activity
20082024
most citedPattern of Global Spin Alignment of and mesons in Heavy-Ion Collisions

149 citations · 527 across the 22 of their papers we have counts for

collaborators

22 papers

eess.SP2024★ 1 cited

5G NR monostatic positioning with array impairments: Data-and-model-driven framework and experiment results

Shengheng Liu, Hao Wang, Mengguan Pan +3

In this article, we present an intelligent framework for 5G new radio (NR) indoor positioning under a monostatic configuration. The primary objective is to estimate both the angle…

q-bio.PE2023★ 1 cited

The Impact of Downgrading Protected Areas (PAD) on Biodiversity

Yufei Li, Lingling Hou, Pengfei Liu

We quantitatively assess the impacts of Downgrading Protected Areas (PAD) on biodiversity in the U.S.. Results show that PAD events significantly reduce biodiversity. The proximity…

cs.IT2023

Sensing Aided Covert Communications: Turning Interference into Allies

Xinyi Wang, Zesong Fei, Peng Liu +3

In this paper, we investigate the realization of covert communication in a general radar-communication cooperation system, which includes integrated sensing and communications as a…

physics.soc-ph2023★ 1 cited

Assessing inequities in electrification via heat pumps across the U.S

Morgan R. Edwards, Jaime Garibay-Rodriguez, Jacob Shimkus Erickson +5

Heat pumps are an energy-efficient and increasingly cost-effective solution for reducing greenhouse gas emissions in the building sector. However, other clean energy technologies s…

stat.ME2022★ 2 cited

Modern Statistical Models and Methods for Estimating Fatigue-Life and Fatigue-Strength Distributions from Experimental Data

William Q. Meeker, Luis A. Escobar, Francis G. Pascual +4

Engineers and scientists have been collecting and analyzing fatigue data since the 1800s to ensure the reliability of life-critical structures. Applications include (but are not li…

cs.AI2022

Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement Learning

Shijie Han, Siyuan Li, Bo An +2

Multi-agent reinforcement learning (MARL) is a prevalent learning paradigm for solving stochastic games. In most MARL studies, agents in a game are defined as teammates or enemies…