Decay Estimates of Heat Transfer to Melton Polymer Flow in Pipes with Viscous Dissipation

In this work, we compare a parabolic equation with an elliptic equation both of which are used in modeling temperature profile of a powerlaw polymer ow in a semi-infinite straight pipe with circular cross section. We show that both models are well-posed and we derive exponential rates of convergence of the two solutions to the same steady state solution away from the entrance. We also show estimates for difference between the two solutions in terms of physical data

Channel Estimation for Massive MIMO-OFDM Systems by Tracking the Joint Angle-Delay Subspace

In this paper, we propose joint angle-delay subspace based channel estimation in single cell for broadband massive multiple-input and multiple-output (MIMO) systems employing orthogonal frequency division multiplexing (OFDM) modulation. Based on a parametric channel model, we present a new concept of the joint angle-delay subspace which can be tracked by the low-complexity low-rank adaptive filtering (LORAF) algorithm. Then, we investigate an interference-free transmission condition that the joint angle-delay subspaces of the users reusing the same pilots are non-overlapping. Since the channel statistics are usually unknown, we develop a robust minimum mean square error (MMSE) estimator under the worst precondition of pilot decontamination, considering that the joint angle-delay subspaces of the interfering users fully overlap. Furthermore, motivated by the interference-free transmission criteria, we present a novel low-complexity greedy pilot scheduling algorithm to avoid the problem of initial value sensitivity. Simulation results show that the joint angle-delay subspace can be estimated effectively, and the proposed pilot reuse scheme combined with robust MMSE channel estimation offers significant performance gains

OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation

Referring video object segmentation (RVOS) aims at segmenting an object in a video following human instruction. Current state-of-the-art methods fall into an offline pattern, in which each clip independently interacts with text embedding for cross-modal understanding. They usually present that the offline pattern is necessary for RVOS, yet model limited temporal association within each clip. In this work, we break up the previous offline belief and propose a simple yet effective online model using explicit query propagation, named OnlineRefer. Specifically, our approach leverages target cues that gather semantic information and position prior to improve the accuracy and ease of referring predictions for the current frame. Furthermore, we generalize our online model into a semi-online framework to be compatible with video-based backbones. To show the effectiveness of our method, we evaluate it on four benchmarks, \ie, Refer-Youtube-VOS, Refer-DAVIS17, A2D-Sentences, and JHMDB-Sentences. Without bells and whistles, our OnlineRefer with a Swin-L backbone achieves 63.5 J&F and 64.8 J&F on Refer-Youtube-VOS and Refer-DAVIS17, outperforming all other offline methods.Comment: Accepted by ICCV2023. The code is at https://github.com/wudongming97/OnlineRefe

How To Reorganize Social Network For Better Knowledge Contribution During Mobile Collaboration? A Study Based On Anti-Social Behavioral Perspective

Mobile collaboration is an emerging kind of collaboration that adopts mobile devices (i.e., laptops, PDAs, and smart phones) and social media software to improve the efficiency and productivity of collaboration. However, many collaborative teams suffer from an anti-social behavior called social loafing. Social loafing will hinder knowledge exchange within the team and further influence team performance and project outcomes. Moreover, the state of an individual’s social loafing is unobservable and changes overtime, making it difficult to be identified in real time. Therefore, our research aims to investigate the evolution of social loafing and its impact on knowledge contribution in the mobile collaboration context. We propose a machine learning model to infer individuals’ unobserved and evolving social loafing state from the series of task behaviors (quantity and quality of the contributed knowledge). Also, we explore how one’s centrality in a social network affects his/her knowledge contribution behavior when he/she is in different social loafing states. We conduct an empirical study and the results show that individuals with high or low social loafing state are very ‘sticky’ to maintain the previous state and the centrality in the network only positively influences individuals in medium social loafing state. In conclusion, our research adopts a machine leaning method to infer the evolution of individuals’ social loafing and provides a comprehensive understanding of knowledge contribution in team work

Static test rig development and application for an airliner’s hyperstatic aero-engine pylon structure

A set of test system, which is suitable for static test of a hyperstatic aero-engine pylon structure of a certain aircraft, was designed according to the requirements of static structure test. This test technology solved some key problems such as support stiffness simulation of hyperstatic engine pylon and aero-engine loading simulation. Based on these experimental techniques, the static test on a hyperstatic aero-engine pylon of a certain aircraft has been completed in the paper. The test results testified to the stable and reliable working performance of the test system. And the aero-engine pylon, the test specimen, didn’t produce any crack or harmful large deformation under all work conditions, indicating that it has met the design requirements on both static strength and stiffness. The test technology can be applied in static tests of similar hyperstatic test specimen. The test data can serve as a basis for structural static strength and stiffness property evaluation of the aero-engine pylon

Optimization of Millet Axial Flow Threshing and Separation Device Based on Discrete Element Method

The difficulties of threshing and separation of millet have not been solved yet which has restricted the development of the millet industry because of the special biological structure and lack of professional agricultural machinery. In order to improve the quality of millet harvest and meet the market demand for millet, in this paper, according to the branching structure of millet, the millet earhead model was established by Discrete Element Method. Using virtual models of millet and device, the simulation tests were carried out whose results have shown that the threshing effect of the rasp-bar threshing element is better than that of the teeth threshing element. Then the rotor structure was optimized into a combined type of the rasp-bar and the teeth. A three-factor five-level quadratic orthogonal rotation combination test was carried out whose results have shown that the combined rotor can meet the requirements of millet harvest