Coherent diffractive imaging using a coherent X-ray source promises to be a useful microscopic method for imaging noncrystalline objects at high spatial resolution. In this article a simple method to estimate the cohe...
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Coherent diffractive imaging using a coherent X-ray source promises to be a useful microscopic method for imaging noncrystalline objects at high spatial resolution. In this article a simple method to estimate the coherently scattered signal as a function of resolution is presented, and it is shown that the required X-ray flux or dose scales as the inverse third power of resolution for a specimen of constant volume and density. A simulated case study using the proposed energy-recovery linac source is also presented, which confirms the estimated flux requirement.
PURPOSE: Total Variation (TV) minimization algorithm is a classical compressed sensing (CS) based iterative image reconstruction algorithm that can accurately reconstruct images from sparse-view projections in compute...
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PURPOSE: Total Variation (TV) minimization algorithm is a classical compressed sensing (CS) based iterative image reconstruction algorithm that can accurately reconstruct images from sparse-view projections in computed tomography (CT). However, the system matrix used in the algorithm is often too large to be stored in computer memory. The purpose of this study is to investigate a new TV algorithm based on image rotation and without system matrix to avoid the memory requirement of system matrix. METHODS: Without loss of generality, a rotation-based adaptive steepest descent-projection onto convex sets (R-ASD-POCS) algorithm is proposed and tested to solve the TV model in parallel beam CT. Specifically, simulation experiments are performed via the Shepp-Logan, FORBILD and real CT image phantoms are used to verify the inverse-crime capability of the algorithm and evaluate the sparse reconstruction capability and the noise suppression performance of the algorithm. RESULTS: Experimental results show that the algorithm can achieve inverse-crime, accurate sparse reconstruction and thus accurately reconstruct images from noisy projections. Compared with the classical ASD-POCS algorithm, the new algorithm may yield the similar image reconstruction accuracy without use of the huge system matrix, which saves the computational memory space significantly. Additionally, the results also show that R-ASD-POCS algorithm is faster than ASD-POCS. CONCLUSIONS: The proposed new algorithm can effectively solve the problem of using huge memory in large scale and iterative image reconstruction. Integrating with ASD-POCS frame, this no-system-matrix based scheme may be readily extended and applied to any iterative image reconstructions.
Passage-time densities are important for the detailed performance analysis of distributed computer and communicating systems. We provide a proof and demonstration of a practical iterative algorithm for extracting comp...
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Passage-time densities are important for the detailed performance analysis of distributed computer and communicating systems. We provide a proof and demonstration of a practical iterative algorithm for extracting complete passage-time densities from expressive semi-Markov systems. We end by showing its application to a distributed web-server cluster model of 15.9 million states. (c) 2004 Elsevier B.V. All rights reserved.
A novel wavelength modulation spectroscopy sensor for studying gas properties near 1.4 μm is developed, validated and used in a direct-connect supersonic combustion test facility. In this sensor there are two H2O tra...
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A novel wavelength modulation spectroscopy sensor for studying gas properties near 1.4 μm is developed, validated and used in a direct-connect supersonic combustion test facility. In this sensor there are two H2O transitions near 7185.60 cm^-1 and 7454.45 cm^-1 that are used to enable the measurements along the line-of-sight. According to an iterative algorithm, the gas pressure, temperature and species mole fraction can be measured simultaneously. The new sensor is used in the isolator and extender of the supersonic combustion test facility. In the isolator, the sensor resolves the transient and measured pressure, temperature and H2O mole fraction with accuracies of 2.5%, 8.2%, and 7.2%, respectively. Due to the non-uniform characteristic in the extender, the measured results cannot precisely characterize gas properties, but they can qualitatively describe the distinctions of different zones or the changes or fluctuations of the gas parameters.
In this paper, an efficient thermal analysis method is presented for large scale compound semiconductor integrated circuits based on a heterojunction bipolar transistor with considering the change of thermal conductiv...
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In this paper, an efficient thermal analysis method is presented for large scale compound semiconductor integrated circuits based on a heterojunction bipolar transistor with considering the change of thermal conductivity with *** influence caused by the thermal conductivity can be equivalent to the increment of the local temperature surrounding the individual device. The junction temperature for each device can be efficiently calculated by the combination of the semianalytic temperature distribution function and the iteration of local temperature with high accuracy, providing a temperature distribution for a full chip. Applying this method to the InP frequency divider chip and the GaAs analog to digital converter chip, the computational results well agree with the results from the simulator COMSOL and the infrared thermal imager respectively. The proposed method can also be applied to thermal analysis in various kinds of semiconductor integrated circuits.
The mobile ticket dispenser system (MTDS) allows customers to remotely draw tickets for service orders anywhere through a mobile handset. In our previous work, the MTDS was applied to a restaurant scenario in which bo...
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The mobile ticket dispenser system (MTDS) allows customers to remotely draw tickets for service orders anywhere through a mobile handset. In our previous work, the MTDS was applied to a restaurant scenario in which both clerks and customers are patient, i.e., once a mobile ticketing (MT) customer remotely draws the ticket, his request can be served by the clerk when the clerk is available, regardless of when the customer arrives at the restaurant. In this paper, the MTDS is applied to a post office scenario in which the customers are patient, but the clerk is impatient since the original ticket drawn by theMT customer may be invalid if he/she does not arrive at the post office before his/her turn. In this case, the behavior of the MT customer is the same as the so-called in-person ticketing customer who needs to draw a ticket in person when he/she arrives at the service counter. We propose an analytical model to derive the probability that an MT customer misses his/her turn when he/she arrives at the post office. A discrete-event simulation model is developed to investigate the performance of the predicted time adjustment mechanism for the MTDS. We also use real data collected at a post office to observe the queuing behavior. Our study provides guidelines for arranging the time for an MT customer to arrive at the MTDS server.
Poisson surface reconstruction (PSR) remains a popular technique for reconstructing watertight surfaces from 3D point samples thanks to its efficiency, simplicity, and robustness. Yet, the existing PSR method and subs...
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Poisson surface reconstruction (PSR) remains a popular technique for reconstructing watertight surfaces from 3D point samples thanks to its efficiency, simplicity, and robustness. Yet, the existing PSR method and subsequent variants work only for oriented points. This paper intends to validate that an improved PSR, called iPSR, can completely eliminate the requirement of point normals and proceed in an iterative manner. In each iteration, iPSR takes as input point samples with normals directly computed from the surface obtained in the preceding iteration, and then generates a new surface with better quality. Extensive quantitative evaluation confirms that the new iPSR algorithm converges in 5-30 iterations even with randomly initialized normals. If initialized with a simple visibility based heuristic, iPSR can further reduce the number of iterations. We conduct comprehensive comparisons with PSR and other powerful implicit-function based methods. Finally, we confirm iPSR's effectiveness and scalability on the AIM@SHAPE dataset and challenging (indoor and outdoor) scenes. Code and data for this paper are at https://***/houfei0801/ipsr.
The recent literature indicates that face recognition and facial expression classification has achieved a high accuracy on benchmark datasets with a large number of face images in the wild. On the other hand, unlike t...
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The recent literature indicates that face recognition and facial expression classification has achieved a high accuracy on benchmark datasets with a large number of face images in the wild. On the other hand, unlike the purpose of recognizing as many people as possible, real applications for families or companies usually aim to recognize a small group of people as accurate as possible. In case of the face is partially occluded, convolutional solutions always simply put images with occlusions into the training dataset and hope the convolution neural network learn a model robust to partial occlusion. These processes not only increase the burden of learning, but also affect the model to identify normal images without occlusions. In this paper, we investigate the research problem of facial image reconstruction to discard the influence of partial occlusion. Based on the phenomenon that human faces are roughly symmetrical, we propose to reconstruct the facial information of occluded areas with the intact half face. Specifically, occlusion on the left-half face is reconstructed with a linear combination of features on the right-half face and vice versa. The process is modeled by keeping row sparsity for the coefficient matrix with l(2,1)-norm regularization while minimizing the reconstruction error. An alternative iterative algorithm is proposed to solve the optimization problem. To validate the effectiveness of the reconstruction, we fine-tune a pretrained model, AlexNet, training on normal face images and test with various occluded images. Extensive experimental results show that our method has improved the classification performance effectively. (c) 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
An efficient iterative method for updating the mass, gyroscopic and stiffness matrices simultaneously using a few of complex measured modal data is developed. By using the proposed iterative method, the unique symmetr...
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An efficient iterative method for updating the mass, gyroscopic and stiffness matrices simultaneously using a few of complex measured modal data is developed. By using the proposed iterative method, the unique symmetric solution can be obtained within finite iteration steps in the absence of roundoff errors by choosing a special kind of initial matrices. Numerical results show that the presented method can be used to update finite element models to get better agreement between analytical and experimental modal parameters. (C) 2011 Elsevier Inc. All rights reserved.
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