Consensus of Star Tree Hypergraphs

2007 ◽  
pp. 325-329
Author(s):  
Fred R. McMorris ◽  
Robert C. Powers
Keyword(s):  
Star Tree

scholarly journals Evaluation of ZigBee Topology Effect on Throughput and End to End Delay Due to Different Transmission Bands for IoT Applications

2020 ◽  
Vol 16 (3) ◽  
pp. 254-259
Author(s):  
Yehia R. Hamdy ◽  
Ahmed I Alghannam
Keyword(s):  
Ieee 802.15.4 ◽  
Transmission Band ◽  
Maximum Throughput ◽  
Iot Applications ◽  
End To End Delay ◽  
Star Tree ◽  
Minimum Delay ◽  
End To End ◽  
Riverbed Modeler ◽  
Ieee 802.15.4 Standard

ZigBee is widely used in wireless network in Internet of Things (IoT) applications to remotely sensing and automation due to its unique characteristics compared to other wireless networks. According to ZigBee classification of IEEE 802.15.4 standard, the network consists of four layers. The ZigBee topology is represented in second layer. Furthermore, the ZigBee topology consists of three topologies, star, tree and mesh. Also there are many transmission bands allowed in physical layer, such as 2.4 GHz, 915 MHz, 868 MHz. The aim of this paper is to evaluate the effect of ZigBee topologies on End to End delay and throughput for different transmission bands. Riverbed Modeler is used to simulate multiple ZigBee proposed scenarios and collect the results. The results of the study recommend which topology should be used at each transmission band to provide lowest End to End delay or obtain maximum throughput, which is case sensitive in some IoT applications that required for example minimum delay time or sending high amount of data.

scholarly journals Integral Layout Optimization of Subsea Production Control System Considering Three-Dimensional Space Constraint

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1947
Author(s):  
Yuanlong Yue ◽  
Zhixiang Liu ◽  
Xin Zuo
Keyword(s):  
Control System ◽  
Oil And Gas ◽  
Production Control ◽  
Dimensional Space ◽  
Adaptive Mutation ◽  
Particle Swarm Algorithm ◽  
Total Cost ◽  
Production Control System ◽  
Star Tree ◽  
Layout Structure

The subsea production control system, characterized by a complex and diverse structure and high cost, is one of the essential parts of a subsea production system. The rational layout of the subsea production control system is essential to reduce development costs and ensure safe production in offshore fields. Most previous studies on layout design in offshore fields have focused on the oil- and gas-gathering system. However, the layout of the subsea production control system has not thoroughly been researched to date and the seabed terrain and integral optimization have rarely been discussed. This paper focuses on the multi-layer star structure and multi-layer star-tree structure, two common layout structures of subsea production control systems, and establishes the corresponding model with obstacle and seabed terrain conditions. Obtaining the lowest possible total cost was the aim of the model. A hybrid algorithm combining the adaptive mutation particle swarm algorithm and the A-star algorithm was applied to integrally optimize the subsea distribution unit and umbilical touch down point positions, the pipe connection topology and pipe routes. The practicality of this approach is demonstrated by designing a layout with one FPSO and 22 subsea control modules. The results indicate that the multi-layer star-tree layout structure has a lower total cost compared to that of the multi-layer star layout structure. In addition, the results were compared with a case that ignores the seabed terrain, indicating differences in the total construction cost. This method provides engineers with quantitative references and reliable cost estimates to make decisions regarding the layout of the subsea production control system.

scholarly journals Three notions of tropical rank for symmetric matrices

2010 ◽  
Vol DMTCS Proceedings vol. AN,... (Proceedings) ◽  
Author(s):  
Dustin Cartwright ◽  
Melody Chan
Keyword(s):  
Convex Hull ◽  
Symmetric Matrices ◽  
Star Tree ◽  
Close Study ◽  
International Audience ◽  
Donnent Lieu ◽  
Tropical Varieties

International audience We introduce and study three different notions of tropical rank for symmetric matrices and dissimilarity matrices in terms of minimal decompositions into rank 1 symmetric matrices, star tree matrices, and tree matrices. Our results provide a close study of the tropical secant sets of certain nice tropical varieties, including the tropical Grassmannian. In particular, we determine the dimension of each secant set, the convex hull of the variety, and in most cases, the smallest secant set which is equal to the convex hull. Nous introduisons et étudions trois notions différentes de rang tropical pour des matrices symétriques et des matrices de dissimilarité, en utilisant des décompositions minimales en matrices symétriques de rang 1, en matrices d'arbres étoiles, et en matrices d'arbres. Nos résultats donnent lieu à une étude détaillée des ensembles des sécantes tropicales de certaines jolies variétés tropicales, y compris la grassmannienne tropicale. En particulier, nous déterminons la dimension de chaque ensemble des sécantes, l'enveloppe convexe de la variété, ainsi que, dans la plupart des cas, le plus petit ensemble des sécantes qui est égal à l'enveloppe convexe.

scholarly journals Starless bias and parameter-estimation bias in the likelihood-based phylogenetic method

2018 ◽  
Author(s):  
Xuhua Xia
Keyword(s):  
Parameter Estimation ◽  
Purifying Selection ◽  
Tree Topology ◽  
Likelihood Method ◽  
Estimation Bias ◽  
Likelihood Methods ◽  
Rate Heterogeneity ◽  
Star Tree ◽  
Constant Rate ◽  
Phylogenetic Method

ABSTRACTI analyzed various site pattern combinations in a 4-OTU case to identify sources of starless bias and parameter-estimation bias in likelihood-based phylogenetic methods, and reported three significant contributions. First, the likelihood method is odd in that it may not generate a star tree with sequences that are equidistant from each other. This behaviour, dubbed starless bias, happens in a 4-OTU tree when there is an excess (i.e., more than expected from a star tree and a substitution model) of conflicting phylogenetic signals supporting the three resolved topologies equally. Special site pattern combinations leading to rejection of a star tree, when sequences are equidistant from each other, were identified. Second, fitting gamma distribution to model rate heterogeneity over sites is strongly confounded with tree topology, especially in conjunction with the starless bias. I present examples to show dramatic differences in the estimated shape parameter α between a star tree and a resolved tree. There may be no rate heterogeneity over sites (with the estimated α > 10000) when a star tree is imposed, but α < 1 (suggesting strong rate heterogeneity over sites) when an (incorrect) resolved tree is imposed. Thus, the dependence of “rate heterogeneity” on tree topology implies that “rate heterogeneity” is not a sequence-specific feature, cautioning against interpreting a small α to mean that some sites are under strong purifying selection and others not. Thirdly, because there is no existing (and working) likelihood method for evaluating a star tree with continuous gamma-distributed rate, I have implemented the method for JC69 in a self-contained R script for a four-OTU tree (star or resolved), in addition to another R script assuming a constant rate over sites. These R scripts should be useful for teaching and exploring likelihood methods in phylogenetics.

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