385 research outputs found
Computational investigation of the thermal conductivities and phonon properties of strontium cobalt oxides
No full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: S.M., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 87-91).The thermal conductivities of electrochemically tuned strontium cobalt oxides (SCO) are significantly different among the perovskite SrCoO3 (P-SCO), the brownmillerite SrCoO2.5 (BM-SCO) and the hydrogenated HSrCoO2.5 (H-SCO)1. The underlying mechanism causing this large difference is still unclear. And phonon properties in SCO have not been investigated thoroughly or have some contradictive predictions. In this work, we have calculated the thermal conductivities in P-SCO and BM-SCO by applying molecular and lattice dynamics, and successfully reconstructed the large difference of the thermal conductivities, consistent with measurements. Furthermore, several phonon properties including heat capacities, group velocities, lifetimes and mean free paths have been calculated, and the key roles of local atomic environment and crystal symmetry in determining the thermal conductivities have been identified. We have also analyzed the impact of interfaces, isotropic strains and defects on thermal conductivities, predicted the neutron scattering intensity in P-SCO, and tested the accuracy and performance of molecular dynamics based on deep learning. Additionally, even though the calculations about the phonon properties in H-SCO are not complete, it still offers some inspirations about its thermal conductivity. The thorough investigations about the phonon properties and the mechanisms determining the thermal conductivities in SCO may benefit future research about tunable thermal conductivities in complex oxides.by Hantao Zhang.S.M.S.M. Massachusetts Institute of Technology, Department of Nuclear Science and Engineerin
Experimental Assessment of the Coarray Concept for DoA Estimation in Wireless Communications
No full textThe direction of arrival (DoA) estimation performance of three different coarray structures, namely, the nested array, the coprime sampling array, and the sparse ruler array are presented and compared. The coarray concept makes it possible to detect the DoAs of much more sources than the number of physical antennas. Crucial is that for the first time, these coarrays are investigated based on real measurements conducted on a demonstrator platform. Based on the results obtained, the conclusion is clear. The MUSIC algorithm-based coarray concept with spatial smoothing is not suitable for DoA estimation in practical circumstances due to the unavoidable multipath phenomenon.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Signal Processing System
Flexi-Compression: A Flexible Model Compression Method for Autonomous Driving
No full textBenefiting from the rapid development of convolutional neural networks, computer vision-based autonomous driving technologies are gradually being deployed in vehicles. However, these neural networks typically have a large number of parameters and extremely high computational costs, making them difficult to deploy in autonomous vehicles with limited storage and computational power. In this paper, we propose an innovative model compression approach to compress convolutional neural networks in autonomous driving algorithms, which we call Flexi-Compression. Flexi-Compression first modifies the model structure by replacing the traditional convolutional layers with our proposed Flexi-CP module, thus reducing the computation of the convolutional layers. Then, we leverage knowledge distillation to enable the compressed model to quickly acquire the knowledge of the original model. In addition, we use a Flexi-Batch Normalization layer to prune the model and finally further reduce the model size by model quantization. We compress an autonomous driving algorithm and achieve excellent performance
Interactions of visual attention and quality perception
No full textSeveral attempts to integrate visual saliency information in quality metrics are described in literature, albeit with contradictory results. The way saliency is integrated in quality metrics should reflect the mechanisms underlying the interaction between image quality assessment and visual attention. This interaction is actually two-fold: (1) image distortions can attract attention away from the Natural Scene Saliency (NSS), and (2) the quality assessment task in itself can affect the way people look at an image. A subjective study was performed to analyze the deviation in attention from NSS as a consequence of being asked to assess the quality of distorted images, and, in particular, whether, and if so how, this deviation depended on the distortion kind and/or amount. Saliency maps were derived from eye-tracking data obtained during scoring distorted images, and they were compared to the corresponding NSS, derived from eye-tracking data obtained during freely looking at high quality images. The study revealed some structural differences between the NSS maps and the ones obtained during quality assessment of the distorted images. These differences were related to the quality level of the images; the lower the quality, the higher the deviation from the NSS was. The main change was identified as a shrinking of the region of interest, being most evident at low quality. No evident role for the kind of distortion in the change in saliency was found. Especially at low quality, the quality assessment task seemed to prevail on the natural attention, forcing it to devi te in order to better evaluate the impact of artifactsElectrical Engineering, Mathematics and Computer Scienc
Toward a Reliable Collection of Eye-Tracking Data for Image Quality Research: Challenges, Solutions, and Applications
No full textImage quality assessment potentially benefits from the addition of visual attention. However, incorporating aspects of visual attention in image quality models by means of a perceptually optimized strategy is largely unexplored. Fundamental challenges, such as how visual attention is affected by the concurrence of visual signals and their distortions; whether visual attention affected by distortion or that driven by the original scene only should be included in an image quality model; and how to select visual attention models for the image quality application context, remain. To shed light on the above unsolved issues, designing and performing eye-tracking experiments are essential. Collecting eye-tracking data for the purpose of image quality study is so far confronted with a bias due to the involvement of stimulus repetition. In this paper, we propose a new experimental methodology to eliminate such inherent bias. This allows obtaining reliable eye-tracking data with a large degree of stimulus variability. In fact, we first conducted 5760 eye movement trials that included 160 human observers freely viewing 288 images of varying quality. We then made use of the resulting eye-tracking data to provide insights into the optimal use of visual attention in image quality research. The new eye-tracking data are made publicly available to the research community
A Perceptually Relevant No-Reference Blockiness Metric Based on Local Image Characteristics
No full textA novel no-reference blockiness metric that provides a quantitative measure of blocking annoyance in block-based DCT coding is presented. The metric incorporates properties of the human visual system (HVS) to improve its reliability, while the additional cost introduced by the HVS is minimized to ensure its use for real-time processing. This is mainly achieved by calculating the local pixel-based distortion of the artifact itself, combined with its local visibility by means of a simplified model of visual masking. The overall computation efficiency and metric accuracy is further improved by including a grid detector to identify the exact location of blocking artifacts in a given image. The metric calculated only at the detected blocking artifacts is averaged over all blocking artifacts in the image to yield an overall blockiness score. The performance of this metric is compared to existing alternatives in literature and shows to be highly consistent with subjective data at a reduced computational load. As such, the proposed blockiness metric is promising in terms of both computational efficiency and practical reliability for real-life applications.MediamaticsElectrical Engineering, Mathematics and Computer Scienc
Learning picture quality from visual distraction: Psychophysical studies and computational models
No full textVisual saliency has been increasingly studied in relation to image quality assessment. Incorporating saliency potentially leads to improved ability of image quality metrics to predict perceived quality. However, challenges to optimising the combination of saliency and image quality metrics remain. Previous psychophysical studies have shown that distortion occurring in an image causes visual distractions, and alters gaze patterns relative to that of the image without distortion. From this, it can be inferred that the measurable changes of gaze patterns driven by distortion may be used as a proxy for the likely variation in perceived quality of natural images. In this paper, rather than using saliency as an add-on to image quality metrics, we investigate the plausibility of approximating picture quality based on measuring the deviation of saliency induced by distortion. First, we designed and conducted a large-scale eye-tracking experiment to clarify the knowledge on the relationship between the deviation of saliency and the variability of image quality. We then used the results to devise an algorithm which predicts perceived image quality based on visual distraction. Experimental results demonstrate this can provide good results of image quality prediction
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