arXiv subjects

Yi Qiang

Publications and source records attributed to Yi Qiang.

6 recordsLinked to original sources

arXiv2025

Feasibility study of multiplexing analog signals from SiPMs for a single layer monolithic PET detector design

Semi monolithic detector designs with a series of stacked thin monolithic scintillator plates and side readout are an attractive approach for potentially achieving very high performance in a positron emission tomography (PET) scanner. In this work, a simulation study of a single layer monolithic detector module was performed with side read out of scintillation light using GATEv8.2. In this design, a single layer LSO crystal was used with dimensions 40 mm*40 mm*40 mm, with 0.60 mm thickness of the ESR (enhanced specular reflector) films covering the crystal's top and bottom surfaces. The photons generated in the scintillation process induced by the gamma ray hitting the crystal were detected by four 1*8 SiPM (silicon photomultiplier) arrays placed along the four sides of the crystal. The scintillation light distribution detected by all of the 32 SiPMs surrounding the crystal layer was then used to extract the gamma-crystal interaction location based on machine learning analysis. In this work, the spatial resolution of the detector module was explored when analog signals from each of the 32 SiPMs were summed to 28, 24, 20, 16, 12, 8, and 4 total outputs. This study showed that good spatial resolution can be achieved even when the number of read out channels is decreased by multiplexing, which can reduce the overall detector manufacturing cost.

physics.ins-det↗

arXiv2023

Comprehensive evaluations of a prototype full field-of-view photon counting CT system through phantom studies

Photon counting CT (PCCT) has been a research focus in the last two decades. Recent studies and advancements have demonstrated that systems using semiconductor-based photon counting detectors (PCDs) have the potential to provide better contrast, noise and spatial resolution performance compared to conventional scintillator-based systems. With multi-energy threshold detection, PCD can simultaneously provide the photon energy measurement and enable material decomposition for spectral imaging. In this work, we report a performance evaluation of our first CdZnTe-based prototype full-size photon counting CT system through various phantom imaging studies. This prototype system supports a 500 mm scan field-of-view (FOV) and 10 mm cone coverage at isocenter. Phantom scans were acquired using 120 kVp from 50 to 400 mAs to assess the imaging performance on: CT number accuracy, uniformity, noise, spatial resolution, material differentiation and quantification. Both qualitative and quantitative evaluations show that PCCT has superior imaging performance with lower noise and improved spatial resolution compared to conventional energy integrating detector (EID)-CT. Using projection domain material decomposition approach with multiple energy bin measurements, PCCT virtual monoenergetic images (VMIs) have lower noise, and superior performance in quantifying iodine and calcium concentrations. These improvements lead to increased contrast-to-noise ratio (CNR) for both high and low contrast study objects compared to EID-CT. PCCT can also generate super-high resolution (SHR) images using much smaller detector pixel size than EID-CT and dramatically improve image spatial resolution.

physics.med-ph↗

arXiv2023

TopoBERT: Plug and Play Toponym Recognition Module Harnessing Fine-tuned BERT

Extracting precise geographical information from textual contents is crucial in a plethora of applications. For example, during hazardous events, a robust and unbiased toponym extraction framework can provide an avenue to tie the location concerned to the topic discussed by news media posts and pinpoint humanitarian help requests or damage reports from social media. Early studies have leveraged rule-based, gazetteer-based, deep learning, and hybrid approaches to address this problem. However, the performance of existing tools is deficient in supporting operations like emergency rescue, which relies on fine-grained, accurate geographic information. The emerging pretrained language models can better capture the underlying characteristics of text information, including place names, offering a promising pathway to optimize toponym recognition to underpin practical applications. In this paper, TopoBERT, a toponym recognition module based on a one dimensional Convolutional Neural Network (CNN1D) and Bidirectional Encoder Representation from Transformers (BERT), is proposed and fine-tuned. Three datasets (CoNLL2003-Train, Wikipedia3000, WNUT2017) are leveraged to tune the hyperparameters, discover the best training strategy, and train the model. Another two datasets (CoNLL2003-Test and Harvey2017) are used to evaluate the performance. Three distinguished classifiers, linear, multi-layer perceptron, and CNN1D, are benchmarked to determine the optimal model architecture. TopoBERT achieves state-of-the-art performance (f1-score=0.865) compared to the other five baseline models and can be applied to diverse toponym recognition tasks without additional training.

cs.CL↗

arXiv2019

Robust Data Preprocessing for Machine-Learning-Based Disk Failure Prediction in Cloud Production Environments

To provide proactive fault tolerance for modern cloud data centers, extensive studies have proposed machine learning (ML) approaches to predict imminent disk failures for early remedy and evaluated their approaches directly on public datasets (e.g., Backblaze SMART logs). However, in real-world production environments, the data quality is imperfect (e.g., inaccurate labeling, missing data samples, and complex failure types), thereby degrading the prediction accuracy. We present RODMAN, a robust data preprocessing pipeline that refines data samples before feeding them into ML models. We start with a large-scale trace-driven study of over three million disks from Alibaba Cloud's data centers, and motivate the practical challenges in ML-based disk failure prediction. We then design RODMAN with three data preprocessing echniques, namely failure-type filtering, spline-based data filling, and automated pre-failure backtracking, that are applicable for general ML models. Evaluation on both the Alibaba and Backblaze datasets shows that RODMAN improves the prediction accuracy compared to without data preprocessing under various settings.

cs.LG↗

arXiv2018

Construction and Performance of the Barrel Electromagnetic Calorimeter for the GlueX Experiment

The barrel calorimeter is part of the new spectrometer installed in Hall D at Jefferson Lab for the GlueX experiment. The calorimeter was installed in 2013, commissioned in 2014 and has been operating routinely since early 2015. The detector configuration, associated Monte Carlo simulations, calibration and operational performance are described herein. The calorimeter records the time and energy deposited by charged and neutral particles created by a multi-GeV photon beam. It is constructed as a lead and scintillating-fiber calorimeter and read out with 3840 large-area silicon photomultiplier arrays. Particles impinge on the detector over a wide range of angles, from normal incidence at 90 degrees down to 11.5 degrees, which defines a geometry that is fairly unique among calorimeters. The response of the calorimeter has been measured during a running experiment and performs as expected for electromagnetic showers below 2.5 GeV. We characterize the performance of the BCAL using the energy resolution integrated over typical angular distributions for $π^0$ and $η$ production of $σ_E/E$=5.2\%/$\sqrt{E(\rm{GeV})} \oplus$ 3.6\% and a timing resolution of $σ$\,=\,150\,ps at 1\,GeV.

physics.ins-det↗

arXiv2012

Radiation Hardness Tests of SiPMs for the JLab Hall D Barrel Calorimeter

We report on the measurement of the neutron radiation hardness of silicon photomultipliers (SiPMs) manufactured by Hamamatsu Corporation in Japan and SensL in Ireland. Samples from both companies were irradiated by neutrons created by a 1 GeV electron beam hitting a thin lead target at Jefferson Lab Hall A. More tests regarding the temperature dependence of the neutron radiation damage and self-annealing were performed on Hamamatsu SiPMs using a calibrated Am-Be neutron source from the Jefferson Lab Radiation Control group. As the result of irradiation both dark current and dark rate increase linearly as a function of the 1 MeV equivalent neutron fluence and a temperature dependent self-annealing effect is observed.

physics.ins-det↗