scholarly journals When the Whole Is Not Greater Than the Combination of Its Parts: A “Decompositional” Look at Compositional Distributional Semantics

2015 ◽  
Vol 41 (1) ◽  
pp. 165-173 ◽  
Author(s):  
Fabio Massimo Zanzotto ◽  
Lorenzo Ferrone ◽  
Marco Baroni
Keyword(s):  
Distributional Semantics ◽  
Important Class ◽  
Strong Link ◽  
Composition Methods ◽  
Convolution Kernels ◽  
Composition Operations ◽  
Compositional Distributional Semantics

Distributional semantics has been extended to phrases and sentences by means of composition operations. We look at how these operations affect similarity measurements, showing that similarity equations of an important class of composition methods can be decomposed into operations performed on the subparts of the input phrases. This establishes a strong link between these models and convolution kernels.

Comparison of Body Composition Methods in African Immigrants

2018 ◽  
Vol 118 (9) ◽  
pp. A25
Author(s):  
S. Andrus ◽  
N. Hayat ◽  
A. Kuemmerle ◽  
E. Leahy ◽  
S. Bernstein ◽  
...  
Keyword(s):  
Body Composition ◽  
African Immigrants ◽  
Composition Methods

A Comparison of Body Composition Methods Across Two Phases of the Menstrual Cycle.

2017 ◽  
Vol 49 (5S) ◽  
pp. 256-257
Author(s):  
Cherilyn McLester ◽  
Courtenay Hicks ◽  
Tiffany Esmat ◽  
John McLester
Keyword(s):  
Body Composition ◽  
Menstrual Cycle ◽  
Composition Methods ◽  
Two Phases

How reverse reactions influence the yield of self-assembly robots

2011 ◽  
Vol 30 (5) ◽  
pp. 627-641 ◽  
Author(s):  
Shuhei Miyashita ◽  
Maurice Göldi ◽  
Rolf Pfeifer
Keyword(s):  
Mathematical Model ◽  
Self Assembly ◽  
Target Product ◽  
Assembly Process ◽  
Assembly Sequence ◽  
Essential Factor ◽  
Kinetic Rate ◽  
Bottom Up ◽  
Composition Methods

The decay in structure size of manufacturing products has yielded new demands on spontaneous composition methods. The key for the realization of small-sized robots lies in how to achieve the efficient assembly sequence in a bottom-up manner, where most of the parts have only limited (or no) computational (i.e. deliberative) abilities. In this paper, based on a novel self-assembly platform consisting of self-propulsive centimetre-sized modules capable of aggregation on the surface of water, we study the effect of stochasticity and morphology (shape) on the yield of targeted formations in self-assembly processes. Specifically, we focus on a unique phenomenon: that a number of modules instantly compose a target product without forming intermediate subassemblies, some of which constitute undesired geometrical formations (termed one-shot aggregation). Together with a focus on the role that the morphology of the modules plays, we validate the effect of one-shot aggregation with a kinetic rate mathematical model. Moreover, we examined the degree of parallelism of the assembly process, which is an essential factor in self-assembly, but is not systematically taken into account by existing frameworks.

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