A graph theoretic model to understand the behavioral difference of PPCA among its paralogs towards recognition of DXCA

Social networks depict complex systems as graph theoretic models. The study of the formation of such systems (or networks) and the subsequent analysis of the network structures are of great interest. For information systems research and its impact on business practice, the ability to model and simulate a system of individuals interacting to achieve a certain socio-economic goal holds much promise for proper design and use of cyber networks. We use case-based decision theory to formulate a customizable model of information gathering in a social network. In this model, the agents in the network have limited awareness of the social network in which they operate and of the fixed, underlying payoff structure. Agents collect payoff information from neighbors within the prevailing social network, and they base their networking decisions on this information. Along with the introduction of the decision theoretic model, we developed software to simulate the formation of such networks in a customizable context to examine how the network structure can be influenced by the parameters that define social relationships. We present computational experiments that illustrate the growth and stability of the simulated social networks ensuing from the proposed model. The model and simulation illustrates how network structure influences agent behavior in a social network and how network structures, agent behavior, and agent decisions influence each other.

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A graph-theoretic model of symmetric givens operations and its implications

Linear Algebra and its Applications ◽

10.1016/s0024-3795(96)00157-7 ◽

1997 ◽

Vol 257 ◽

pp. 311-320 ◽

Cited By ~ 3

Author(s):

D.E. Stewart

Keyword(s):

Theoretic Model ◽

Graph Theoretic

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COMPUTING SHORTEST, FASTEST, AND FOREMOST JOURNEYS IN DYNAMIC NETWORKS

International Journal of Foundations of Computer Science ◽

10.1142/s0129054103001728 ◽

2003 ◽

Vol 14 (02) ◽

pp. 267-285 ◽

Cited By ~ 153

Author(s):

B. BUI XUAN ◽

A. FERREIRA ◽

A. JARRY

Keyword(s):

New Technologies ◽

Dynamic Networks ◽

Graph Model ◽

Temporal Variations ◽

Time Span ◽

Theoretic Model ◽

Arrival Date ◽

Hop Count ◽

Communications Networks ◽

Graph Theoretic

New technologies and the deployment of mobile and nomadic services are driving the emergence of complex communications networks, that have a highly dynamic behavior. This naturally engenders new route-discovery problems under changing conditions over these networks. Unfortunately, the temporal variations in the network topology are hard to be effectively captured in a classical graph model. In this paper, we use and extend a recently proposed graph theoretic model, which helps capture the evolving characteristic of such networks, in order to propose and formally analyze least cost journey (the analog of paths in usual graphs) in a class of dynamic networks, where the changes in the topology can be predicted in advance. Cost measures investigated here are hop count (shortest journeys), arrival date (foremost journeys), and time span (fastest journeys).

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Modeling, Analysis, and Comparison of Nanotechnology System: A Graph-Theoretic Approach

10.20944/preprints202007.0089.v1 ◽

2020 ◽

Author(s):

Tanvir Singh ◽

V.P. Agrawal

Keyword(s):

Graph Theory ◽

Complete Analysis ◽

Theoretic Model ◽

Theoretic Approach ◽

Graph Theoretic ◽

Systems Model ◽

System A ◽

Modeling Analysis ◽

Graph Theoretic Approach ◽

Permanent Function

Nanotechnology can create many new nanomaterials and nanodevices with a vast range of applications, such as in medicine, electronics, biomaterials, and energy production, etc. An attempt is made to develop an integrated systems model for the structure of the nanotechnology system in terms of its constituents and interactions between the constituents and processes, etc. using graph theory and matrix algebra. The nanotechnology system is first modeled with the help of graph theory, secondly by variable adjacency matrix and thirdly by multinomial (which is known as a permanent function). The permanent function provides an opportunity to carry out a structural analysis of nanotechnology system in terms of its strength, weakness, improvement, and optimization, by correlating the different systems with its structure. The physical meaning has been associated with each term of the permanent function. Different structural attributes of the nanotechnology system are identified concurrently to reduce cost, time for design and development, and also to develop a graph-theoretic model, matrix model, and multinomial permanent model of nanotechnology system. The top-down approach for a complete analysis of any nanotechnology systems is given. The general methodology is presented for the characterization and comparison of two nanotechnology systems.

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