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The understanding of people’s communication structure is crucial to answering the ongoing debates about whether social media is a “filter bubble”. Focusing on this topic, our work investigated people’s preference for homogeneous or cross-cutting communications in an online activism setting, also the difference in language use and hyperlink use in different communications types. We used the tweets with #Silent Sam to classify communication types of user interactions. After the metric generation, significance tests, and subgraph mining, we found that people are 15 times more likely to communicate with like-minded people. However, cross-cutting communications increase simultaneously with homogeneous ones when the activity level rises. Also, homogeneous communications significantly use more words related to perception, while cross-cutting ones have more words about cognition. We also unveiled the dark side of the crosscutting communications as they are generally more toxic and aggressive. The use of outside links in the tweets is rare for both cross-cutting and homogeneous communications. Nonetheless, the cross-cutting tweets embed more URLs while they direct to less diverse domains than the homogeneous ones. Left-leaning media sources with mixed to high factuality are linked as the outside source for mostly homogeneous interactions. Our work made contributions in the ways of providing the new methodology of subgraph mining to research about partisan sharing and rendering new insights to the research in online activism.

University of Technology Sydney. Faculty of Engineering and Information Technology. Sports video analysis and object 3D detection are extensively studied problems in computer vision. As one of the most important scenarios of object detection in 3D, multiple-camera multiple-object 3D localization (MCMOL) in sports videos has recently drawn much attention in the research community due to the growing trend of object detection from monocular to multiview, i.e., from 2D to 3D. Due to heavy occlusion in crowded sports scenes and high-speed moving targets in sports games, MCMOL for sports objects tends to be extremely challenging. Existing solutions generally apply foreground extraction as input, design statistical or Convolutional Neural Network (CNN) models commonly to all visible targets to obtain objects’ coordinates and/or location encoding. However, ambiguous foreground masks and heavy occlusion limit their performance by a large margin. Moreover, the obtained coordinates cannot be associated or retrieved back to the particular objects. There is no one-to-one relationship between the outcomes and the objects to be detected. Thus, the false-positive and false-negative rates increase. To deal with the above-mentioned issues, in this thesis, we conduct comprehensive studies about the MCMOL problems in sports videos. Due to the challenges mentioned above, we develop three multi-camera multi-object 3D localization approaches that provide accurate, reliable, and distinguishable results. Firstly, we apply Convolutional Neural Network with Initialization Settings over the Probabilistic Occupancy Map (i.e., POM+CNN+IniSet). This approach applies CNN-based monocular segmentation jointly on multiple cameras and develops an indicative parameter initialization scheme for the Bayesian iteration model. Afterward, we propose the POM with Identification (PomID) method and introduce the DeepPlayer model including a Cascade Mask-RCNN model and a pose-guided partial feature embedding to conduct segmentation and identification simultaneously for multiple players. This method separately estimates locations for individuals with identified labels and the rest of the objects without specific identities. Finally, we propose the Probabilistic and Identified Occupancy Map (PIOM) method and develop an Image&ID model to mathematically describe the segmentation pixels and identification estimation as the likelihood probabilities. This method then creates a multi-dimensional Bayesian model to estimate the localization results as posterior occupancy probabilities with unique ID labels. Given the pre-defined prior probabilities, the Bayesian model is optimized by an efficient iterative convergence. Our work is the first attempt to take advantage of CNN-based object identification for object 3D localization applications. Experimental results demonstrate that our proposed framework improves the localization performance by a large margin and outperforms the state-of-the-art in MCMOL sports video scenarios.

We statistically study the relationship between the Lyman-alpha (\lya) and 1--8 �� soft X-ray (SXR) emissions from 658 M- and X-class solar flares observed by the {\em Geostationary Operational Environmental Satellite} during 2006--2016. Based on the peak times of the two waveband emissions, we divide the flares into three types. Type I (III) has an earlier (a later) peak time in the \lya\ emission than that in the SXR emission, while type II has nearly a same peak time (within the time resolution of 10 s) between the \lya\ and SXR emissions. In these 658 flares, we find that there are 505 (76.8\%) type I flares, 10 (1.5\%) type II flares, and 143 (21.7\%) type III flares, and that the three types appear to have no dependence on the flare duration, flare location, or solar cycle. Besides the main peak, the \lya\ emission of the three type flares also shows sub-peaks which can appear in the impulsive or gradual phase of the flare. It is found that the main-peak (for type I) and sub-peak (for type III) emissions of \lya\ that appear in the impulsive phase follow the Neupert effect in general. This indicates that such \lya\ emissions are related to the nonthermal electron beam heating. While the main-peak (for type III) and sub-peak (for type I) emissions of \lya\ that appear in the gradual phase are supposed to be primarily contributed by the thermal plasma that cools down., 22 pages, 10 figures

An dynamic system for real-time obstacle avoidance path planning of redundant robots is constructed in this paper. Firstly, the inter-frame difference method is used to identify the moving target and to calculate the target area, then on the basis of color features and gradient features extracted from the target area, the feature fusion Cam-Shift mean shift algorithm is used to track target, improving the robustness of the tracking algorithm. Secondly, a parallel two-channel target identification and location method based on binocular vision is proposed, updating the target's three-dimensional information in real time. Then, a dynamic collision-free path planning method is implemented: the safety rods are removed through the intersection test, and the minimum distance is derived directly by using the coordinate values of the target in the local coordinate system of the rod. On this basis, the obstacle avoidance gain and escape velocity related to the minimum distance is established, and obstacle avoidance path planning is implemented by using the zero space mapping matrix of redundant robot. Experiments are performed to study the efficiency of the proposed system.

© 2019 Elsevier Ltd Round-trip link delay is an important indicator for network performance optimization and troubleshooting. The Software-Defined Networking (SDN) paradigm, which provides flexible and centralized control capability, paves the way for efficient round-trip link delay measurement. In this paper, we study the round-trip link delay measurement problem in SDN networks. We propose an efficient measurement scheme, which infers round-trip link delays from end-to-end delay of some measurement paths implemented with few flow rules in each SDN switch. Furthermore, to reduce measurement cost and meet measurement constraint, we address the Monitor Placement and Link Assignment (MPLA) problem involved in the measurement scheme. Specifically, we formulate the MPLA problem as a Mixed Integer Linear Programming (MILP) problem, prove that it is NP-hard, and propose an efficient algorithm called MPLA Algorithm based on Biding Strategy (MPLAA-BS) to solve the problem. The extensive simulation results on real network topologies reveal that the proposed scheme can efficiently and accurately measure round-trip link delays in SDN networks, and the MPLAA-BS can find feasible and resource-efficient solutions for the MPLA problem.

0Cr18Ni9 stainless steel pipe is a commonly used welding material, which has great demand in shipbuilding, boiler pressure vessel and construction engineering. In this paper, for a given welding process condition, select reasonable parameters, carry out numerical simulation process on welded joints, analyze the temperature field distribution law and stress field value of welded joints, and judge whether it is consistent with the actual.

In order to maintain and enhance the operational reliability of a robotic manipulator deployed in space, an operational reliability system control method is presented in this paper. First, a method to divide factors affecting the operational reliability is proposed, which divides the operational reliability factors into task-related factors and cost-related factors. Then the models describing the relationships between the two kinds of factors and control variables are established. Based on this, a multivariable and multiconstraint optimization model is constructed. Second, a hierarchical system control model which incorporates the operational reliability factors is constructed. The control process of the space manipulator is divided into three layers: task planning, path planning, and motion control. Operational reliability related performance parameters are measured and used as the system’s feedback. Taking the factors affecting the operational reliability into consideration, the system can autonomously decide which control layer of the system should be optimized and how to optimize it using a control level adjustment decision module. The operational reliability factors affect these three control levels in the form of control variable constraints. Simulation results demonstrate that the proposed method can achieve a greater probability of meeting the task accuracy requirements, while extending the expected lifetime of the space manipulator.