arXiv subjects

Ziliang Wang

Publications and source records attributed to Ziliang Wang.

43 records · Page 3Linked to original sources

arXiv2024

Point Cloud Compression via Constrained Optimal Transport

This paper presents a novel point cloud compression method COT-PCC by formulating the task as a constrained optimal transport (COT) problem. COT-PCC takes the bitrate of compressed features as an extra constraint of optimal transport (OT) which learns the distribution transformation between original and reconstructed points. Specifically, the formulated COT is implemented with a generative adversarial network (GAN) and a bitrate loss for training. The discriminator measures the Wasserstein distance between input and reconstructed points, and a generator calculates the optimal mapping between distributions of input and reconstructed point cloud. Moreover, we introduce a learnable sampling module for downsampling in the compression procedure. Extensive results on both sparse and dense point cloud datasets demonstrate that COT-PCC outperforms state-of-the-art methods in terms of both CD and PSNR metrics. Source codes are available at \url{https://github.com/cognaclee/PCC-COT}.

cs.CV↗

arXiv2023

Kinetic Monte Carlo Simulations of Sodium Ion Transport in NaSICON Electrodes

The development of high-performance sodium (Na) ion batteries requires improved electrode materials. The energy and power densities of Na superionic conductor (NaSICON) electrode materials are promising for large-scale energy storage applications. However, several practical issues limit the full utilization of the theoretical energy densities of NaSICON electrodes. A pressing challenge lies in the limited sodium extraction in low Na content NaSICONs, e.g., $\rm Na_1V^{IV}V^{IV}(PO_4)_3 \leftrightarrow V^{V}V^{IV}(PO_4)_3 + 1e^- + 1Na^+$. Hence, it is important to quantify the Na-ion mobility in a broad range of NaSICON electrodes. Using a kinetic Monte Carlo approach bearing the accuracy of first-principles calculations, we elucidate the variability of Na-ion transport vs. Na content in three important NaSICON electrodes, Na$_{\rm x}$Ti$_{2}$(PO$_{4}$)$_{3}$, Na$_{\rm x}$V$_{2}$(PO$_{4}$)$_{3}$, and Na$_{\rm x}$Cr$_{2}$(PO$_{4}$)$_{3}$. Our study suggests that Na$^+$ transport in NaSICON electrodes is almost entirely determined by the local electrostatic and chemical environment set by the transition metal and the polyanionic scaffold. The competition with the ordering-disordering phenomena of Na-vacancies also plays a role in influencing Na-transport. We link the variations in the Na$^+$ kinetic properties by analyzing the competition of ligand field stabilization transition metal ions and their ionic radii. We interpret the limited Na-extraction at $x = 1$ observed experimentally by gaining insights into the local Na-vacancy interplay. We propose that targeted chemical substitutions of transition metals disrupting local charge arrangements will be critical to reducing the occurrence of strong Na$^+$-vacancy orderings at low Na concentrations, thus, expanding the accessible capacities of these electrode materials.

cond-mat.mtrl-sci↗

arXiv2023

Unlocking the Inaccessible Energy Density of Sodium Vanadium Fluorophosphate Electrode Materials by Transition Metal Mixing

Sodium (Na) vanadium (V) fluorophosphate $\mathrm{Na_xV_2(PO_4)_2F_3}$ (NVPF) is a highly attractive intercalation electrode material due to its high operation voltage, large capacity, and long cycle life. However, several issues limit the full utilization of NVPF's energy density: 1) the high voltage plateau associated with extracting the "third" Na ion in the reaction N$_1$VPF $\rightarrow$ VPF (~4.9 V vs Na/Na$^+$) appears above the electrochemical stability window of most practical electrolytes (~4.5 V); 2) a sudden drop in Na-ion diffusivity is observed near composition $\mathrm{Na_1V_2(PO_4)_2F_3}$. Therefore, it is important to investigate the potential substitution of V by other transition metals in NVPF derivatives, which can access the extraction of the third Na-ion. In this work, we investigate the partial substitution of V with molybdenum (Mo), niobium (Nb), or tungsten (W) in NVPF to improve its energy density. We examine the structural and electrochemical behaviors of $\mathrm{Na_xV_{2-y}Mo_y(PO_4)_2F_3}$, $\mathrm{Na_xV_{2-y}Nb_y(PO_4)_2F_3}$, and $\mathrm{Na_xW_{2}(PO_4)_2F_3}$ across the whole Na composition region of 0 $\leq$ x $\leq$ 4, and at various transition metal substitution levels, namely, y=0.5, 1.0, 1.5, 2.0 for Mo, and y=1.0, 2.0 for Nb. We find that partial substitution of 50% V by Mo in NVPF reduces the voltage plateau for extracting the third Na ion by 0.6 Volts, which enables further Na extraction from $\mathrm{Na_1Mo_{2}(PO_4)_2F_3}$ and increases the theoretical gravimetric capacity from ~128 to ~174 mAh/g. Analysis of the migration barriers for Na-ions in $\mathrm{Na_xVMo(PO_4)_2F_3}$ unveils improved kinetic properties over NVPF. The proposed $\mathrm{Na_xVMo(PO_4)_2F_3}$ material provides an optimal gravimetric energy density of ~577.3 Wh/kg versus ~507 Wh/kg for the pristine NVPF, which amounts to an increase of ~13.9%.

cond-mat.mtrl-sci↗

arXiv2022

Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos

Real-time 3D human pose estimation is crucial for human-computer interaction. It is cheap and practical to estimate 3D human pose only from monocular video. However, recent bone splicing based 3D human pose estimation method brings about the problem of cumulative error. In this paper, the concept of virtual bones is proposed to solve such a challenge. The virtual bones are imaginary bones between non-adjacent joints. They do not exist in reality, but they bring new loop constraints for the estimation of 3D human joints. The proposed network in this paper predicts real bones and virtual bones, simultaneously. The final length of real bones is constrained and learned by the loop constructed by the predicted real bones and virtual bones. Besides, the motion constraints of joints in consecutive frames are considered. The consistency between the 2D projected position displacement predicted by the network and the captured real 2D displacement by the camera is proposed as a new projection consistency loss for the learning of 3D human pose. The experiments on the Human3.6M dataset demonstrate the good performance of the proposed method. Ablation studies demonstrate the effectiveness of the proposed inter-frame projection consistency constraints and intra-frame loop constraints.

cs.CV↗

arXiv2021

Phase Stability and Sodium-Vacancy Orderings in a NaSICON Electrode

We elucidate the thermodynamics of sodium (Na) intercalation into the sodium super-ionic conductor (NaSICON)-type electrode, Na$_x$V$_2$(PO$_4$)$_3$, for promising Na-ion batteries with high-power density. This is the first report of a computational temperature-composition phase diagram of the NaSICON-type electrode Na$_x$V$_2$(PO$_4$)$_3$. We identify two thermodynamically stable phases at the compositions Na$_2$V$_2$(PO$_4$)$_3$ and Na$_{3.5}$V$_2$(PO$_4$)$_3$, and their structural features are described for the first time based on our computational analysis. We unveil the crystal-structure and the electronic-structure origins of the ground-state compositions associated with specific Na/vacancy arrangements, which are driven by charge orderings on the vanadium sites. These results are significant for the optimization of high-energy and power densities electrodes for sustainable Na-ion batteries

cond-mat.mtrl-sci↗

arXiv2020

A Probability Distribution and Location-aware ResNet Approach for QoS Prediction

In recent years, the number of online services has grown rapidly, invoke the required services through the cloud platform has become the primary trend. How to help users choose and recommend high-quality services among huge amounts of unused services has become a hot issue in research. Among the existing QoS prediction methods, the collaborative filtering(CF) method can only learn low-dimensional linear characteristics, and its effect is limited by sparse data. Although existing deep learning methods could capture high-dimensional nonlinear features better, most of them only use the single feature of identity, and the problem of network deepening gradient disappearance is serious, so the effect of QoS prediction is unsatisfactory. To address these problems, we propose an advanced probability distribution and location-aware ResNet approach for QoS Prediction(PLRes). This approach considers the historical invocations probability distribution and location characteristics of users and services, and first use the ResNet in QoS prediction to reuses the features, which alleviates the problems of gradient disappearance and model degradation. A series of experiments are conducted on a real-world web service dataset WS-DREAM. The results indicate that PLRes model is effective for QoS prediction and at the density of 5%-30%, which means the data is sparse, it significantly outperforms a state-of-the-art approach LDCF by 12.35%-15.37% in terms of MAE.

cs.SE↗

arXiv2017

The generalization of charged AdS black hole specific volume and number density

In this paper, by proposing a generalized $specific~volume$, we restudy the $P-V$ criticality of charged AdS black holes in the extended phase space. The results show that most of the previous conclusions can be generalized without change, but the ratio $\tildeρ_c$ should be $3 \tildeα/16$ in general case. Further research on the thermodynamical phase transition of black hole leads us to a natural interpretation of our assumption, and more black hole properties can be generalized. Finally, we study the number density for charged AdS black hole in higher dimensions, the results show the necessity of our assumption.

gr-qc↗