(Invited) Random Network Structure of Materials Developing Next Generation AI Devices for Autonomous Robotics

2021 ◽  
Vol MA2021-01 (30) ◽  
pp. 996-996
Author(s):  
Hirofumi Tanaka ◽  
Hakaru Tamukoh ◽  
Takashi Morie
Keyword(s):  
Network Structure ◽  
Random Network ◽  
Next Generation ◽  
Autonomous Robotics

scholarly journals Advances in Liquid Crystalline Epoxy Resins for High Thermal Conductivity

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1302
Author(s):  
Younggi Hong ◽  
Munju Goh
Keyword(s):  
Thermal Conductivity ◽  
Network Structure ◽  
Epoxy Resins ◽  
Liquid Crystalline ◽  
Random Network ◽  
Three Dimensional ◽  
Heat Insulator ◽  
Liquid Crystalline Epoxy ◽  
Thermally Conductive ◽  
Substantial Interest

Epoxy resin (EP) is one of the most famous thermoset materials. In general, because EP has a three-dimensional random network, it possesses thermal properties similar to those of a typical heat insulator. Recently, there has been substantial interest in controlling the network structure of EP to create new functionalities. Indeed, the modified EP, represented as liquid crystalline epoxy (LCE), is considered promising for producing novel functionalities, which cannot be obtained from conventional EPs, by replacing the random network structure with an oriented one. In this paper, we review the current progress in the field of LCEs and their application to highly thermally conductive composite materials.

EFFECTS OF CONFIDENCE SCALE AND NETWORK STRUCTURE ON MINORITY OPINION SPREADING

2010 ◽  
Vol 21 (08) ◽  
pp. 1001-1010 ◽  
Author(s):  
BO SHEN ◽  
YUN LIU
Keyword(s):  
Simple Model ◽  
Network Structure ◽  
Random Network ◽  
Random Networks ◽  
Scale Free Network ◽  
Opinion Formation ◽  
Scale Free ◽  
Scale Free Networks ◽  
Free Network ◽  
Confidence Scale

We study the dynamics of minority opinion spreading using a proposed simple model, in which the exchange of views between agents is determined by a quantity named confidence scale. To understand what will promote the success of minority, two types of networks, random network and scale-free network are considered in opinion formation. We demonstrate that the heterogeneity of networks is advantageous to the minority and exchanging views between more agents will reduce the opportunity of minority's success. Further, enlarging the degree that agents trust each other, i.e. confidence scale, can increase the probability that opinions of the minority could be accepted by the majority. We also show that the minority in scale-free networks are more sensitive to the change of confidence scale than that in random networks.

scholarly journals Afrikaans as a complex network: The word co-occurrence network in André P. Brink’s Donkermaan in Afrikaans, Dutch and English

2016 ◽  
Vol 35 (1) ◽  
Author(s):  
Burgert A. Senekal ◽  
Cornelia Geldenhuys
Keyword(s):  
Complex Systems ◽  
Network Model ◽  
Network Structure ◽  
Random Network ◽  
Small World ◽  
Distribution Patterns ◽  
Small World Networks ◽  
Scale Free ◽  
Free Network ◽  
Link Distribution

Language has already been approached as a system since De Saussure, and recently the theory of complex systems has been applied within Linguistics as well. Complex systems, however, can also be modelled as complex networks, and a variety of studies investigating the network structure of language have already been undertaken worldwide. The current study follows in the footsteps of overseas studies and investigates the network structure of Afrikaans by analysing a word co-occurrence network compiled from André P. Brink’s novel Donkermaan. Link distribution patterns and the small-world phenomenon are investigated and then compared to the English and Dutch translations of this novel. The current study represents the first network study of Afrikaans. Firstly, the random network model of Erdös and Rényi and the scale-free network model by Barabási and Albert are used to indicate that the link distribution patterns in a word co-occurrence network of Afrikaans are better described according to the network model of Barabási and Albert than by that of Erdös and Rényi. Furthermore, the method proposed by Humphreys and Gurney to define smallworldedness (S) was used to quantify this phenomenon for the Afrikaans, as well as English and Dutch versions of the text. With 522 ≤ S ≤ 797, it is indicated that Afrikaans, English and Dutch are all clearly small-world networks. Suggestions are also made for further research.

scholarly journals DEVELOPMENT OF STATISTICALLY AVERAGED MODELS OF DEFORMATION OF MATERIALS WITH RANDOM NETWORK STRUCTURE OF DIFFERENTLY ORIENTED FIBERS

2021 ◽  
pp. 94-128
Author(s):  
Mykola M. Tkachuk
Keyword(s):  
Network Structure ◽  
Random Network ◽  
Strain Analysis ◽  
Physical And Mechanical Properties ◽  
Network Structures ◽  
Stress Strain ◽  
One Dimensional ◽  
Material Deformation ◽  
Averaged Models ◽  
Keywords Stress

The paper describes the developed statistically averaged models of deformation of materials with a random network structure of differently oriented fibers. New methods of stress-strain analysis and micromacromechanical models of material deformation in the volume of bodies made of material with a network structure taking into account structural and physical nonlinearities have been created. These models are based on the micromechanics of network structures at the level of statistical sets of their chains. The novelty of approaches, models, methods and results is the creation of theoretical foundations for the analysis of the deformation of non-traditional network materials. Nonlinear mathematical models of material deformation in the form of a chaotic network structure of one-dimensional fragments are proposed, which are constructed involving fundamentally new approaches to the description of physical and mechanical properties at the micro level of statistical sets of fiber chains and spatial homogenization of their macroproperties. Compared to traditional models, they more adequately model the features of material deformation in the form of spatial chaotic and ordered network structures, as they do not involve a number of additional non-physical hypotheses. This creates fundamentally new opportunities not only for analyzing the properties of such materials, but also when creating new ones with specified properties. Using the created methods, models and research tools, the basis for solving a number of model and applied problems has been created. The nature of deformation of non-traditional materials with a network structure of one-dimensional elements is determined. The macro-properties of these materials are established on the basis of the developed micromechanical models, variational formulations and averaging methods. Keywords: stress-strain state, network structures, contact interaction, finite element method, contact pressure, machine parts, variational formulation

scholarly journals Dual Cluster Model for Medium-Range Order in Metallic Glasses

Metals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1840
Author(s):  
Masato Shimono ◽  
Hidehiro Onodera
Keyword(s):  
Network Structure ◽  
Metallic Glasses ◽  
Random Network ◽  
Alloy System ◽  
Md Simulations ◽  
Range Order ◽  
Size Difference ◽  
Medium Range Order ◽  
Liquid Phases ◽  
Medium Range

The atomic structure of medium-range order in metallic glasses is investigated by using molecular dynamics (MD) simulations. Glass formation processes were simulated by rapid cooling from liquid phases of a model binary alloy system of different-sized elements. Two types of short-range order of atomic clusters with the five-fold symmetry are found in glassy phases: icosahedral clusters (I-clusters) formed around the smaller-sized atoms and Frank–Kasper clusters (i.e., Z14, Z15, and Z16 clusters (Z-clusters)) formed around the bigger-sized atoms. Both types of clusters (I-and Z-clusters) are observed even in liquid phases and the population of them goes up as the temperature goes down. A considerable atomic size difference between alloying elements would enhance the formation of both the I- and Z-clusters. In glassy phases, the I- and Z-clusters are mutually connected to form a complicated network, and the network structure becomes denser as the structural relaxation goes on. In the network, the medium-range order is mainly constructed by the volume sharing type connection between I- and Z-clusters. Following Nelson’s disclination theory, the network structure can be understood as a random network of Z-clusters, which is complimentarily surrounded by another type of network formed by I-clusters.

scholarly journals Learning Dynamics and Norm Psychology Supports Human Cooperation in a Large-Scale Prisoner’s Dilemma on Networks

Games ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 90 ◽  
Author(s):  
John Realpe-Gómez ◽  
Daniele Vilone ◽  
Giulia Andrighetto ◽  
Luis Nardin ◽  
Javier Montoya
Keyword(s):  
Social Norms ◽  
Network Structure ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Prisoner's Dilemma ◽  
Random Network ◽  
Prisoner’S Dilemma ◽  
Extended Model ◽  
Fixed Position ◽  
Learning Dynamics

In this work, we explore the role of learning dynamics and social norms in human cooperation on networks. We study the model recently introduced in [Physical Review E, 97, 042321 (2018)] that integrates the well-studied Experience Weighted Attraction learning model with some features characterizing human norm psychology, namely the set of cognitive abilities humans have evolved to deal with social norms. We provide further evidence that this extended model—that we refer to as Experience Weighted Attraction with Norm Psychology—closely reproduces cooperative patterns of behavior observed in large-scale experiments with humans. In particular, we provide additional support for the finding that, when deciding to cooperate, humans balance between the choice that returns higher payoffs with the choice in agreement with social norms. In our experiment, agents play a prisoner’s dilemma game on various network structures: (i) a static lattice where agents have a fixed position; (ii) a regular random network where agents have a fixed position; and (iii) a dynamic lattice where agents are randomly re-positioned at each game iteration. Our results show that the network structure does not affect the dynamics of cooperation, which corroborates results of prior laboratory experiments. However, the network structure does seem to affect how individuals balance between their self-interested and normative choices.

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