3,269 research outputs found

    FastDepth: Fast Monocular Depth Estimation on Embedded Systems

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    Depth sensing is a critical function for robotic tasks such as localization, mapping and obstacle detection. There has been a significant and growing interest in depth estimation from a single RGB image, due to the relatively low cost and size of monocular cameras. However, state-of-the-art single-view depth estimation algorithms are based on fairly complex deep neural networks that are too slow for real-time inference on an embedded platform, for instance, mounted on a micro aerial vehicle. In this paper, we address the problem of fast depth estimation on embedded systems. We propose an efficient and lightweight encoder-decoder network architecture and apply network pruning to further reduce computational complexity and latency. In particular, we focus on the design of a low-latency decoder. Our methodology demonstrates that it is possible to achieve similar accuracy as prior work on depth estimation, but at inference speeds that are an order of magnitude faster. Our proposed network, FastDepth, runs at 178 fps on an NVIDIA Jetson TX2 GPU and at 27 fps when using only the TX2 CPU, with active power consumption under 10 W. FastDepth achieves close to state-of-the-art accuracy on the NYU Depth v2 dataset. To the best of the authors' knowledge, this paper demonstrates real-time monocular depth estimation using a deep neural network with the lowest latency and highest throughput on an embedded platform that can be carried by a micro aerial vehicle.Comment: Accepted for presentation at ICRA 2019. 8 pages, 6 figures, 7 table

    Jet Quenching and Holographic Thermalization

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    We employ the AdS/CFT correspondence to investigate the thermalization of the strongly-coupled plasma and the jet quenching of a hard probe traversing such a thermalizing medium.Comment: 3 pages, 2 figures, The proceeding of Eleventh Conference on the Intersections of Particle and Nuclear Physics --- CIPANP 2012, May 28, 2012 - June 3, 2012, St. Petersburg, FL, US

    A direct method for analyzing the vertical vehicle-structure interaction

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    A new method for the dynamic analysis of the vertical vehicle-structure interaction is presented. The vehicle and structure systems can be discretized with various types of finite elements and may have any degree of complexity. The equations of both systems are complemented with additional compatibility equations to ensure contact between the vehicles and the structure. The equations of motion and the compatibility equations form a single system that is solved directly, thus avoiding the iterative procedure used by other authors to satisfy the compatibility between the vehicle and structure. For large structural systems the proposed method is usually more efficient than those that frequently update and factorize the system matrix. Some numerical examples have shown that the proposed formulation is accurate and efficient

    Syntenin-1 is a promoter and prognostic marker of head and neck squamous cell carcinoma invasion and metastasis.

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    Metastasis represents a key factor associated with poor prognosis of head and neck squamous cell carcinoma (HNSC). However, the underlying molecular mechanisms remain largely unknown. In this study, our liquid chromatography with tandem mass spectrometry analysis revealed a number of significantly differentially expressed membrane/membrane-associated proteins between high invasive UM1 and low invasive UM2 cells. One of the identified membrane proteins, Syntenin-1, was remarkably up-regulated in HNSC tissues and cell lines when compared to the controls, and also over-expressed in recurrent HNSC and high invasive UM1 cells. Syntenin-1 over-expression was found to be significantly associated with lymph node metastasis and disease recurrence. HNSC patients with higher syntenin-1 expression had significantly poorer long term overall survival and similar results were found in many other types of cancers based on analysis of The Cancer Genome Atlas data. Finally, knockdown of syntenin-1 inhibited the proliferation, migration and invasion of HNSC cells, and opposite findings were observed when syntenin-1 was over-expressed. Collectively, our studies indicate that syntenin-1 promotes invasion and progression of HNSC. It may serve as a valuable biomarker for lymph node metastasis or a potential target for therapeutic intervention in HNSC

    Learner interpretations of shared space in multilateral English blogging

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    Probing the Underlying Structure of Modern Expectancy-Value Theory in Multicultural Education: A Bayesian Exploratory Factor Analysis

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    Expectancy-Value (EV) theory has been widely used in a plethora of domains except for multicultural education, a distinct and critical field in many countries due to increasing student diversity. In light of the domain-specific nature of the EV theory and the discrepancy between the theoretical framework and empirical models found in previous studies, the purpose of the present study was to explore the factors of the EV theory in multicultural education. Participants were 187 college students who completed the Multicultural Expectancy-Value Scale (EVS). Exploratory factor analysis (EFA) with Bayes estimation and GEOMIN rotation resulted in two factors: Value and Expectancy. The two factors had a positive significant correlation of .42, p<.001. Participants with a Master’s or Doctoral degree had significantly higher Expectancy beliefs in multicultural education than those with a Bachelor’s degree (t(47.727)=-2.90, p<.01). Although our finding was consistent with the major tenets of the theory that expectancy and value beliefs are two primary motivating factors, it did not fully support the theoretical model, indicating a more parsimonious factor structure may be more appropriate. The distinct factor model in our study suggests a need for further research in examining the structural validity of the EV theory in multicultural education

    Probing the Underlying Structure of Modern Expectancy-Value Theory in Multicultural Education: A Bayesian Exploratory Factor Analysis

    Get PDF
    Expectancy-Value (EV) theory has been widely used in a plethora of domains except for multicultural education, a distinct and critical field in many countries due to increasing student diversity. In light of the domain-specific nature of the EV theory and the discrepancy between the theoretical framework and empirical models found in previous studies, the purpose of the present study was to explore the factors of the EV theory in multicultural education. Participants were 187 college students who completed the Multicultural Expectancy-Value Scale (EVS). Exploratory factor analysis (EFA) with Bayes estimation and GEOMIN rotation resulted in two factors: Value and Expectancy. The two factors had a positive significant correlation of .42, p<.001. Participants with a Master’s or Doctoral degree had significantly higher Expectancy beliefs in multicultural education than those with a Bachelor’s degree (t(47.727)=-2.90, p<.01). Although our finding was consistent with the major tenets of the theory that expectancy and value beliefs are two primary motivating factors, it did not fully support the theoretical model, indicating a more parsimonious factor structure may be more appropriate. The distinct factor model in our study suggests a need for further research in examining the structural validity of the EV theory in multicultural education
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