A deep generative directed network for scene depth ordering

Author(s):  
Kewei Wu ◽  
Yang Gao ◽  
Hailong Ma ◽  
Yongxuan Sun ◽  
Tingting Yao ◽  
...  
2011 ◽  
Vol 31 (3) ◽  
pp. 591-593
Author(s):  
Wen-ju YUAN ◽  
Fei-peng LI ◽  
Xin SUN ◽  
Feng FU ◽  
Yan-heng LIU

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Wenjun Hu ◽  
Gang Zhang ◽  
Zhongjun Ma ◽  
Binbin Wu

The multiagent system has the advantages of simple structure, strong function, and cost saving, which has received wide attention from different fields. Consensus is the most basic problem in multiagent systems. In this paper, firstly, the problem of partial component consensus in the first-order linear discrete-time multiagent systems with the directed network topology is discussed. Via designing an appropriate pinning control protocol, the corresponding error system is analyzed by using the matrix theory and the partial stability theory. Secondly, a sufficient condition is given to realize partial component consensus in multiagent systems. Finally, the numerical simulations are given to illustrate the theoretical results.


2021 ◽  
Vol 13 (11) ◽  
pp. 5859
Author(s):  
Shedong Ren ◽  
Fangzhi Gui ◽  
Yanwei Zhao ◽  
Min Zhan ◽  
Wanliang Wang ◽  
...  

Low-carbon product design involves a redesign process that requires not only structural module modification, but more importantly, generating innovative principles to solve design contradictions. Such contradictions include when current design conditions cannot satisfy design requirements or there are antithetical design goals. On the other hand, configuration tasks in the reconfiguration process are interdependent, which requires a well-scheduled arrangement to reduce feedback information. This study proposes an effective configuration methodology for low-carbon design. Firstly, configuration tasks and configuration parameters are designated through quality characteristics, and the directed network along with the associated values of configuration tasks are transformed into the design structure matrix to construct the information flow diagram. Then, the Extenics-based problem-solving model is presented to address design contradictions: low-carbon incompatibility and antithetical problems are clarified and formulated with a basic-element model; extensible and conjugate analysis tools are used to identify problematic structures and provide feasible measures; the Gantt chart of measures execution based on the information flow diagram is constructed to reduce feedback and generate robust schemes with strategy models. The methodology is applied to the vacuum pump low-carbon design, the results show that it effectively solves contradictions with innovative design schemes, and comparative analysis verifies the performance of Extenics.


Author(s):  
Lorenzo Chicchi ◽  
Gloria Cecchini ◽  
Ihusan Adam ◽  
Giuseppe de Vito ◽  
Roberto Livi ◽  
...  

AbstractAn inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
L. Orr ◽  
S. C. Chapman ◽  
J. W. Gjerloev ◽  
W. Guo

AbstractGeomagnetic substorms are a global magnetospheric reconfiguration, during which energy is abruptly transported to the ionosphere. Central to this are the auroral electrojets, large-scale ionospheric currents that are part of a larger three-dimensional system, the substorm current wedge. Many, often conflicting, magnetospheric reconfiguration scenarios have been proposed to describe the substorm current wedge evolution and structure. SuperMAG is a worldwide collaboration providing easy access to ground based magnetometer data. Here we show application of techniques from network science to analyze data from 137 SuperMAG ground-based magnetometers. We calculate a time-varying directed network and perform community detection on the network, identifying locally dense groups of connections. Analysis of 41 substorms exhibit robust structural change from many small, uncorrelated current systems before substorm onset, to a large spatially-extended coherent system, approximately 10 minutes after onset. We interpret this as strong indication that the auroral electrojet system during substorm expansions is inherently a large-scale phenomenon and is not solely due to many meso-scale wedgelets.


2016 ◽  
Vol 3 (11) ◽  
pp. 160270 ◽  
Author(s):  
Taro Takaguchi ◽  
Yuichi Yoshida

When we represent real-world systems as networks, the directions of links often convey valuable information. Finding module structures that respect link directions is one of the most important tasks for analysing directed networks. Although many notions of a directed module have been proposed, no consensus has been reached. This lack of consensus results partly because there might exist distinct types of modules in a single directed network, whereas most previous studies focused on an independent criterion for modules. To address this issue, we propose a generic notion of the so-called truss structures in directed networks. Our definition of truss is able to extract two distinct types of trusses, named the cycle truss and the flow truss, from a unified framework. By applying the method for finding trusses to empirical networks obtained from a wide range of research fields, we find that most real networks contain both cycle and flow trusses. In addition, the abundance of (and the overlap between) the two types of trusses may be useful to characterize module structures in a wide variety of empirical networks. Our findings shed light on the importance of simultaneously considering different types of modules in directed networks.


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