This paper proposes a long-range (LoRa)-based outdoor localization and tracking method.
Our method presents an unsupervised localization approach that utilizes symbolized LoRa …

Combustion instability poses a negative impact on the performance and structural durability
of both land-based and aircraft gas turbine engines, and early detection of combustion …

In a majority of multivariate processes, propagating nature of malfunctions makes the fault
diagnosis a challenging task. This paper presents a novel data-driven strategy for real-time …

Combustion instability, characterized by self-sustained, large-amplitude pressure
oscillations and periodic shedding of coherent vortex structures at varied spatial scales, has …

Early fault diagnosis is crucial to reduce the machine downtime. This paper presents a novel
method based on symbolic dynamic filtering (SDF) for early fault detection and intrinsic …

Accurate and efficient identification of various fault categories, especially for the big data and
multisensory system, is a challenge in rotating machinery fault diagnosis. For the diagnosis …

This paper addresses the problem of target detection in dynamic environments in a semi-
supervised data-driven setting with low-cost passive sensors. A key challenge here is to …

This paper presents a dynamic data-driven method for early detection of thermoacoustic
instabilities in combustors based on short-length time series of sensor data, where the …

Ambient assisted living and smart home technologies are a good way to take care of
dependent people whose number will increase in the future. They allow the discovery and …

Multiscale symbolic dynamic entropy (MSDE) has been recently proposed to characterize
the dynamical behavior of time series, which has merits of high computational efficiency and …