scholarly journals Self-Organizing Networks in Complex Infrastructure Projects

2018 ◽  
Vol 49 (2) ◽  
pp. 18-41 ◽  
Author(s):  
Stephen Pryke ◽  
Sulafa Badi ◽  
Huda Almadhoob ◽  
Balamurugan Soundararaj ◽  
Simon Addyman
Keyword(s):  
Network Theory ◽  
Small World ◽  
Self Organization ◽  
Infrastructure Projects ◽  
Self Organized ◽  
Management Techniques ◽  
Path Lengths ◽  
High Degree ◽  
Self Organizing Networks ◽  
Self Organizing

While significant importance is given to establishing formal organizational and contractual hierarchies, existing project management techniques neglect the management of self-organizing networks in large-infrastructure projects. We offer a case-specific illustration of self-organization using network theory as an investigative lens. The findings have shown that these networks exhibit a high degree of sparseness, short path lengths, and clustering in dense “functional” communities around highly connected actors, thus demonstrating the small-world topology observed in diverse real-world self-organized networks. The study underlines the need for these non-contractual functions and roles to be identified and sponsored, allowing the self-organizing network the space and capacity to evolve.

SELF-ORGANIZED CORONA GRAPHS: A DETERMINISTIC COMPLEX NETWORK MODEL WITH HIERARCHICAL STRUCTURE

2019 ◽  
Vol 22 (06) ◽  
pp. 1950019
Author(s):  
ROHAN SHARMA ◽  
BIBHAS ADHIKARI ◽  
TYLL KRUEGER
Keyword(s):  
Power Law ◽  
Small World ◽  
Self Organization ◽  
Scale Free ◽  
Self Organized ◽  
Power Law Exponent ◽  
Growing Networks ◽  
Growing Network ◽  
Hierarchical Pattern ◽  
Corona Graphs

In this paper, we propose a self-organization mechanism for newly appeared nodes during the formation of corona graphs that define a hierarchical pattern in the resulting corona graphs and we call it self-organized corona graphs (SoCG). We show that the degree distribution of SoCG follows power-law in its tail with power-law exponent approximately 2. We also show that the diameter is less equal to 4 for SoCG defined by any seed graph and for certain seed graphs, the diameter remains constant during its formation. We derive lower bounds of clustering coefficients of SoCG defined by certain seed graphs. Thus, the proposed SoCG can be considered as a growing network generative model which is defined by using the corona graphs and a self-organization process such that the resulting graphs are scale-free small-world highly clustered growing networks. The SoCG defined by a seed graph can also be considered as a network with a desired motif which is the seed graph itself.

scholarly journals Una Exploración Conceptual de la Formación de Patrones en Sistemas Sociales Autorganizados

Ingeniería ◽  
2018 ◽  
Vol 23 (1) ◽  
pp. 84
Author(s):  
David Anzola
Keyword(s):  
Pattern Formation ◽  
Interdisciplinary Collaboration ◽  
Complexity Science ◽  
Self Organization ◽  
Social Self ◽  
Social Scientists ◽  
Self Organized ◽  
Scientists And Engineers ◽  
High Level ◽  
Self Organizing

Context: The concept of self-organization plays a major role in contemporary complexity science. Yet, the current framework for the study of self-organization is only able to capture some of the nuances of complex social self-organizing phenomena.Method: This article addresses some of the problematic elements in the study of social selforganization. For this purpose, it focuses on pattern formation, a feature of self-organizing phenomena that is common across definitions. The analysis is carried out through three main questions: where can we find these patterns, what are these patterns and how can we study these patterns.Results: The discussion shows that there is a high level of specificity in social self-organized phenomena that is not adequately addressed by the current complexity framework. It argues that some elements are neglected by this framework because they are relatively exclusive to social science; others, because of the relative novelty of social complexity.Conclusions: It is suggested that interdisciplinary collaboration between social scientists and complexity scientists and engineers is needed, in order to overcome traditional disciplinary limitations in the study of social self-organized phenomena.

Self-Organization and Peirce’s Notion of Communication and Semiosis

2011 ◽  
Vol 1 (2) ◽  
pp. 53-61
Author(s):  
João Queiroz ◽  
Angelo Loula
Keyword(s):  
Complex System ◽  
Artificial Life ◽  
Self Organization ◽  
Central Control ◽  
Local Interactions ◽  
Global Pattern ◽  
Self Organized ◽  
Experimental Protocols ◽  
Systemic Process ◽  
Self Organizing

Semiosis can be described as an emergent self-organizing process in a complex system of distributed sign users interacting locally and mutually affecting each other. Contextually grounded, semiosis is characterized as a pattern that emerges through the cooperation between agents in a communication act, which concerns an utterer, a sign, and an interpreter. Some implications of this approach are explored in the context of Artificial Life experimental protocols. To model communication as a self-organized process, the authors create a scenario to investigate a potentially self-organizing dynamic of communication, via local interactions. According to the results, a systemic process (symbol-based communication) emerges as a global pattern (a common repertoire of signs) from local interactions, without any external or central control.

scholarly journals An Approach to Determining the Spatially Contiguous Zone of a Self-Organized Urban Agglomeration

2019 ◽  
Vol 11 (12) ◽  
pp. 3490
Author(s):  
Fei Liu ◽  
Qing Huang
Keyword(s):  
Urban Agglomeration ◽  
Self Organization ◽  
Urban Agglomerations ◽  
Urban Dynamics ◽  
Self Organized ◽  
Spatial Features ◽  
Spatial Range ◽  
The One ◽  
Selection Of ◽  
Self Organizing

The evolution of the urban agglomeration is a significant development in urban geography. Determining its spatial range for effective measurement remains a challenge for researchers. In previous studies, determining spatial range has primarily been done through distinguishing the cities that should belong to urban agglomerations from among other cities by using various indicators. Both the selection of indicators and the standards used for calculation and identification have been based on subjective choices, and have not considered spatial distribution or morphology. The urban agglomeration can be regarded as a self-organized space, and spatial features of the fractal can be regarded as one of the morphological characterizations of spatial self-organization. From the perspective of the assumption that the space of urban agglomerations is molecule like assembled, and through the extraction and analysis of spatial fractals, we present an objective method to determine the “spatially contiguous zone” of urban agglomeration, particularly the spatial range in which the urban agglomeration is able to exercise jurisdiction within the radius of its capacity, rather than in the administrative division. Our method is applied in this paper to the Beijing–Tianjin–Hebei urban agglomeration and produced the following results: (1) the existence of spatial fractals and the theory of space unit molecule like self-organization or assembly in the morphology of urban agglomerations has been proved; and (2) a spatially contiguous zone could be identified for the urban agglomeration has been confirmed. Compared with previous methods used for determining space, this method is centered on the spatial morphology of urban agglomerations; the recognition of a spatially contiguous zone liberates the geographical limits of the result from city boundary restrictions. Concurrently, by considering the linkages within the city as a self-organizing black box, we can circumvent the one-sidedness involved with the selection of indicators that has biased previous studies, thereby avoiding having to focus on the specific mechanism of urban dynamics, and coming much closer to its self-organizing dynamic inner nature. This approach will prove to be a useful reference for the identification of spatial ranges in future studies.

Self-organized innovation networks from the perspective of complex systems

2018 ◽  
Vol 31 (5) ◽  
pp. 962-983 ◽  
Author(s):  
Adauto Lucas Silva ◽  
Fabio Müller Guerrini
Keyword(s):  
Complex Systems ◽  
Web Of Science ◽  
Organizational Management ◽  
Self Organization ◽  
Innovation Networks ◽  
Content Type ◽  
Self Organized ◽  
Analytical Perspective ◽  
Expected Benefits ◽  
Self Organizing

Purpose In order to deepen the understanding of self-organization, the purpose of the paper is to raise and analyze the state of the art in the area of innovation networks, particularly the characteristics of self-organizing, relying on the theory of complex systems to overcome any shortcomings. Design/methodology/approach The databases selected for the search were Web of Science and Scopus; the keywords searched in the titles of articles were innovation networks, complex systems, self-organization and self-organizing; the timeline of the search covers the period between 2000 and 2014 due to the presence of important studies in the field of networks starting in the early 2000s; only studies published in English were used; the articles selected were examined by first reading the titles, then the abstracts, and finally the texts in full. Findings The way the main constructs from the analytical perspective of innovation networks intersect with complex systems explains how self-organization is presented and how it can be allowed to occur within a view of expected benefits for the purposes of these networks. Originality/value The originality of the research lies in the questioning of the classical form of organizational management in innovation networks, essentially based on the concentration of hierarchical power.

scholarly journals Tuning the Spatially Controlled Growth, Structural Self-Organizing and Cluster-Assembling of the Carbyne-Enriched Nanostructured Metamaterials during Ion-Assisted Pulse-Plasma Deposition

2021 ◽  
Author(s):  
Alexander Lukin ◽  
Oğuz Gülseren
Keyword(s):  
Pattern Formation ◽  
Electric Field ◽  
Spatial Structure ◽  
Plasma Deposition ◽  
The Self ◽  
Self Organization ◽  
Structure And Properties ◽  
Self Organized ◽  
Wave Patterns ◽  
Self Organizing

Structural self-organizing and pattern formation are universal and key phenomena observed during growth and cluster-assembling of the carbyne-enriched nanostructured metamaterials at the ion-assisted pulse-plasma deposition. Fine tuning these universal phenomena opens access to designing the properties of the growing carbyne-enriched nano-matrix. The structure of bonds in the grown carbyne-enriched nano-matrices can be programmed by the processes of self-organization and auto-synchronization of nanostructures. We propose the innovative concept, connected with application of the universal Cymatics phenomena during the predictive growth of the carbyne-enriched nanostructured metamaterials. We also propose the self-organization approach for increase stability of the long linear carbon chains. The main idea of suggested concept is manipulating by the self-organized wave patterns excitation phenomenon and their distribution by the spatial structure and properties of the nanostructured metamaterial grows region through the new synergistic effect. Mentioned effect will be provided through the vibration-assisted self-organized wave patterns excitation along with simultaneous manipulating by their properties through the electric field. We propose to use acoustic activation of the plasma zone of nano-matrix growing. Interaction between the inhomogeneous electric field distribution generated on the vibrating layer and the plasma ions will serve as the additional energizing factor controlling the local pattern formation and self-organizing of the nano-structures. Suggested concept makes it possible to provide precise predictive designing the spatial structure and properties of the advanced carbyne-enriched nanostructured metamaterials.

scholarly journals ASSESSMENT OF AKURE ROAD NETWORK: A SHORTEST PATH APPROACH

2016 ◽  
Vol 19 (2) ◽  
Author(s):  
SEUN OLUWAJANA ◽  
OLUFIKAYO ADERINLEWO ◽  
ADEBAYO OWOLABI ◽  
SILVANA CROOPE
Keyword(s):  
Shortest Path ◽  
Road Network ◽  
Shortest Paths ◽  
Small World ◽  
Edge Length ◽  
The Road ◽  
Self Organized ◽  
Path Lengths ◽  
The City ◽  
Path Properties

<p>In this paper, the road network of Akure (a city in south western Nigeria) was studied based on its shortest path properties. Three sections, each measuring 1 square mile, were sampled from the entire road network and developed into graphs using both a primal approach and graph theory in which the intersections and streets were represented as nodes and edges respectively. These graphs were assessed for the edge lengths and shortest paths between nodes from which their edge length distributions, average path lengths and efficiencies were also obtained. It was concluded that the city of Akure is self-organized with small world properties since the network case studies showed small path lengths.</p>

Network Optimization Methods for Self-Organization of Future Cellular Networks

2016 ◽  
pp. 35-65 ◽  
Author(s):  
Furqan Ahmed ◽  
Alexis A. Dowhuszko ◽  
Olav Tirkkonen
Keyword(s):  
Cellular Networks ◽  
Network Optimization ◽  
Optimization Methods ◽  
Primary Component ◽  
Self Organization ◽  
Network Synchronization ◽  
Local Coordination ◽  
Self Organized ◽  
Network Utility ◽  
Self Organizing

This chapter discusses network optimization methods for enabling self-organization in current cellular networks such as Long Term Evolution (LTE)/LTE-Advanced (LTE-A), and the upcoming 5G networks. Discrete and continuous optimization models are discussed for developing distributed algorithms for self-configuration and self-optimization. The focus is on Self-Organized Networking (SON) problems, which are relevant to small cell networks. Examples include Physical Cell-ID (PCI) assignment, Primary Component Carrier (PCC) selection, Inter-Cell Interference Coordination (ICIC), and network synchronization. A conflict-graph model is considered for PCI assignment and PCC selection problems, which paves the way for different graph coloring algorithms with self-organizing properties. Algorithms for self-organized ICIC and network synchronization are also developed in a principled manner, through a network utility maximization framework. This systematic approach leads to a variety of algorithms which adhere to self-organization principles, but have varying requirements in terms of inter-cell coordination and computation complexity. Fully distributed self-organizing algorithms do not involve any inter-cell dedicated message-passing, and thus are faster and more scalable than the ones that are distributed but require local coordination via exchange of messages between cells. However, local coordination enables higher network utility and better convergence properties.

scholarly journals Cardioids reveal self-organizing principles of human cardiogenesis

2020 ◽  
Author(s):  
Pablo Hofbauer ◽  
Stefan Jahnel ◽  
Nora Papai ◽  
Magdalena Giesshammer ◽  
Mirjam Penc ◽  
...  
Keyword(s):  
Human Heart ◽  
Heart Defects ◽  
Bmp Signaling ◽  
Self Organization ◽  
List Type ◽  
Endothelial Lining ◽  
Heart Chamber ◽  
Self Organized ◽  
Signaling Axis ◽  
Self Organizing

SUMMARYOrganoids that self-organize into tissue-like structures have transformed our ability to model human development and disease. To date, all major organs can be mimicked using self-organizing organoids with the notable exception of the human heart. Here, we established self-organizing cardioids from human pluripotent stem cells that intrinsically specify, pattern and morph into chamber-like structures containing a cavity. Cardioid complexity can be controlled by signaling that instructs the separation of cardiomyocyte and endothelial layers, and by directing epicardial spreading, inward migration and differentiation. We find that cavity morphogenesis is governed by a mesodermal WNT-BMP signaling axis and requires its target HAND1, a transcription factor linked to human heart chamber cavity defects. In parallel, a WNT-VEGF axis coordinates myocardial self-organization with endothelial patterning and specification. Human cardioids represent a powerful platform to mechanistically dissect self-organization and congenital heart defects, serving as a foundation for future translational research.Highlights- Cardioids form cardiac-like chambers with inner endothelial lining and interact with epicardium- Cardioid self-organization and lineage complexity can be controlled by signaling- WNT-BMP signaling directs cavity formation in self-organized cardioids via HAND1- WNT-VEGF coordinate endothelial patterning with myocardial cavity morphogenesis

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