arXiv subjects

Zhu Mao

Publications and source records attributed to Zhu Mao.

4 recordsLinked to original sources

arXiv2025

Design and Evaluation of a PMT High-Voltage system for Deepsea Neutrino Telescope

We present the design and characterization of a Cockcroft--Walton (CW) high-voltage (HV) system developed for deep-sea neutrino telescopes. The system provides independently adjustable bias voltages for 31 three-inch photomultiplier tubes (PMTs) housed in a hybrid Digital Optical Module (hDOM). We describe the system architecture, control logic, and laboratory test procedures, and report the combined PMT--base performance in terms of baseline stability, gain uniformity, and timing accuracy under conditions designed to emulate the deep-sea environment. Baseline measurements show low and stable electronic noise. Gain calibrations based on single-photoelectron spectra demonstrate that all PMTs can be tuned to a common nominal gain and remain stable over multi-day operation. Transit-time-spread measurements yield values below 1.8~ns (FWHM), consistent with manufacturer specifications. These results indicate that the CW-based HV system provides the stability and timing precision required for deep-sea multi-PMT optical modules.

hep-ex↗

arXiv2023

Boosting Multimodal Remote Sensing Image Classification with Transformer-based Heterogeneously Salient Graph Representation

Data collected by different modalities can provide a wealth of complementary information, such as hyperspectral image (HSI) to offer rich spectral-spatial properties, synthetic aperture radar (SAR) to provide structural information about the Earth's surface, and light detection and ranging (LiDAR) to cover altitude information about ground elevation. Therefore, a natural idea is to combine multimodal images for refined and accurate land-cover interpretation. Although many efforts have been attempted to achieve multi-source remote sensing image classification, there are still three issues as follows: 1) indiscriminate feature representation without sufficiently considering modal heterogeneity, 2) abundant features and complex computations associated with modeling long-range dependencies, and 3) overfitting phenomenon caused by sparsely labeled samples. To overcome the above barriers, a transformer-based heterogeneously salient graph representation (THSGR) approach is proposed in this paper. First, a multimodal heterogeneous graph encoder is presented to encode distinctively non-Euclidean structural features from heterogeneous data. Then, a self-attention-free multi-convolutional modulator is designed for effective and efficient long-term dependency modeling. Finally, a mean forward strategy is developed in order to avoid overfitting. Based on the above structures, the proposed model is able to break through modal gaps to obtain differentiated graph representation with competitive time cost, even for a small fraction of training samples. Experiments and analyses in three benchmark datasets with various state-of-the-art (SOTA) approaches show the performance of the proposed THSGR. The code will be available in https://github.com/jqyang22.

cs.CV↗

arXiv2018

Vibration-Based Damage Detection in Wind Turbine Blades using Phase-Based Motion Estimation and Motion Magnification

Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art non-contact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-meter long Skystream wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade.

eess.IV↗

arXiv2013

A statistical classification of the unassociated gamma-ray sources in the second Fermi Large Area Telescope Catalog

With assistance of the identified/associated sources in the second Fermi Large Area Telescope (LAT) catalog, we analyze and resolve the spatial distribution and the distributions of the gamma-ray spectral and variability indices of the remaining 575 unassociated Fermi LAT sources. Consequently, it is suggested that the unassociated sources could statistically consist of Galactic supernova remnants/pulsar wind nebulae, BL Lacertae objects, flat spectrum radio quasars, and other types of active galaxies with fractions of 25%, 29%, 41%, and 5%, respectively.

astro-ph.HE↗