arXiv subjects

Qian Wu

Publications and source records attributed to Qian Wu.

At least 37 records · Page 2Linked to original sources

arXiv2024

In-Orbit Processing or Not? Sunlight-Aware Task Scheduling for Energy-Efficient Space Edge Computing Networks

With the rapid evolution of space-borne capabilities, space edge computing (SEC) is becoming a new computation paradigm for future integrated space and terrestrial networks. Satellite edges adopt advanced on-board hardware, which not only enables new opportunities to perform complex intelligent tasks in orbit, but also involves new challenges due to the additional energy consumption in power-constrained space environment. In this paper, we present PHOENIX, an energy-efficient task scheduling framework for emerging SEC networks. PHOENIX exploits a key insight that in the SEC network, there always exist a number of sunlit edges which are illuminated during the entire orbital period and have sufficient energy supplement from the sun. PHOENIX accomplishes energy-efficient in-orbit computing by judiciously offloading space tasks to "sunlight-sufficient" edges or to the ground. Specifically, PHOENIX first formulates the SEC battery energy optimizing (SBEO) problem which aims at minimizing the average battery energy consumption while satisfying various task completion constraints. Then PHOENIX incorporates a sunlight-aware scheduling mechanism to solve the SBEO problem and schedule SEC tasks efficiently. Finally, we implement a PHOENIX prototype and build an SEC testbed. Extensive data-driven evaluations demonstrate that as compared to other state-of-the-art solutions, PHOENIX can effectively reduce up to 54.8% SEC battery energy consumption and prolong battery lifetime to 2.9$\times$ while still completing tasks on time.

cs.NI↗

arXiv2024

SKYCASTLE: Taming LEO Mobility to Facilitate Seamless and Low-latency Satellite Internet Services

Emerging integrated space and terrestrial networks (ISTN) built upon low earth orbit (LEO) satellite constellations aim at providing planet-wide Internet services, not only for residential users, but also for mobile users (e.g., in airplane and cruise scenarios). Efficiently managing global mobility and keeping connections active for mobile users is critical for ISTN operators. However, our quantitative analysis identifies that existing mobility management (MM) schemes suffer from frequent connection interruptions and long latency in ISTN scenarios. The fundamental challenge stems from a unique characteristic of ISTNs: not only users are mobile, but also core network infrastructures (i.e., LEO satellites) are frequently changing their locations in the network. To facilitate seamless and low-latency satellite Internet services, this paper presents SKYCASTLE, a novel network-based global mobility management mechanism. SKYCASTLE incorporates two key techniques to address frequent connection interruptions in ISTNs. First, to reduce the interruption time, SKYCASTLE adopts distributed satellite anchors to track the location changes of mobile nodes, manage handovers and avoid routing convergence. Second, SKYCASTLE leverages an anchor manager to schedule MM functionalities at satellites to reduce deployment costs while guaranteeing low latency. Extensive evaluations combining real constellation information and mobile user trajectories show that: SKYCASTLE can improve up to 55.8% uninterrupted time and reduce 47.8% latency as compared to other existing MM solutions.

cs.NI↗

arXiv2024

Your Mega-Constellations Can Be Slim:A Cost-Effective Approach for Constructing Survivable and Performant LEO Satellite Networks

In this paper, we investigate an important research problem facing the upcoming satellite Internet: from a network perspective, how many satellites exactly do we need to construct a survivable and performant LSN? To answer this question, we first formulate the survivable and performant LSN design (SPLD) problem, which aims to find the minimum number of needed satellites to construct an LSN that can provide sufficient amount of redundant paths, required link capacity and acceptable latency for traffic carried by the LSN. Second, to efficiently solve the tricky SPLD problem, we propose MEGAREDUCE, a requirement-driven constellation optimization mechanism, which can calculate feasible solutions for SPLD in polynomial time. Finally, we conduct extensive trace-driven simulations to verify MEGAREDUCE's cost-effectiveness in constructing survivable and performant LSNs on demand, and showcase how MEGAREDUCE can help optimize the incremental deployment and long-term maintenance of future satellite Internet.

cs.NI↗

arXiv2024

Instability of Self-Driving Satellite Mega-Constellation: From Theory to Practical Impacts on Network Lifetime and Capacity

Low Earth Orbit (LEO) satellite mega-constellations aim to enable high-speed Internet for numerous users anywhere on Earth. To safeguard their network infrastructure in congested outer space, they perform automatic orbital maneuvers to avoid collisions with external debris and satellites. However, our control-theoretic analysis and empirical validation using Starlink's space situational awareness datasets discover that, these safety-oriented maneuvers themselves can threaten safety and networking via cascaded collision avoidance inside the mega-constellation. This domino effect forces a dilemma between long-term LEO network lifetime and short-term LEO network capacity. Its root cause is that, the decades-old local pairwise maneuver paradigm for standalone satellites is inherently unstable if scaled out to recent mega-constellation networks. We thus propose an alternative bilateral maneuver control that stabilizes self-driving mega-constellations for concurrent network lifetime and capacity boosts. Our operational trace-driven emulation shows a 8$\times$ network lifetime extension in Starlink without limiting its network capacity.

cs.NI↗

arXiv2024

Volumic deformation of human cornea under pressure

The cornea, as the outer element of the human eye, plays a pivotal role in vision. Any defects in its shape can result in visual impairments. Mechanical defect manifest as shape defects, as the cornea is under to pressure. Our study presents the first comprehensive observation of human corneal deformation throughout its entire thickness during an inflation test, through Optical Coherence Tomography (OCT). Horizontal deformation reveals depth-dependent heterogeneity, suggesting that the cornea's posterior part is softer than the anterior part. Vertical deformation was observed at levels significantly higher than expected and exhibited depth-dependent heterogeneity, delineating three distinct regions. The central region of the cornea initially experienced rapid swelling, possibly due to osmotic effects, followed by increasing compressions as pressure rose. Conversely, the anterior and posterior regions showed no sign of swelling, and a difference in the compressive response, possibly due to difference in stiffness. Our study shows the complexity of human corneal mechanics, highlighting strong anisotropy and depth-dependent behavior, and implicating osmotic and poroelastic properties.

physics.med-ph↗

arXiv2024

Smart patterning for topological pumping of elastic surface waves

Topological pumping supplies a robust mechanism to steer waves across a sample without being affected by disorders and defects. For the first time, we demonstrate the pumping of elastic surface waves, achieved by a smart patterning of a surface that creates a synthetic dimension, which is explored by the wave as it is launched perpendicularly to the steering direction. Specifically, we design and fabricate an elastic medium decorated with arrays of pillar-type resonators whose eigenmodes are locate below the sound cone, together with coupling bridges edged according to a specific algorithm. We establish a connection between the collective dynamics of the pillars and that of electrons in a magnetic field by deriving an accurate tight-binding model and developing a WKB-type analysis suitable for such discrete aperiodic systems with spatially slow-varying couplings. This enable us to predict topological pumping pattern, which is numerically and experimentally demonstrated by steering waves from one edge of the system to the other. Finally, the immune character of the topologically pumped surface waves against disorder and defects is evidenced. The principle of surface patterning together with the WKB-analysis could provide a powerful new platform for surface wave control and exploration of topological matter in higher dimensions.

physics.app-ph↗

arXiv2024

Tractable $T$-matix model for reaction processes in muon catalyzed fusion $(dtμ)_{J=v=0} \to \; α+ n + μ+ 17.6\, {\rm MeV} \; \mbox{or} \; (αμ)_{nl} + n +17.6 \,{\rm MeV}$

Reaction processes in muon catalyzed fusion ($μ$CF), $(dtμ)_{J=v=0} \to α+ n + μ+ 17.6\,{\rm MeV}\:$ or $ \;(αμ)_{nl} + n + 17.6\,{\rm MeV}$ in the D-T mixture was comprehensively studied by Kamimura, Kino and Yamashita [Phys. Rev. C 107, 034607 (2023)] by solving the $dtμ$-$αnμ$ coupled channel (CC) Schrödinger equation under a boundary condition where the muonic molecule $(dtμ)_{J=v=0}$ was set as the initial state and the outgoing wave was in the $αnμ$ channel. We approximate this CC framework and propose a considerably more tractable model using the $T$-matrix method based on the Lippmann-Schwinger equation. Nuclear interactions adopted in the $T$-matrix model are determined by reproducing the cross section of the reaction $d + t \to α+ n + 17.6\,{\rm MeV}$ at low energies. The cross section of the strong-coupling rearrangement reaction is presented in a simple closed form based on our new model. This $T$-matrix model have reproduced most of the calculated results on the above $μ$CF reaction reported by Kamimura et al. (2023) and is applicable to other $μ$CF systems such as $(ddμ)$, $(ttμ)$, $(dtμ)^*$, $(ddμ)^*$.

nucl-th↗

arXiv2024

HaltingVT: Adaptive Token Halting Transformer for Efficient Video Recognition

Action recognition in videos poses a challenge due to its high computational cost, especially for Joint Space-Time video transformers (Joint VT). Despite their effectiveness, the excessive number of tokens in such architectures significantly limits their efficiency. In this paper, we propose HaltingVT, an efficient video transformer adaptively removing redundant video patch tokens, which is primarily composed of a Joint VT and a Glimpser module. Specifically, HaltingVT applies data-adaptive token reduction at each layer, resulting in a significant reduction in the overall computational cost. Besides, the Glimpser module quickly removes redundant tokens in shallow transformer layers, which may even be misleading for video recognition tasks based on our observations. To further encourage HaltingVT to focus on the key motion-related information in videos, we design an effective Motion Loss during training. HaltingVT acquires video analysis capabilities and token halting compression strategies simultaneously in a unified training process, without requiring additional training procedures or sub-networks. On the Mini-Kinetics dataset, we achieved 75.0% top-1 ACC with 24.2 GFLOPs, as well as 67.2% top-1 ACC with an extremely low 9.9 GFLOPs. The code is available at https://github.com/dun-research/HaltingVT.

cs.CV↗

arXiv2023

Fifth Force and Hyperfine Splitting in Muonic Atoms

The potential existence of a fifth fundamental force, mediated by the X17 boson, has generated significant interest. This force can manifest itself as either a vector or pseudoscalar particle. In order to gain insight into the effective potentials produced by the X17 boson for hyperfine interactions in muonic systems, we conduct calculations for both the pseudoscalar and vector hypotheses. Our study reveals that, for muonic atoms with nuclear charge numbers ranging from 10 to 15, the energy shift associated with the fifth force can be as high as 0.61 eV. These effects have the potential to be detected through the utilization of high-precision X-ray detectors that are used to analyze the energy spectrum of muonic characteristic X-rays.

hep-ph↗

arXiv2023

Probing the existence of η^3He mesic nucleus with a few-body approach

Motivated by the two recent observations in the WASA-at-COSY detector, we investigate the $η^3$He nucleus with the $ηNNN$ few body method. We construct the effective $s$-wave energy dependent $ηN$ potential which reproduce the $ηN$ subthreshold scattering amplitude in the 2005 Green-Wycech model. It gives the $η$ separation energy and decay width of 0.19 MeV and 1.71 MeV, respectively. We also construct various sets of effective $s$-wave energy independent $ηN$ potentials where the corresponding complex scattering lengths (a) are within the range given in most theoretical models. We obtain the bound $η^3$He nucleus with decay width of about 5 MeV when a is (1.0 fm, 0.3 fm), and of about 10 MeV when a is (1.0 fm, 0.5 fm).

nucl-th↗

arXiv2023

Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head

Accurate localization of cephalometric landmarks holds great importance in the fields of orthodontics and orthognathics due to its potential for automating key point labeling. In the context of landmark detection, particularly in cephalometrics, it has been observed that existing methods often lack standardized pipelines and well-designed bias reduction processes, which significantly impact their performance. In this paper, we revisit a related task, human pose estimation (HPE), which shares numerous similarities with cephalometric landmark detection (CLD), and emphasize the potential for transferring techniques from the former field to benefit the latter. Motivated by this insight, we have developed a robust and adaptable benchmark based on the well-established HPE codebase known as MMPose. This benchmark can serve as a dependable baseline for achieving exceptional CLD performance. Furthermore, we introduce an upscaling design within the framework to further enhance performance. This enhancement involves the incorporation of a lightweight and efficient super-resolution module, which generates heatmap predictions on high-resolution features and leads to further performance refinement, benefiting from its ability to reduce quantization bias. In the MICCAI CLDetection2023 challenge, our method achieves 1st place ranking on three metrics and 3rd place on the remaining one. The code for our method is available at https://github.com/5k5000/CLdetection2023.

cs.CV↗

arXiv2023

Differentiable Resolution Compression and Alignment for Efficient Video Classification and Retrieval

Optimizing video inference efficiency has become increasingly important with the growing demand for video analysis in various fields. Some existing methods achieve high efficiency by explicit discard of spatial or temporal information, which poses challenges in fast-changing and fine-grained scenarios. To address these issues, we propose an efficient video representation network with Differentiable Resolution Compression and Alignment mechanism, which compresses non-essential information in the early stage of the network to reduce computational costs while maintaining consistent temporal correlations. Specifically, we leverage a Differentiable Context-aware Compression Module to encode the saliency and non-saliency frame features, refining and updating the features into a high-low resolution video sequence. To process the new sequence, we introduce a new Resolution-Align Transformer Layer to capture global temporal correlations among frame features with different resolutions, while reducing spatial computation costs quadratically by utilizing fewer spatial tokens in low-resolution non-saliency frames. The entire network can be end-to-end optimized via the integration of the differentiable compression module. Experimental results show that our method achieves the best trade-off between efficiency and performance on near-duplicate video retrieval and competitive results on dynamic video classification compared to state-of-the-art methods. Code:https://github.com/dun-research/DRCA

cs.CV↗

arXiv2023

GaitFormer: Revisiting Intrinsic Periodicity for Gait Recognition

Gait recognition aims to distinguish different walking patterns by analyzing video-level human silhouettes, rather than relying on appearance information. Previous research on gait recognition has primarily focused on extracting local or global spatial-temporal representations, while overlooking the intrinsic periodic features of gait sequences, which, when fully utilized, can significantly enhance performance. In this work, we propose a plug-and-play strategy, called Temporal Periodic Alignment (TPA), which leverages the periodic nature and fine-grained temporal dependencies of gait patterns. The TPA strategy comprises two key components. The first component is Adaptive Fourier-transform Position Encoding (AFPE), which adaptively converts features and discrete-time signals into embeddings that are sensitive to periodic walking patterns. The second component is the Temporal Aggregation Module (TAM), which separates embeddings into trend and seasonal components, and extracts meaningful temporal correlations to identify primary components, while filtering out random noise. We present a simple and effective baseline method for gait recognition, based on the TPA strategy. Extensive experiments conducted on three popular public datasets (CASIA-B, OU-MVLP, and GREW) demonstrate that our proposed method achieves state-of-the-art performance on multiple benchmark tests.

cs.CV↗

arXiv2023

Possibility of generating the $^3_{Λ_c}$H in the quark-delocalization color-screening model

We probe the existence of the $^3_{Λ_c}$H where the $NΛ_c$ potentials are derived from the quark-delocalization color-screening model (QDCSM). The $NΛ_c$ system is studied and the $NΛ_c$ scattering length so as the effective range are obtained in the QDCSM. We construct effective Gaussian-type $NΛ_c$ potentials which reproduce the $NΛ_c$ scattering data given by the QDCSM. By solving the $NNΛ_c$ three body Schrödinger equation with the Gaussian expansion method, we calculate the energies of the $^3_{Λ_c}$H with isospin $I=0$, $J^P=1/2^+$ and $I=0$, $J^P=3/2^+$ under different color screening parameter $μ$. The $J^P=1/2^+$ and $J^P=3/2^+$ states are both bound when the color screening parameter $μ$ is set to 1.0 or 1.2, where the $J^P=1/2^+$ state is bound by $0.08\sim0.85$ MeV and the $J^P=3/2^+$ state is bound by $0.15\sim1.31$ MeV with respect to the deuteron-$Λ_c$ threshold.

nucl-th↗

arXiv2022

3D-CSL: self-supervised 3D context similarity learning for Near-Duplicate Video Retrieval

In this paper, we introduce 3D-CSL, a compact pipeline for Near-Duplicate Video Retrieval (NDVR), and explore a novel self-supervised learning strategy for video similarity learning. Most previous methods only extract video spatial features from frames separately and then design kinds of complex mechanisms to learn the temporal correlations among frame features. However, parts of spatiotemporal dependencies have already been lost. To address this, our 3D-CSL extracts global spatiotemporal dependencies in videos end-to-end with a 3D transformer and find a good balance between efficiency and effectiveness by matching on clip-level. Furthermore, we propose a two-stage self-supervised similarity learning strategy to optimize the entire network. Firstly, we propose PredMAE to pretrain the 3D transformer with video prediction task; Secondly, ShotMix, a novel video-specific augmentation, and FCS loss, a novel triplet loss, are proposed further promote the similarity learning results. The experiments on FIVR-200K and CC_WEB_VIDEO demonstrate the superiority and reliability of our method, which achieves the state-of-the-art performance on clip-level NDVR.

cs.CV↗

arXiv2022

Characterization of the Thermospheric Mean Winds and Circulation during Solstice using ICON/MIGHTI Observations

Using the horizontal neutral wind observations from the MIGHTI instrument onboard NASA's ICON (Ionospheric Connection Explorer) spacecraft with continuous coverage, we determine the climatology of the mean zonal and meridional winds and the associated mean circulation at low- to middle latitudes ($10^\circ$S-40$^{\circ}$N) for Northern Hemisphere {summer} solstice conditions between 90 km and 200 km altitudes, specifically on 20 June 2020 solstice as well as for a one-month period from 8 June-7 July 2020 {and for Northern winter season from 16 December 2019-31 January 2020, which spans a 47-day period, providing full local time coverage}. The data are averaged within appropriate altitude, longitude, latitude, solar zenith angle, and local time bins to produce mean wind distributions. The geographical distributions and local time variations of the mean horizontal circulation are evaluated. The instantaneous horizontal winds exhibit a significant degree of spatiotemporal variability often exceeding $\pm 150 $ m s$^{-1}$. The daily averaged zonal mean winds demonstrate day-to-day variability. Eastward zonal winds and northward (winter-to-summer) meridional winds are prevalent in the lower thermosphere, which provides indirect observational evidence of the eastward momentum deposition by small-scale gravity waves. The mean neutral winds and circulation exhibit smaller scale structures in the lower thermosphere (90-120 km), while they are more homogeneous in the upper thermosphere, indicating the increasingly dissipative nature of the thermosphere. The mean wind and circulation patterns inferred from ICON/MIGHTI measurements can be used to constrain and validate general circulation models, as well as input for numerical wave models.

physics.space-ph↗

arXiv2022

Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans

Tumor lesion segmentation is one of the most important tasks in medical image analysis. In clinical practice, Fluorodeoxyglucose Positron-Emission Tomography~(FDG-PET) is a widely used technique to identify and quantify metabolically active tumors. However, since FDG-PET scans only provide metabolic information, healthy tissue or benign disease with irregular glucose consumption may be mistaken for cancer. To handle this challenge, PET is commonly combined with Computed Tomography~(CT), with the CT used to obtain the anatomic structure of the patient. The combination of PET-based metabolic and CT-based anatomic information can contribute to better tumor segmentation results. %Computed tomography~(CT) is a popular modality to illustrate the anatomic structure of the patient. The combination of PET and CT is promising to handle this challenge by utilizing metabolic and anatomic information. In this paper, we explore the potential of U-Net for lesion segmentation in whole-body FDG-PET/CT scans from three aspects, including network architecture, data preprocessing, and data augmentation. The experimental results demonstrate that the vanilla U-Net with proper input shape can achieve satisfactory performance. Specifically, our method achieves first place in both preliminary and final leaderboards of the autoPET 2022 challenge. Our code is available at https://github.com/Yejin0111/autoPET2022_Blackbean.

eess.IV↗

arXiv2022

Cluster structures of the $0^+$ states of $^{13}_Λ{\rm C}$ with the 3$α+Λ$ four-body orthogonality condition model

We study structures of the $0^+$ states of $^{13}_Λ$C within the framework of $α+α+α+Λ$ four-body orthogonality condition model with the Gaussian expansion method. We obtain five $0^+$ states of $^{13}_Λ$C and compare them with the low-lying four $0^+$ states of $^{12}$C. We find that the $0_1^+$, $0_2^+$ and $0_4^+$ states correspond to the $0_1^+$, $0_2^+$ and $0_4^+$ states of $^{12}$C, respectively. We also find that both the $0_3^+$ and $0_5^+$ states have analogous nature to the $0_3^+$ state of $^{12}$C, where the additional $Λ$ particle couples with $^8$Be cluster and one $α$ cluster, in the $0_3^+$ state of $^{12}$C, respectively. The former is then shown to have an elongated $^9_Λ$Be$(0_1^+) + α$ cluster structure with a higher nodal behaviour for their relative wave function, and the latter have a dilute three-body gas consisting of $2α+^5_Λ$He clusters.

nucl-th↗