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Bing Zhou

Publications and source records attributed to Bing Zhou.

104 records · Page 6Linked to original sources
arXiv2017

Design of a Trigger Data Serializer ASIC for the Upgrade of the ATLAS Forward Muon Spectrometer

The small-strip Thin Gap Chamber (sTGC) will be used for both triggering and precision tracking purposes in the upgrade of the ATLAS forward muon spectrometer. Both sTGC pad and strip detectors are readout by a Trigger Data Serializer (TDS) ASIC in the trigger path. This ASIC has two operation modes to prepare trigger data from pad and strip detectors respectively. The pad mode (pad-TDS) collects the firing status for up to 104 pads from one detector layer and transmits the data at 4.8 Gbps to the pad trigger extractor every 25 ns. The pad trigger extractor collects pad-TDS data from eight detector layers and defines a region of interest along the path of a muon candidate. In the strip mode (strip-TDS), the deposited charges from up to 128 strips are buffered, time-stamped, and a trigger matching procedure is performed to read out strips underneath the region of interest. The strip-TDS output is also transmitted at 4.8 Gbps to the following FPGA processing circuits. Details about the ASIC design and test results are presented in this paper.

physics.ins-det↗
arXiv2015

FPGA Implementation of a Fixed Latency Scheme in a Signal Packet Router for the Upgrade of ATLAS Forward Muon Trigger Electronics

We propose a new fixed latency scheme for Xilinx gigabit transceivers that will be used in the upgrade of the ATLAS forward muon spectrometer at the Large Hadron Collider. The fixed latency scheme is implemented in a 4.8 Gbps link between a frontend data serializer ASIC and a packet router. To achieve fixed latency, we use IO delay and dedicated carry in resources in a Xilinx FPGA, while minimally relying on the embedded features of the FPGA transceivers. The scheme is protocol independent and can be adapted to FPGA from other vendors with similar resources. This paper presents a detailed implementation of the fixed latency scheme, as well as simulations of the real environment in the ATLAS forward muon region.

physics.ins-det↗
arXiv2015

Characterization of a Serializer ASIC chip for the upgrade of the ATLAS muon detector

We report on the design of a serializer ASIC to be used in the ATLAS forward muon detector for trigger data transmission. We discuss the performance of a prototype chip covering power dissipation, latency and stable operating line rate. Tests show that the serializer is capable of running at least at 5.76 Gbps with a bit error ratio below 1x10^{-15}, and a power consumption of 200 mW running at 4.8 Gbps. The latency between the start of loading 30 bits into the serializer to the transmission of the first bit from the serializer is measured to be about 6 ns.

physics.ins-det↗
arXiv2015

Facial Expression Cloning with Elastic and Muscle Models

Expression cloning plays an important role in facial expression synthesis. In this paper, a novel algorithm is proposed for facial expression cloning. The proposed algorithm first introduces a new elastic model to balance the global and local warping effects, such that the impacts from facial feature diversity among people can be minimized, and thus more effective geometric warping results can be achieved. Furthermore, a muscle-distribution-based (MD) model is proposed, which utilizes the muscle distribution of the human face and results in more accurate facial illumination details. In addition, we also propose a new distance-based metric to automatically select the optimal parameters such that the global and local warping effects in the elastic model can be suitably balanced. Experimental results show that our proposed algorithm outperforms the existing methods.

cs.GR↗
arXiv2015

Improved Image Deblurring based on Salient-region Segmentation

Image deblurring techniques play important roles in many image processing applications. As the blur varies spatially across the image plane, it calls for robust and effective methods to deal with the spatially-variant blur problem. In this paper, a Saliency-based Deblurring (SD) approach is proposed based on the saliency detection for salient-region segmentation and a corresponding compensate method for image deblurring. We also propose a PDE-based deblurring method which introduces an anisotropic Partial Differential Equation (PDE) model for latent image prediction and employs an adaptive optimization model in the kernel estimation and deconvolution steps. Experimental results demonstrate the effectiveness of the proposed algorithm.

cs.CV↗
arXiv2015

Macroblock Classification Method for Video Applications Involving Motions

In this paper, a macroblock classification method is proposed for various video processing applications involving motions. Based on the analysis of the Motion Vector field in the compressed video, we propose to classify Macroblocks of each video frame into different classes and use this class information to describe the frame content. We demonstrate that this low-computation-complexity method can efficiently catch the characteristics of the frame. Based on the proposed macroblock classification, we further propose algorithms for different video processing applications, including shot change detection, motion discontinuity detection, and outlier rejection for global motion estimation. Experimental results demonstrate that the methods based on the proposed approach can work effectively on these applications.

cs.MM↗
arXiv2013

Plasma panel-based radiation detectors

The plasma panel sensor (PPS) is a gaseous micropattern radiation detector under current development. It has many operational and fabrication principles common to plasma display panels. It comprises a dense matrix of small, gas plasma discharge cells within a hermetically sealed panel. As in plasma display panels, it uses nonreactive, intrinsically radiation-hard materials such as glass substrates, refractory metal electrodes, and mostly inert gas mixtures. We are developing these devices primarily as thin, low-mass detectors with gas gaps from a few hundred microns to a few millimeters. The PPS is a high gain, inherently digital device with the potential for fast response times, fine position resolution (<50-mm RMS) and low cost. In this paper, we report on prototype PPS experimental results in detecting betas, protons, and cosmic muons, and we extrapolate on the PPS potential for applications including the detection of alphas, heavy ions at low-to-medium energy, thermal neutrons, and X-rays.

physics.ins-det↗
arXiv2012

Plasma Panel Sensors for Particle and Beam Detection

The plasma panel sensor (PPS) is an inherently digital, high gain, novel variant of micropattern gas detectors inspired by many operational and fabrication principles common to plasma display panels (PDPs). The PPS is comprised of a dense array of small, plasma discharge, gas cells within a hermetically-sealed glass panel, and is assembled from non-reactive, intrinsically radiation-hard materials such as glass substrates, metal electrodes and mostly inert gas mixtures. We are developing the technology to fabricate these devices with very low mass and small thickness, using gas gaps of at least a few hundred micrometers. Our tests with these devices demonstrate a spatial resolution of about 1 mm. We intend to make PPS devices with much smaller cells and the potential for much finer position resolutions. Our PPS tests also show response times of several nanoseconds. We report here our results in detecting betas, cosmic-ray muons, and our first proton beam tests.

physics.ins-det↗
arXiv2012

Development of a plasma panel radiation detector: recent progress and key issues

A radiation detector based on plasma display panel technology, which is the principal component of plasma television displays is presented. Plasma Panel Sensor (PPS) technology is a variant of micropattern gas radiation detectors. The PPS is conceived as an array of sealed plasma discharge gas cells which can be used for fast response (O(5ns) per pixel), high spatial resolution detection (pixel pitch can be less than 100 micrometer) of ionizing and minimum ionizing particles. The PPS is assembled from non-reactive, intrinsically radiation-hard materials: glass substrates, metal electrodes and inert gas mixtures. We report on the PPS development program, including simulations and design and the first laboratory studies which demonstrate the usage of plasma display panels in measurements of cosmic ray muons, as well as the expansion of experimental results on the detection of betas from radioactive sources.

physics.ins-det↗
arXiv2010

Progress in the Development of Plasma Panel Radiation Detectors

Plasma Display Panels (PDP), the underlying engine of panel plasma television displays, are being investigated for their utility as radiation detectors called Plasma Panel Sensors (PPS). The PPS a novel variant of a micropattern radiation detector, is intended to be a fast, high resolution detector comprised of an array of plasma discharge cells operating in a hermetically sealed gas mixture. We report on the PPS development effort, including recent laboratory measurements.

physics.ins-det↗
arXiv2010

Plasma Panel Detectors for MIP Detection for the SLHC and a Test Chamber Design

Performance demands for high and super-high luminosity at the LHC (up to 10^35 cm^(-2) sec^(-1) after the 2017 shutdown) and at future colliders demand high resolution tracking detectors with very fast time response and excellent temporal and spatial resolution. We are investigating a new radiation detector technology based on Plasma Display Panels (PDP), the underlying engine of panel plasma television displays. The design and production of PDPs is supported by four decades of industrial development. Emerging from this television technology is the Plasma Panel Sensor (PPS), a novel variant of the micropattern radiation detector. The PPS is fundamentally an array of micro-Geiger plasma discharge cells operating in a non-ageing, hermetically sealed gas mixture . We report on the PPS development program, including design of a PPS Test Cell.

physics.ins-det↗
arXiv2008

A Multivariate Training Technique with Event Reweighting

An event reweighting technique incorporated in multivariate training algorithm has been developed and tested using the Artificial Neural Networks (ANN) and Boosted Decision Trees (BDT). The event reweighting training are compared to that of the conventional equal event weighting based on the ANN and the BDT performance. The comparison is performed in the context of the physics analysis of the ATLAS experiment at the Large Hadron Collider (LHC), which will explore the fundamental nature of matter and the basic forces that shape our universe. We demonstrate that the event reweighting technique provides an unbiased method of multivariate training for event pattern recognition.

physics.data-an↗