arXiv subjects

Yan Jiang

Publications and source records attributed to Yan Jiang.

At least 73 records · Page 4Linked to original sources

arXiv2025

An energy-based discontinuous Galerkin method for the wave equation with nonsmooth solutions

We develop a stable and high-order accurate discontinuous Galerkin method for the second order wave equation, specifically designed to handle nonsmooth solutions. Our approach integrates the energy-based discontinuous Galerkin method with the oscillation-free technique to effectively suppress spurious oscillations near solution discontinuities. Both stability analysis and apriori error estimates are established for common choices of numerical fluxes. We present a series of numerical experiments to confirm the optimal convergence rates for smooth solutions and its robustness in maintaining oscillation-free behavior for nonsmooth solutions in wave equations without or with nonlinear source terms.

math.NA↗

arXiv2025

The MALATANG survey: Dense gas distribution on sub-kiloparsec scales across the disk of M82

We present observations of HCN J=4-3 and HCO^+ J=4-3 lines obtained with the James Clerk Maxwell Telescope as part of the MALATANG survey, combined with archival HCN J=1-0 and HCO^+ J=1-0 data from the Green Bank Telescope, to study the spatial distribution and excitation conditions of dense molecular gas in the disk of M82. We detect HCN J=4-3 and HCO^+ J=4-3 emission within the central region (< 500 pc) of the galaxy, while the J=1-0 emission lines exhibit a more extended spatial distribution (> 700 pc). The dense gas shows a clear double-lobed structure in both spatial distribution and kinematics, with the HCN and HCO^+ J=4-3 lines in the southwest lobe blueshifted by ~ 40 km/s relative to the J=1-0 lines. The HCN J=4-3/1-0 and HCO^+ J=4-3/1-0 line-luminosity ratios range from 0.09 to 0.53 and from 0.14 to 0.87, respectively, with mean values of 0.18 +/- 0.04 and 0.36 +/- 0.06. The HCN ratio is lower than the typical average observed in nearby star-forming galaxies, whereas the HCO^+ ratio is comparatively higher, suggesting that the high-J HCN emission in M82 is significantly sub-thermally excited. Spatially, the peak values of the J=4-3/1-0 ratios are found in the northwest region of M82, coinciding with the galaxy-scale outflow. Elevated HCN/HCO^+ ratios are also detected in roughly the same area, potentially tracing local excitation enhancements driven by the outflow. The HCN/HCO^+ J=4-3 ratio across all detected regions ranges from 0.19 to 1.07 with a mean value of 0.41 +/- 0.11, which is significantly lower than the average J=1-0 ratio of 0.76 +/- 0.08. Both ratios are significantly lower than the average values observed in nearby star-forming galaxies, which could be related to the relatively low gas density and the presence of an extended photo-dissociation region in M82.

astro-ph.GA↗

arXiv2025

OTPTO: Joint Product Selection and Inventory Optimization in Fresh E-commerce Front-End Warehouses

In China's competitive fresh e-commerce market, optimizing operational strategies, especially inventory management in front-end warehouses, is key to enhance customer satisfaction and to gain a competitive edge. Front-end warehouses are placed in residential areas to ensure the timely delivery of fresh goods and are usually in small size. This brings the challenge of deciding which goods to stock and in what quantities, taking into account capacity constraints. To address this issue, traditional predict-then-optimize (PTO) methods that predict sales and then decide on inventory often don't align prediction with inventory goals, as well as fail to prioritize consumer satisfaction. This paper proposes a multi-task Optimize-then-Predict-then-Optimize (OTPTO) approach that jointly optimizes product selection and inventory management, aiming to increase consumer satisfaction by maximizing the full order fulfillment rate. Our method employs a 0-1 mixed integer programming model OM1 to determine historically optimal inventory levels, and then uses a product selection model PM1 and the stocking model PM2 for prediction. The combined results are further refined through a post-processing algorithm OM2. Experimental results from JD.com's 7Fresh platform demonstrate the robustness and significant advantages of our OTPTO method. Compared to the PTO approach, our OTPTO method substantially enhances the full order fulfillment rate by 4.34% (a relative increase of 7.05%) and narrows the gap to the optimal full order fulfillment rate by 5.27%. These findings substantiate the efficacy of the OTPTO method in managing inventory at front-end warehouses of fresh e-commerce platforms and provide valuable insights for future research in this domain.

cs.LG↗

arXiv2025

Adaptive Pricing for Optimal Coordination in Networked Energy Systems with Nonsmooth Cost Functions

Incentive-based coordination mechanisms for distributed energy consumption have shown promise in aligning individual user objectives with social welfare, especially under privacy constraints. Our prior work proposed a two-timescale adaptive pricing framework, where users respond to prices by minimizing their local cost, and the system operator iteratively updates the prices based on aggregate user responses. A key assumption was that the system cost need to smoothly depend on the aggregate of the user demands. In this paper, we relax this assumption by considering the more realistic model of where the cost are determined by solving a DCOPF problem with constraints. We present a generalization of the pricing update rule that leverages the generalized gradients of the system cost function, which may be nonsmooth due to the structure of DCOPF. We prove that the resulting dynamic system converges to a unique equilibrium, which solves the social welfare optimization problem. Our theoretical results provide guarantees on convergence and stability using tools from nonsmooth analysis and Lyapunov theory. Numerical simulations on networked energy systems illustrate the effectiveness and robustness of the proposed scheme.

eess.SY↗

arXiv2025

Pricing Strategies for Different Accuracy Models from the Same Dataset Based on Generalized Hotelling's Law

We consider a scenario where a seller possesses a dataset $D$ and trains it into models of varying accuracies for sale in the market. Due to the reproducibility of data, the dataset can be reused to train models with different accuracies, and the training cost is independent of the sales volume. These two characteristics lead to fundamental differences between the data trading market and traditional trading markets. The introduction of different models into the market inevitably gives rise to competition. However, due to the varying accuracies of these models, traditional multi-oligopoly games are not applicable. We consider a generalized Hotelling's law, where the accuracy of the models is abstracted as distance. Buyers choose to purchase models based on a trade-off between accuracy and price, while sellers determine their pricing strategies based on the market's demand. We present two pricing strategies: static pricing strategy and dynamic pricing strategy, and we focus on the static pricing strategy. We propose static pricing mechanisms based on various market conditions and provide an example. Finally, we demonstrate that our pricing strategy remains robust in the context of incomplete information games.

cs.AI↗

arXiv2025

Hyperspectral Adapter for Object Tracking based on Hyperspectral Video

Object tracking based on hyperspectral video attracts increasing attention to the rich material and motion information in the hyperspectral videos. The prevailing hyperspectral methods adapt pretrained RGB-based object tracking networks for hyperspectral tasks by fine-tuning the entire network on hyperspectral datasets, which achieves impressive results in challenging scenarios. However, the performance of hyperspectral trackers is limited by the loss of spectral information during the transformation, and fine-tuning the entire pretrained network is inefficient for practical applications. To address the issues, a new hyperspectral object tracking method, hyperspectral adapter for tracking (HyA-T), is proposed in this work. The hyperspectral adapter for the self-attention (HAS) and the hyperspectral adapter for the multilayer perceptron (HAM) are proposed to generate the adaption information and to transfer the multi-head self-attention (MSA) module and the multilayer perceptron (MLP) in pretrained network for the hyperspectral object tracking task by augmenting the adaption information into the calculation of the MSA and MLP. Additionally, the hyperspectral enhancement of input (HEI) is proposed to augment the original spectral information into the input of the tracking network. The proposed methods extract spectral information directly from the hyperspectral images, which prevent the loss of the spectral information. Moreover, only the parameters in the proposed methods are fine-tuned, which is more efficient than the existing methods. Extensive experiments were conducted on four datasets with various spectral bands, verifing the effectiveness of the proposed methods. The HyA-T achieves state-of-the-art performance on all the datasets.

cs.CV↗

arXiv2025

Inverse Lax-Wendroff boundary treatment for solving conservation laws with finite difference HWENO methods

This paper presents a novel inverse Lax-Wendroff (ILW) boundary treatment for finite difference Hermite weighted essentially non-oscillatory (HWENO) schemes to solve hyperbolic conservation laws on arbitrary geometries. The complex geometric domain is divided by a uniform Cartesian grid, resulting in challenge in boundary treatment. The proposed ILW boundary treatment could provide high order approximations of both solution values and spatial derivatives at ghost points outside the computational domain. Distinct from existing ILW approaches, our boundary treatment constructs the extrapolation via optimized through a least squares formulation, coupled with the spatial derivatives at the boundary obtained via the ILW procedure. Theoretical analysis indicates that compared with other ILW methods, our proposed one would require fewer terms by using the relatively complicated ILW procedure and thus improve computational efficiency while preserving accuracy and stability. The effectiveness and robustness of the method are validated through numerical experiments.

math.NA↗

arXiv2025

Non-oscillatory entropy stable DG schemes for hyperbolic conservation law

In this paper, we propose a class of non-oscillatory, entropy-stable discontinuous Galerkin (NOES-DG) schemes for solving hyperbolic conservation laws. By incorporating a specific form of artificial viscosity, our new scheme directly controls entropy production and suppresses spurious oscillations. To address the stiffness introduced by the artificial terms, which can restrict severely time step sizes, we employ the integration factor strong stability-preserving Runge-Kutta method for time discretization. Furthermore, our method remains compatible with positivity-preserving limiters under suitable CFL conditions in extreme cases. Various numerical examples demonstrate the efficiency of the proposed scheme, showing that it maintains high-order accuracy in smooth regions and avoids spurious oscillations near discontinuities.

math.NA↗

arXiv2025

Zero-Shot Hashing Based on Reconstruction With Part Alignment

Hashing algorithms have been widely used in large-scale image retrieval tasks, especially for seen class data. Zero-shot hashing algorithms have been proposed to handle unseen class data. The key technique in these algorithms involves learning features from seen classes and transferring them to unseen classes, that is, aligning the feature embeddings between the seen and unseen classes. Most existing zero-shot hashing algorithms use the shared attributes between the two classes of interest to complete alignment tasks. However, the attributes are always described for a whole image, even though they represent specific parts of the image. Hence, these methods ignore the importance of aligning attributes with the corresponding image parts, which explicitly introduces noise and reduces the accuracy achieved when aligning the features of seen and unseen classes. To address this problem, we propose a new zero-shot hashing method called RAZH. We first use a clustering algorithm to group similar patches to image parts for attribute matching and then replace the image parts with the corresponding attribute vectors, gradually aligning each part with its nearest attribute. Extensive evaluation results demonstrate the superiority of the RAZH method over several state-of-the-art methods.

cs.CV↗

arXiv2025

Structure-preserving nodal DG method for the Euler equations with gravity: well-balanced, entropy stable, and positivity preserving

We propose an entropy stable and positivity preserving discontinuous Galerkin (DG) scheme for the Euler equations with gravity, which is also well-balanced for hydrostatic equilibrium states. To achieve these properties, we utilize the nodal DG framework and carefully design the source term discretization using entropy conservative fluxes. Furthermore, we demonstrate that the proposed methodology is compatible with a positivity preserving scaling limiter, ensuring positivity of density and pressure under an appropriate CFL condition. To the best of our knowledge, this is the first DG scheme to simultaneously achieve these three properties with theoretical justification. Numerical examples further demonstrate its robustness and efficiency.

math.NA↗

arXiv2025

Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse

Detecting phishing, spam, fake accounts, data scraping, and other malicious activity in online social networks (OSNs) is a problem that has been studied for well over a decade, with a number of important results. Nearly all existing works on abuse detection have as their goal producing the best possible binary classifier; i.e., one that labels unseen examples as "benign" or "malicious" with high precision and recall. However, no prior published work considers what comes next: what does the service actually do after it detects abuse? In this paper, we argue that detection as described in previous work is not the goal of those who are fighting OSN abuse. Rather, we believe the goal to be selecting actions (e.g., ban the user, block the request, show a CAPTCHA, or "collect more evidence") that optimize a tradeoff between harm caused by abuse and impact on benign users. With this framing, we see that enlarging the set of possible actions allows us to move the Pareto frontier in a way that is unattainable by simply tuning the threshold of a binary classifier. To demonstrate the potential of our approach, we present Predictive Response Optimization (PRO), a system based on reinforcement learning that utilizes available contextual information to predict future abuse and user-experience metrics conditioned on each possible action, and select actions that optimize a multi-dimensional tradeoff between abuse/harm and impact on user experience. We deployed versions of PRO targeted at stopping automated activity on Instagram and Facebook. In both cases our experiments showed that PRO outperforms a baseline classification system, reducing abuse volume by 59% and 4.5% (respectively) with no negative impact to users. We also present several case studies that demonstrate how PRO can quickly and automatically adapt to changes in business constraints, system behavior, and/or adversarial tactics.

cs.LG↗

arXiv2025

Extending SEEDS to a Supervoxel Algorithm for Medical Image Analysis

In this work, we extend the SEEDS superpixel algorithm from 2D images to 3D volumes, resulting in 3D SEEDS, a faster, better, and open-source supervoxel algorithm for medical image analysis. We compare 3D SEEDS with the widely used supervoxel algorithm SLIC on 13 segmentation tasks across 10 organs. 3D SEEDS accelerates supervoxel generation by a factor of 10, improves the achievable Dice score by +6.5%, and reduces the under-segmentation error by -0.16%. The code is available at https://github.com/Zch0414/3d_seeds

cs.CV↗

arXiv2025

A globally divergence-free entropy stable nodal DG method for conservative ideal MHD equations

We propose an arbitrarily high-order globally divergence-free entropy stable nodal discontinuous Galerkin (DG) method to directly solve the conservative form of the ideal MHD equations using appropriate quadrature rules. The method ensures a globally divergence-free magnetic field by updating it at interfaces with a constraint-preserving formulation [5] and employing a novel least-squares reconstruction technique. Leveraging this property, the semi-discrete nodal DG scheme is proven to be entropy stable. To handle the problems with strong shocks, we introduce a novel limiting strategy that suppresses unphysical oscillations while preserving the globally divergence-free property. Numerical experiments verify the accuracy and efficacy of our method.

math.NA↗

arXiv2024

PowerRadio: Manipulate Sensor Measurementvia Power GND Radiation

Sensors are key components enabling various applications, e.g., home intrusion detection and environmental monitoring. While various software defenses and physical protections are used to prevent sensor manipulation, this paper introduces a new threat vector, PowerRadio, that bypasses existing protections and changes sensor readings from a distance. PowerRadio leverages interconnected ground (GND) wires, a standard practice for electrical safety at home, to inject malicious signals. The injected signal is coupled by the sensor's analog measurement wire and eventually survives the noise filters, inducing incorrect measurement. We present three methods to manipulate sensors by inducing static bias, periodical signals, or pulses. For instance, we show adding stripes into the captured images of a surveillance camera or injecting inaudible voice commands into conference microphones. We study the underlying principles of PowerRadio and identify its root causes: (1) the lack of shielding between ground and data signal wires and (2) the asymmetry of circuit impedance that enables interference to bypass filtering. We validate PowerRadio against a surveillance system, broadcast systems, and various sensors. We believe that PowerRadio represents an emerging threat, exhibiting the advantages of both radiated and conducted EMI, e.g., expanding the effective attack distance of radiated EMI yet eliminating the requirement of line-of-sight or approaching physically. Our insights shall provide guidance for enhancing the sensors' security and power wiring during the design phases.

eess.SP↗

arXiv2024

CO-CHANGES II: spatially resolved IRAM 30M CO line observations of 23 nearby edge-on spiral galaxies

Molecular gas, as the fuel for star formation, and its relationship with atomic gas are crucial for understanding how galaxies regulate their star forming (SF) activities. We conducted IRAM 30m observations of 23 nearby spiral galaxies from the CHANG-ES project to investigatet the distribution of molecular gas and the Kennicutt-Schmidt law. Combining these results with atomic gas masses from previous studies, we aim to investigate the scaling relations that connect the molecular and atomic gas masses with stellar masses and the baryonic Tully-Fisher relation. Based on spatially resolved observations of the three CO lines, we calculated the total molecular gas masses, the ratios between different CO lines, and derived physical parameters such as temperature and optical depth. The median line ratios for nuclear/disk regions are 8.6/6.1 (^{12}\mathrm{CO}/^{13}\mathrm{CO}\ J=1{-}0) and 0.53/0.39 (^{12}\mathrm{CO}\ J=2{-}1/J=1{-}0). Molecular gas mass derived from ^{13}\mathrm{CO} is correlated but systematically lower than that from ^{12}\mathrm{CO}. Most galaxies follow the spatially resolved SF scaling relation with a median gas depletion timescale of approximately 1 Gyr, while a few exhibit shorter timescales of approximately 0.1 Gyr. The molecular-to-atomic gas mass ratio correlates strongly with stellar mass, consistent with previous studies. Galaxies with lower stellar masses show an excess of atomic gas, indicating less efficient conversion to molecular gas. Most galaxies tightly follow the baryonic Tully-Fisher relation, but NGC 2992 and NGC 4594 deviate from the relation due to different physical factors. We find that the ratio of the cold gas (comprising molecular and atomic gas) to the total baryon mass decreases with the gravitational potential of the galaxy, as traced by rotation velocity, which could be due to gas consumption in SF or being heated to the hot phase.

astro-ph.GA↗

arXiv2024

High-Order Implicit Low-Rank Method with Spectral Deferred Correction for Matrix Differential Equations

In this paper, we develop a low-rank method with high-order temporal accuracy using spectral deferred correction (SDC) to compute linear matrix differential equations. In [1], a low rank numerical method is proposed to correct the modeling error of the basis update and the Galerkin (BUG) method, which is a computational approach for DLRA. This method (merge-BUG/mBUG method) has been demonstrated to be first order convergent for general advection-diffusion problems. In this paper, we explore using SDC to elevate the convergence order of the mBUG method. In SDC, we start by computing a first-order solution by mBUG, and then perform successive updates by computing low-rank solutions to the Picard integral equation. Rather than a straightforward application of SDC with mBUG, we propose two aspects to improve computational efficiency. The first is to reduce the intermediate numerical rank by detailed analysis of dependence of truncation parameter on the correction levels. The second aspect is a careful choice of subspaces in the successive correction to avoid inverting large linear systems (from the K- and L-steps in BUG). We prove that the resulting scheme is high-order accurate for the Lipschitz continuous and bounded dynamical system. We consider numerical rank control in our framework by comparing two low-rank truncation strategies: the hard truncation strategy by truncated singular value decomposition and the soft truncation strategy by soft thresholding. We demonstrate numerically that soft thresholding offers better rank control in particular for higher-order schemes for weakly (or non-)dissipative problems.

math.NA↗

arXiv2024

Inverse problems for a quasilinear hyperbolic equation with multiple unknowns

We propose and study several inverse boundary problems associated with a quasilinear hyperbolic equation of the form ${c(x)^{-2}}\partial_t^2u=Δ_g(u+F(x, u))+G(x, u)$ on a compact Riemannian manifold $(M, g)$ with boundary. We show that if $F(x, u)$ is monomial and $G(x, u)$ is analytic in $u$, then $F, G$ and $c$ as well as the associated initial data can be uniquely determined and reconstructed by the corresponding hyperbolic DtN (Dirichlet-to-Neumann) map. Our work leverages the construction of proper Gaussian beam solutions for quasilinear hyperbolic PDEs as well as their intriguing applications in conjunction with light-ray transforms and stationary phase techniques for related inverse problems. The results obtained are also of practical importance in assorted of applications with nonlinear waves.

math.AP↗

arXiv2024

eDIG-CHANGES III: the lagging eDIG revealed by multi-slit spectroscopy of NGC 891

The kinematic information of the extraplanar diffuse ionized gas (eDIG) around galaxies provides clues to the origin of the gas. The eDIG-CHANGES project studies the physical and kinematic properties of the eDIG around the CHANG-ES sample of nearby edge-on disk galaxies. We use a novel multi-slit narrow-band spectroscopy technique to obtain the spatial distribution of spectral properties of the ionized gas around NGC 891, which is often regarded as an analog of the Milky Way. We developed specific data reduction procedures for the multi-slit narrow-band spectroscopy data taken with the MDM 2.4m telescope. The data presented in this paper covers the H$α$ and [N II]$λλ$6548,6583Åemission lines. The eDIG traced by the H$α$ and [N II] lines shows an obvious asymmetric morphology, being brighter in the northeastern part of the galactic disk and extending a few kpc above and below the disk. Global variations in the [N II]/H$α$ line ratio suggest additional heating mechanisms for the eDIG at large heights beyond photoionization. We also construct position-velocity (PV) diagrams of the eDIG based on our optical multi-slit spectroscopy data and compare them to similar PV diagrams constructed with the H I data. The dynamics of the two gas phases are generally consistent with each other. Modeling the rotation curves at different heights from the galactic mid-plane suggests a vertical negative gradient in turnover radius and maximum rotation velocity, with magnitudes of approximately $3$ kpc kpc$^{-1}$ and $22-25$ km s$^{-1}$ kpc$^{-1}$, respectively. Measured vertical gradients of the rotation curve parameters suggest significant differential rotation of the ionized gas in the halo, or often referred to as the lagging eDIG. Systematic study of the lagging eDIG in our eDIG-CHANGES project, will help us to better understand the dynamics of the ionized gas in the halo.

astro-ph.GA↗