565 research outputs found
Exploring Cross-National Differences in Online Review Topics between China and the United States
The fast growing cross-border e-commerce makes it imperative for online merchants to deeply understand the cross-national differences in consumers’ preferences and online shopping behaviors. Using a data-driven topic model, this study plans to investigate the semantic differences in online product reviews posted by consumers from China and the United Sates. The preliminary results from a pilot study of online reviews of books show that Chinese reviewers focus more on a product’s concrete attributes while American reviewers prefer to express their general evaluations of the product
Risky business: red foxes killed when scavenging from snow leopard kills
Scavenging of foods is a common but potentially dangerous behavior that exposes animals to risk of injury and even death from other animals. Here we report on two observations of red foxes that were killed when scavenging from snow leopard kills that illustrates the risks associated with scavenging for red foxes and other small and medium-sized predators
Non-line-of-sight imaging with arbitrary illumination and detection pattern
Non-line-of-sight (NLOS) imaging aims at reconstructing targets obscured from
the direct line of sight. Existing NLOS imaging algorithms require dense
measurements at rectangular grid points in a large area of the relay surface,
which severely hinders their availability to variable relay scenarios in
practical applications such as robotic vision, autonomous driving, rescue
operations and remote sensing. In this work, we propose a Bayesian framework
for NLOS imaging with no specific requirements on the spatial pattern of
illumination and detection points. By introducing virtual confocal signals, we
design a confocal complemented signal-object collaborative regularization
(CC-SOCR) algorithm for high quality reconstructions. Our approach is capable
of reconstructing both albedo and surface normal of the hidden objects with
fine details under the most general relay setting. Moreover, with a regular
relay surface, coarse rather than dense measurements are enough for our
approach such that the acquisition time can be reduced significantly. As
demonstrated in multiple experiments, the new framework substantially enhances
the applicability of NLOS imaging.Comment: main article: 32 pages with 8 figures; supplementary information: 49
pages with 26 figure
Few-shot Non-line-of-sight Imaging with Signal-surface Collaborative Regularization
The non-line-of-sight imaging technique aims to reconstruct targets from
multiply reflected light. For most existing methods, dense points on the relay
surface are raster scanned to obtain high-quality reconstructions, which
requires a long acquisition time. In this work, we propose a signal-surface
collaborative regularization (SSCR) framework that provides noise-robust
reconstructions with a minimal number of measurements. Using Bayesian
inference, we design joint regularizations of the estimated signal, the 3D
voxel-based representation of the objects, and the 2D surface-based description
of the targets. To our best knowledge, this is the first work that combines
regularizations in mixed dimensions for hidden targets. Experiments on
synthetic and experimental datasets illustrated the efficiency and robustness
of the proposed method under both confocal and non-confocal settings. We report
the reconstruction of the hidden targets with complex geometric structures with
only confocal measurements from public datasets, indicating an
acceleration of the conventional measurement process by a factor of 10000.
Besides, the proposed method enjoys low time and memory complexities with
sparse measurements. Our approach has great potential in real-time
non-line-of-sight imaging applications such as rescue operations and autonomous
driving.Comment: main article: 10 pages, 7 figures supplement: 11 pages, 24 figure
An Improved EPA-Based Receiver Design for Uplink LDPC Coded SCMA System
Sparse code multiple access (SCMA) is an emerging paradigm for efficient enabling of massive connectivity in future machine-type communications (MTC). In this letter, we conceive the uplink transmissions of the low-density parity check (LDPC) coded SCMA system. Traditional receiver design of LDPC-SCMA system, which is based on message passing algorithm (MPA) for multiuser detection followed by individual LDPC decoding, may suffer from the drawback of the high complexity and large decoding latency, especially when the system has large codebook size and/or high overloading factor. To address this problem, we introduce a novel receiver design by applying the expectation propagation algorithm (EPA) to the joint detection and decoding (JDD) involving an aggregated factor graph of LDPC code and sparse codebooks. Our numerical results demonstrate the superiority of the proposed EPA based JDD receiver over the conventional Turbo receiver in terms of both significantly lower complexity and faster convergence rate without noticeable error rate performance degradation
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