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Xinghua Guo

dblp:302/9376 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Wireless sensing and localization · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Energy systems and smart grids · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization
material characterization
1.012026
BatTera: Non-Destructive Lithium-Ion Battery Coating Measurement With Terahertz · IEEE Trans. Mob. Comput. 2026
Wireless sensing and localization
terahertz sensing
1.012026
BatTera: Non-Destructive Lithium-Ion Battery Coating Measurement With Terahertz · IEEE Trans. Mob. Comput. 2026
Wireless sensing and localization
wireless sensing
1.012026
BatTera: Non-Destructive Lithium-Ion Battery Coating Measurement With Terahertz · IEEE Trans. Mob. Comput. 2026

Methods — techniques the papers use, named apart from their topics

signal processing · 2.0echo arrival time modeling · 2.0
YearPublicationVenuePosition
2026 BatTera: Non-Destructive Lithium-Ion Battery Coating Measurement With Terahertz
abstract
Electrode coating measurement is a crucial task in practical lithium-ion battery systems, where the thickness and refractive index of the electrode coating directly reflect the battery's quality, energy density, capacity, and lifespan. In this paper, we propose the design, implementation, and evaluation of BatTera, the practical system for an accurate, high-resolution, non-destructive, and safe electrode coating measurement, with the ability to simultaneously measure coating thickness and refractive index. BatTera's contributions are twofold. Firstly, we build a comprehensive mathematical model that characterizes the arrival time of echo signals from both sides of the electrode coating by thoroughly analyzing the electrode structure based on “coating-foil-coating”. This model serves as a theoretical foundation guiding the measurement of coating thickness and refractive index. Secondly, we propose a series of effective signal-processing algorithms to address the practical challenges of double-side coating misalignment and deformation interference, thus adaptive improving the signal-to-noise ratio of Terahertz signals and pushing BatTera one big step closer to real adoptions. We implement BatTera based on the commercial Terahertz device QT-TO1000 and conduct extensive experiments using five types of cathode electrode samples in three different sizes, collected from one of the world's largest new energy battery manufacturers. The results show that BatTera achieves high measurement accuracy with a mean average error of 6.106$\upmu$m for thickness and 0.230 for refractive index.
Long Tan, Xiuzhen Guo, Xinghua Guo, Yuanchao Shu, Jiming Chen 0001
IEEE Trans. Mob. Comput.4
2021 Adversarial Attack with KD-Tree Searching on Training Set
Xinghua Guo, Fan Jia 0006, Jianqiao An, Yahong Han
ICIG (2)1