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EDBT 2026 Demo / reviewers in the wild / expert

Xinmeng Lyu

dblp:228/5875 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

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

Computer networks · 1

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
Internet of things and sensor networks · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › wireless sensor network
environmental monitoring		 0.312018
Continuous Low-Power Ammonia Monitoring Using Long Short-Term Memory Neural Networks · SenSys 2018

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

neural network · 0.3long short-term memory · 0.3
YearPublicationVenuePosition
2018 Continuous Low-Power Ammonia Monitoring Using Long Short-Term Memory Neural Networks
abstract
Accurate and continuous ammonia monitoring is important for laboratory animal studies and many other applications. Existing solutions are often expensive, inaccurate, or unsuitable for long-term monitoring. In this work, we propose a new ammonia monitoring approach that is low-power, automatic, accurate, and wireless.
Zhenhua Jia, Xinmeng Lyu, Wuyang Zhang, Richard P. Martin, Richard E. Howard, Yanyong Zhang
 SenSys2