381 research outputs found

    On the performance of a mixed RF/MIMO FSO variable gain dual-hop transmission system

    Get PDF
    In this work, we propose a mixed radio frequency (RF) and multiple-input-multiple-output (MIMO) free-space optical (FSO) system based on a variable-gain dual-hop relay transmission scheme. The RF channel is modeled by Rayleigh distribution and Gamma–Gamma turbulence distribution is adopted for the MIMO FSO link, which accounts for the equal gain combining diversity technique. Moreover, new closed-form mathematical formulas are obtained including the cumulative distribution function, probability density function, moment generating function, and moments of equivalent signal-to-noise ratio of the dual-hop relay system based on Meijer’s G function. As such, we derive the novel analytical expressions of the outage probability, the higher-order fading, and the average bit error rate for a range of modulations in terms of Meijer’s G function. Furthermore, the exact closed-form formula of the ergodic capacity is derived based on the bivariate Meijer’s G function. The evaluation and simulation are provided for system performance, and the effect of spatial diversity technique is discussed as well

    Towards Best Practice of Interpreting Deep Learning Models for EEG-based Brain Computer Interfaces

    Get PDF
    As deep learning has achieved state-of-the-art performance for many tasks of EEG-based BCI, many efforts have been made in recent years trying to understand what have been learned by the models. This is commonly done by generating a heatmap indicating to which extent each pixel of the input contributes to the final classification for a trained model. Despite the wide use, it is not yet understood to which extent the obtained interpretation results can be trusted and how accurate they can reflect the model decisions. In order to fill this research gap, we conduct a study to evaluate different deep interpretation techniques quantitatively on EEG datasets. The results reveal the importance of selecting a proper interpretation technique as the initial step. In addition, we also find that the quality of the interpretation results is inconsistent for individual samples despite when a method with an overall good performance is used. Many factors, including model structure and dataset types, could potentially affect the quality of the interpretation results. Based on the observations, we propose a set of procedures that allow the interpretation results to be presented in an understandable and trusted way. We illustrate the usefulness of our method for EEG-based BCI with instances selected from different scenarios

    Impact of Wall Configurations on Seismic Fragility of Steel-Sheathed Cold-Formed Steel-Framed Buildings

    Get PDF
    Seismic fragility of steel-sheathed cold-formed steel-framed (CFSF) structures is scarcely investigated; thus, the information for estimation of seismic losses of the steel-sheathed CFSF buildings is insufficient. This study aims to investigate the seismic fragility of steel-sheathed CFSF buildings with different wall configurations. Analytic models for four 2-story steel-sheathed CFSF buildings are established based on shaking table tests on steel-sheathed CFS walls. Then, a group of fragility curves for these buildings are generated. The results show that the thickness of steel sheathing and the fastener spacing of the wall have significant impact on seismic fragility of steel-sheathed CFSF buildings. The seismic fragility of the CFSF building can be reduced by increasing the thickness of steel sheathing or decreasing the fastener spacing. By increasing the thickness of steel sheathing, the reduction on probability is more obvious for the CP limit. It is also found that the exceeding probability is approximately linear with fastener spacing, with a slope in the range from 0.25%/mm to 0.50%/mm

    Unsupervised Temporal Action Localization via Self-paced Incremental Learning

    Full text link
    Recently, temporal action localization (TAL) has garnered significant interest in information retrieval community. However, existing supervised/weakly supervised methods are heavily dependent on extensive labeled temporal boundaries and action categories, which is labor-intensive and time-consuming. Although some unsupervised methods have utilized the ``iteratively clustering and localization'' paradigm for TAL, they still suffer from two pivotal impediments: 1) unsatisfactory video clustering confidence, and 2) unreliable video pseudolabels for model training. To address these limitations, we present a novel self-paced incremental learning model to enhance clustering and localization training simultaneously, thereby facilitating more effective unsupervised TAL. Concretely, we improve the clustering confidence through exploring the contextual feature-robust visual information. Thereafter, we design two (constant- and variable- speed) incremental instance learning strategies for easy-to-hard model training, thus ensuring the reliability of these video pseudolabels and further improving overall localization performance. Extensive experiments on two public datasets have substantiated the superiority of our model over several state-of-the-art competitors

    The changes of pigment contents and their environmental implications in the lake sediments of Ny-Ă…lesund, Svalbard, the Arctic

    Get PDF
    According to palaeoclimatic and modern instrumental data, numerous studies have indicated that the Arctic climate has undergone a significant warming during the past 100 years, and this may lead to significant impact on the fragile lake ecosystem. In this study, we collected a lake sediment core from the Ny-Ă…lesund of Svalbard and determined the concentrations of four pigments including chlorophyll derivatives, total carotenoids, oscillaxanthin and myxoxanthophyll in the sediments. Combined with other physical and chemical proxies such as calcium carbonate, total organic carbon, biogenic silicon etc.,we have reconstructed the historical changes of lacustrine primary productivity in Ny-Ă…lesund, especially for the past 100 years. The results showed that during the period of Little Ice Age(LIA), the climate was unfavorable for the growth of the lake algae, and thus the lacustrine productivity declined. This result was supported by the relatively low contents of pigment and biogenic silica in the sediments. In contrast, the contents of total organic carbon(TOC) and sediment pigments increased significantly in the upper 5cm (~1890AD), reflecting the rapid growth of the lake algae, thus the great increase of lacustrine primary productivity, corresponding to the warming climate after LIA. However, the biogenic silica in the upper sediments still had a relatively low level, and this might be related to the growth competition with other algae species. Over the past 100 years, the ratio of Osc/Myx in the sediments decreased continuously, indicative of durative increase of myxoxanthophyll in blue-green algal pigments, and this might imply that the human activity had enhanced the nutrition level of the lake in the Arctic region
    • …
    corecore