Sensor networks are highly distributed networks of small, lightweight wireless nodes, deployed in large numbers to monitor the environment or system by the measurement of physical parameters such as ...

Distributed inference when the participants are only machines or electronic devices, e.g., sensors, has been explored extensively in the signal processing and machine learning literature. However, ...

For office and household users, the intermittent unreliability of computer networks is a frustrating inconvenience, but for scientific researchers it can disrupt data pipeline necessary to advance ...

Distributed beamforming, coupled with effective frequency synchronization, represents a paradigm shift in the performance and reliability of wireless sensor networks. This approach harnesses the ...

One way to design an underwater monitoring device is to take inspiration from nature and emulate an underwater creature. [Michael Barton-Sweeney] is making devices in the shape of, and functioning ...

As the automotive sector accelerates toward higher levels of autonomy, the complexity and scale of sensor networks within vehicles are rapidly expanding. For semiconductor engineers, the challenge is ...

Disturbance exists everywhere in most real networks and systems, and in most cases, has a negative effect on system performance. Disturbance can be modeled from environmental interference, measurement ...

Ordinary visible matter accounts for only about 4.9 percent of the universe, while dark matter makes up about 26.8 percent. Axions are hypothetical, extremely light particles—with field-like ...