5,352 research outputs found

    A Study of Pricing Evolution in the Online Toy Market

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    We examine the pricing trends in the online toy markets based on a unique set of panel data collected across three years’ span. The analysis was made through panel data regression models with error components and serial correlation, allowing comparisons of prices and price dispersions between the two types of online retailers as well as examinations of dynamics of prices and price dispersions. Our results indicate that both online branch of multichannel retailers (OBMCRS) and dotcoms charge similar prices on average, and over time their prices move in tandem. Although the OBMCR retailers charge significantly different prices, the dotcoms do charge similar prices. Moreover, both retailer types demonstrate different magnitudes of price dispersion that move at different rates over time. Although the price dispersion of OBMCRS is higher than that of the dotcoms at the beginning, the gap narrows over time.e-commerce, online pricing strategies, online toy market, price dispersion, pricing trends

    Full-Duplex Cloud Radio Access Network: Stochastic Design and Analysis

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    Full-duplex (FD) has emerged as a disruptive communications paradigm for enhancing the achievable spectral efficiency (SE), thanks to the recent major breakthroughs in self-interference (SI) mitigation. The FD versus half-duplex (HD) SE gain, in cellular networks, is however largely limited by the mutual-interference (MI) between the downlink (DL) and the uplink (UL). A potential remedy for tackling the MI bottleneck is through cooperative communications. This paper provides a stochastic design and analysis of FD enabled cloud radio access network (C-RAN) under the Poisson point process (PPP)-based abstraction model of multi-antenna radio units (RUs) and user equipments (UEs). We consider different disjoint and user-centric approaches towards the formation of finite clusters in the C-RAN. Contrary to most existing studies, we explicitly take into consideration non-isotropic fading channel conditions and finite-capacity fronthaul links. Accordingly, upper-bound expressions for the C-RAN DL and UL SEs, involving the statistics of all intended and interfering signals, are derived. The performance of the FD C-RAN is investigated through the proposed theoretical framework and Monte-Carlo (MC) simulations. The results indicate that significant FD versus HD C-RAN SE gains can be achieved, particularly in the presence of sufficient-capacity fronthaul links and advanced interference cancellation capabilities

    A One Stop 3D Target Reconstruction and multilevel Segmentation Method

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    3D object reconstruction and multilevel segmentation are fundamental to computer vision research. Existing algorithms usually perform 3D scene reconstruction and target objects segmentation independently, and the performance is not fully guaranteed due to the challenge of the 3D segmentation. Here we propose an open-source one stop 3D target reconstruction and multilevel segmentation framework (OSTRA), which performs segmentation on 2D images, tracks multiple instances with segmentation labels in the image sequence, and then reconstructs labelled 3D objects or multiple parts with Multi-View Stereo (MVS) or RGBD-based 3D reconstruction methods. We extend object tracking and 3D reconstruction algorithms to support continuous segmentation labels to leverage the advances in the 2D image segmentation, especially the Segment-Anything Model (SAM) which uses the pretrained neural network without additional training for new scenes, for 3D object segmentation. OSTRA supports most popular 3D object models including point cloud, mesh and voxel, and achieves high performance for semantic segmentation, instance segmentation and part segmentation on several 3D datasets. It even surpasses the manual segmentation in scenes with complex structures and occlusions. Our method opens up a new avenue for reconstructing 3D targets embedded with rich multi-scale segmentation information in complex scenes. OSTRA is available from https://github.com/ganlab/OSTRA

    Crosstalk Impacts on Homogeneous Weakly-Coupled Multicore Fiber Based IM/DD System

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    We numerically discussed crosstalk impacts on homogeneous weakly-coupled multicore fiber based intensity modulation/direct-detection (IM/DD) systems taking into account mean crosstalk power fluctuation, walk-off between cores, laser frequency offset, and laser linewidth.Comment: 3 pages, 11 figures
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