absence of the reference 3D model. Furthermore, few 3D-QA metrics consider color information, which significantly restricts their effectiveness and scope of application. In this paper, we propose a no-reference (NR) quality assessment metric for colored 3D models represented by both point cloud and mesh. First, we project the 3D models from 3D space into quality-related geometry and color feature domains. Then, the 3D natural scene statistics (3D-NSS) and entropy are utilized to extract quality-aware features. Finally, machine learning is employed to regress the quality-aware features into visual quality scores. Our method is validated on the colored point cloud quality assessment database (SJTU-PCQA), the Waterloo point cloud assessment database (WPC), and the colored mesh quality assessment database (CMDM). The experimental results show that the proposed method outperforms most compared NR 3D-QA metrics with competitive computational resources and greatly reduces the performance gap with the state-of-the-art FR 3D-QA metrics. The code of the proposed model is publicly available now to facilitate further research.

cs.CV↗

arXiv2022

Ultra-Bright Electron Bunch Injection in a Plasma Wakefield Driven by a Superluminal Flying Focus Electron Beam

We propose a new method for self-injection of high-quality electron bunches in the plasma wakefield structure in the blowout regime utilizing a "flying focus" produced by a drive beam with an energy chirp. In a flying focus the speed of the density centroid of the drive bunch can be superluminal or subluminal by utilizing the chromatic dependence of the focusing optics. We first derive the focal velocity and the characteristic length of the focal spot in terms of the focal length and an energy chirp. We then demonstrate using multidimensional particle-in-cell simulations that a wake driven by a superluminally propagating flying focus of an electron beam can generate GeV-level electron bunches with ultralow normalized slice emittance ($\sim$30 nm rad), high current ($\sim$ 17 kA), low slice energy-spread ($\sim$0.1%) and therefore high normalized brightness ($>10^{19}$ A/rad$^2$/m$^2$) in a plasma of density $\sim10^{19}$ cm$^{-3}$. The injection process is highly controllable and tunable by changing the focal velocity and shaping the drive beam current. Near-term experiments at FACET II where the capabilities to generate tens of kA, <10 fs drivers are planned, could potentially produce beams with brightness near $10^{20}$ A/rad$^2$/m$^2$.

physics.plasm-ph↗

arXiv2022

Efficient Generation of Tunable Magnetic and Optical Vortices Using Plasmas

Plasma is an attractive medium for generating strong microscopic magnetic structures and tunable electromagnetic radiation with predictable topologies due to its extraordinary ability to sustain and manipulate high currents and strong fields. Here, using theory and simulations, we show efficient generation of multi-megagauss magnetic and tunable optical vortices when a sharp relativistic ionization front (IF) passes through a relatively long-wavelength Laguerre-Gaussian (LG) laser pulse with orbital angular momentum (OAM). The optical vortex is frequency upshifted within a wide spectral range simply by changing the plasma density and compressed in duration. The topological charges of both vortices can be manipulated by controlling the OAM mode of the incident LG laser and/or by controlling the topology and density of the IF. For relatively high (low) plasma densities, most energy of the incident LG laser pulse is converted to the magnetic (optical) vortex.

physics.plasm-ph↗

arXiv2022

Electron Weibel instability induced magnetic fields in optical-field ionized plasmas

Generation and amplification of magnetic fields in plasmas is a long-standing topic that is of great interest to both plasma and space physics. The electron Weibel instability is a well-known mechanism responsible for self-generating magnetic fields in plasmas with temperature anisotropy and has been extensively investigated in both theory and simulations, yet experimental verification of this instability has been challenging. Recently, we demonstrated a new experimental platform that enables the controlled initialization of highly nonthermal and/or anisotropic plasma electron velocity distributions via optical-field ionization. Using an external electron probe bunch from a linear accelerator, the onset, saturation and decay of the self-generated magnetic fields due to electron Weibel instability were measured for the first time to our knowledge. In this paper, we will first present experimental results on time-resolved measurements of the Weibel magnetic fields in non-relativistic plasmas produced by Ti:Sapphire laser pulses (0.8 $μm$) and then discuss the feasibility of extending the study to quasi-relativistic regime by using intense $\rm CO_2$ (e.g., 9.2 $μm$) lasers to produce much hotter plasmas.

physics.plasm-ph↗

arXiv2022

Mapping the self-generated magnetic fields due to thermal Weibel instability

Weibel-type instability can self-generate and amplify magnetic fields in both space and laboratory plasmas with temperature anisotropy. The electron Weibel instability has generally proven more challenging to measure than its ion counterpart owing to the much smaller inertia of electrons, resulting in a faster growth rate and smaller characteristic wavelength. Here, we have probed the evolution of the two-dimensional distribution of the magnetic field components and the current density due to electron Weibel instability, in $\rm CO_2$-ionized hydrogen gas (plasma) with picosecond resolution using a relativistic electron beam. We find that the wavenumber spectra of the magnetic fields are initially broad but eventually shrink to a narrow spectrum representing the dominant quasi-single mode. The measured $k$-resolved growth rates of the instability validate kinetic theory. Concurrently, self-organization of microscopic plasma currents is observed to amplify the current modulation magnitude that converts up to $\sim 1\%$ of the plasma thermal energy into magnetic energy.

physics.plasm-ph↗

arXiv2022

Expected Constant Time Self-stabilizing Byzantine Pulse Resynchronization

In extending fast digital clock synchronization to the bounded-delay model, the expected constant time Byzantine pulse resynchronization problem is investigated. In this problem, the synchronized state of the system should not only be deterministically maintained but be reached from arbitrary states with expected constant time in the presence of Byzantine faults. An intuitive geometric representation of the problem is introduced, with which the classical approximate agreement, randomized Byzantine agreement, and random walk are integrated with some geometric operations. Efficient realizations are also provided for practical uses. Compared with the state-of-the-art solutions, the assumed common pulses need not be regularly generated, the message complexity can be lowered as approximate agreement, and the expected stabilization time is optimal. With this, the provided solution can efficiently convert irregularly generated common pulses to self-stabilizing Byzantine pulse synchronization.

cs.DC↗

arXiv2022

On the use of multilayer Laue lenses with X-ray Free Electron Lasers

Multilayer Laue lenses were used for the first time to focus x-rays from an X-ray Free Electron Laser (XFEL). In an experiment, which was performed at the European XFEL, we demonstrated focusing to a spot size of a few tens of nanometers. A series of runs in which the number of pulses per train was increased from 1 to 2, 3, 4, 5, 6, 7, 10, 20 and 30 pulses per train, all with a pulse separation of 3.55 us, was done using the same set of lenses. The increase in the number of pulses per train was accompanied with an increase of x-ray intensity (transmission) from 9% to 92% at 5 pulses per train, and then the transmission was reduced to 23.5 % when the pulses were increased further. The final working condition was 30 pulses per train and 23.5% transmission. Only at this condition we saw that the diffraction efficiency of the MLLs changed over the course of a pulse train, and this variation was reproducible from train to train. We present the procedure to align and characterize these lenses and discuss challenges working with the pulse trains from this unique x-ray source.

physics.acc-ph↗

arXiv2022

Intro-Stabilizing Byzantine Clock Synchronization in Heterogeneous IoT Networks

For reaching dependable high-precision clock synchronization (CS) upon IoT networks, the distributed CS paradigm adopted in ultra-high reliable systems and the master-slave CS paradigm adopted in high-performance but unreliable systems are integrated. Meanwhile, traditional internal clock synchronization is also integrated with external time references to achieve efficient stabilization. Low network connectivity, low complexity, high precision, and high reliability are all considered. To tolerate permanent failures, the Byzantine CS is integrated with the common CS protocols. To tolerate transient failures, the self-stabilizing Byzantine CS is also extended upon open-world IoT networks. With these, the proposed intro-stabilizing Byzantine CS solution can establish and maintain synchronization with arbitrary initial states in the presence of permanent Byzantine faults. With the formal analysis and numerical simulations, it is shown that the best of the CS solutions provided for the ultra-high reliable systems and the high-performance unreliable systems can be well integrated upon IoT networks to derive dependable high-precision CS even across the traditional closed safety-boundary.

cs.DC↗

arXiv2022

Modeling Needs for High Power Target

The next generation of high power targets will use more complex geometries, novel materials, and new concepts (like flowing granular materials); however, the current numerical approaches will not be sufficient to converge towards a reliable target design that satisfies the physical requirements. We will discuss what can be improved in the next 10 years in target modeling to support high power (MW class) targets.

physics.acc-ph↗

arXiv2022

Reaching Efficient Byzantine Agreements in Bipartite Networks

For reaching efficient deterministic synchronous Byzantine agreement upon partially connected networks, the traditional broadcast primitive is extended and integrated with a general framework. With this, the Byzantine agreement is extended to fully connected bipartite networks and some bipartite bounded-degree networks. The complexity of the Byzantine agreement is lowered and optimized with the so-called Byzantine-levers under a general system structure. Some bipartite simulation of the butterfly networks and some finer properties of bipartite bounded-degree networks are also provided for building efficient incomplete Byzantine agreement under the same system structure. It shows that efficient real-world Byzantine agreement systems can be built with the provided algorithms with sufficiently high system assumption coverage. Meanwhile, the proposed bipartite solutions can improve the dependability of the systems in some open, heterogeneous, and even antagonistic environments.

cs.DC↗

arXiv2022

A New Fault-Tolerant Synchronization Scheme with Anonymous Pulses

Robust pulse synchronization is fundamental in constructing reliable synchronous applications in wired and wireless distributed systems. In wired systems, self-stabilizing Byzantine pulse synchronization aims for synchronizing fault-prone distributed components with arbitrary initial states in bounded-delay message-passing systems. In wireless systems, fault-tolerant synchronization of pulse-coupled oscillators is also built for a similar goal but often works under specific system restrictions, such as low computation power, low message complexity, and anonymous physical pulses whose senders cannot be identified by the receivers. These restrictions often prevent us from constructing high-reliable wireless synchronous applications. This paper tries to break barriers between bounded-delay message-passing systems and classical pulse-coupled oscillators by introducing a new fault-tolerant synchronization scheme for the so-called anonymous bounded-delay pulsing systems in the presence of indeterministic communication delays and inconsistent faults. For low computation power and low message complexity, instead of involving in consensus-based primitives, the proposed synchronization scheme integrates the so-called discrete mean-fields, planar random walks, and some additional easy operations in utilizing only sparsely generated anonymous pulses. For fault-tolerance, we show that a square-root number of faulty oscillators can be tolerated by utilizing planar random walks in anonymous pulse synchronization. For self-stabilization, we show that the stabilization can be reached in an expected constant number of observing windows in anonymous bounded-delay pulsing systems with the pulsing-frequency restriction.

cs.DC↗