Signal Processing
This synthetic dataset or phantom consists of 3 jpg format databases, in the two-dimensional (2-D) domain, which are identified as follows:
DB1: Ground Truth
DB2: Speckle noise with zero mean and 0.005 standard deviation
DB3: Speckle noise with zero mean and 0.05 standard deviation
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Gas monitoring plays a crucial role in our intelligent societies. Thus we build those stepwise-collected data for gas concentration modeling in dynamic setting which can boost training data collection. First column is time, you have 8 columns for different sensors, including GM402B, GM702B, GM512B, GM302B, MICS5914, MICS5914, MICS4514, and MICS4514. The remaining 3 columns is recorded as the flow rate, which the flow rate of methane and the oxygen-nitrogen mixture is read as L/min, while hydrogen is read as mL/min.
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The experimental measurement model includes the transmitter, receiver and signal processing parts:The transmitter part includes 1 antenna, capable of transmitting signals at a frequency of 1090 MHz.The signal supplied to the transmitting antenna is generated by the FMCOMMS5 transceiver circuit.To generate the transmit signal, a Matlab program is implemented on the computer to control the FMCOMMS5 circuit through the ZC706 FPGA board.The control process is transmitted via Ethernet communication using a LAN (Local Area Network) cable.Specifically, the signal is generated in the Matlab program
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This dataset image is based on the monthly average temperatures collected at 299 stations of the Brazilian Meteorological Temperature Dataset. Each station in the dataset image is linked to the eight nearest stations in its vicinity. Based on the data in the Brazilian temperature dataset, we draw a graph with node numbers N = 299 and K = 8. The graph is drawn with July data in the dataset, as shown in Fig.
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The faulty joint clearance sizes in the study are taken as 0.25 mm and 0.75 mm. The nonfaulty joint clearance size is guaranteed by fine machining (within 0.04 mm). Fifty groups of vibration data are measured per operation condition（normal condition and three mechanical fault conditions）. Therefore, 400 recordings of the three clearance joint faults and normal operating conditions are collected in the end.
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Low-light images and video footage often exhibit issues due to the interplay of various parameters such as aperture, shutter speed, and ISO settings. These interactions can lead to distortions, especially in extreme lighting conditions. This distortion is primarily caused by the inverse relationship between decreasing light intensity and increasing photon noise, which gets amplified with higher sensor gain. Additionally, secondary characteristics like white balance and color effects can also be adversely affected and may require post-processing correction.
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The scintillator detectors are recalibrated against the datasheet given by the manufacturer. Optimal and mutual dependent values of (a) high voltage at PMT (Photomultiplier Tube), (b) amplifier gain, (c) average time to count the radiation particles (set by operator), and (d) number of instances/sample number are estimated. Total 5: two versions of Central Limit Theorem (CLT), (3) industry preferred Pulse Width Saturation, (4) calibration based on MPPC coupled Gamma-ray detector, and (5) gross method are used.
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A non-destructive testing system requires multiple system configuration parameters during the operation process. For a given transducer, scanning frequency and number of measurements for averaging are just among those parameters. This work tests the central limit theorem to optimally set these parameters. The authors have designed a compact ultrasound computer tomography scanner from scratch just to test this criterion. It is shown that optimal frequency value changes with respect to the scanning angle for an object with a heterogeneous inner profile.
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This dataset contains spectra of 8 types of commodities collected from two different environments. The dataset can be used to study the impact of scanning environments on the spectra distortion
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The growing antenna array scale, the uncorrelated fadings between downlink and uplink of frequency division duplex (FDD) or analog beamforming design increases the difficulty of channel sounding or estimation. Non-wireless channel detection or beam weight prediction method is a promising solution to help obtain timely and accurate wireless channel state. Furthermore, beamforming can be enhanced by the powerful sensing capability of cameras.
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