Concept Of Centrality Research Articles

Decentralized Supervision of Petri Nets

This note extends previous results on the supervision of Petri nets (PNs) to the decentralized setting. While focusing on the extension of supervision based on place invariants (SBPI), the proposed approach is more general and could be applied to other types of supervision as well. We begin by introducing d-admissibility as an extension to the decentralized setting of the centralized admissibility concept. We define also structural d-admissibility, as the counterpart of the simple sufficient conditions for centralized admissibility in the context of the SBPI. Note that (structural) d-admissibility is only sufficient for a specification to be enforcible with the same permissiveness as in the centralized setting with full controllability and observability. However, structural d-admissibility can be checked with low polynomial complexity. Based on the d-admissibility concept, we propose two suboptimal methods to design decentralized supervisors. The first method is to find a centralized solution, and then distribute the centralized supervisory policy by means of communication. The amount of communication can be minimized by means of an integer linear program (ILP). The second method is to transform the specification to a (more restrictive) d-admissible specification by means of an ILP. In the case of decentralized supervision with communication, the ILP can be used to minimize the amount of communication required by the solution.

A Graph-theoretic perspective on centrality

The concept of centrality is often invoked in social network analysis, and diverse indices have been proposed to measure it. This paper develops a unified framework for the measurement of centrality. All measures of centrality assess a node's involvement in the walk structure of a network. Measures vary along four key dimensions: type of nodal involvement assessed, type of walk considered, property of walk assessed, and choice of summary measure. If we cross-classify measures by type of nodal involvement (radial versus medial) and property of walk assessed (volume versus length), we obtain a four-fold polychotomization with one cell empty which mirrors Freeman's 1979 categorization. At a more substantive level, measures of centrality summarize a node's involvement in or contribution to the cohesiveness of the network. Radial measures in particular are reductions of pair-wise proximities/cohesion to attributes of nodes or actors. The usefulness and interpretability of radial measures depend on the fit of the cohesion matrix to the one-dimensional model. In network terms, a network that is fit by a one-dimensional model has a core-periphery structure in which all nodes revolve more or less closely around a single core. This in turn implies that the network does not contain distinct cohesive subgroups. Thus, centrality is shown to be intimately connected with the cohesive subgroup structure of a network.

Subgraph centrality and clustering in complex hyper-networks

The representation of complex systems as networks is inappropriate for the study of certain problems. We show several examples of social, biological, ecological and technological systems where the use of complex networks gives very limited information about the structure of the system. Consequently, we extend the concepts of subgraph centrality and clustering for complex networks represented by hypergraphs: complex hyper-networks. The first parameter characterizes the node participation in different sub-hypergraphs and the second one characterizes the transitivity in the hyper-network through the proportion of hyper-triangles to paths of length two. Another measure characterizing the formation of triples of mutually adjacent groups in the hyper-network is also introduced. All of these characteristics are studied in three different hyper-networks: a scientific collaboration hyper-network, an ecological competition hyper-network and the hyper-network formed by the American corporate elite in 1999.

From centrality to temporary fame: Dynamic centrality in complex networks

We develop a new approach to the study of the dynamics of link utilization in complex networks using records of communication in a large social network. Counter to the perspective that nodes have particular roles, we find roles change dramatically from day to day. “Local hubs” have a power law degree distribution over time, with no characteristic degree value. Our results imply a significant reinterpretation of the concept of node centrality in complex networks, and among other conclusions suggest that interventions targeting hubs will have significantly less effect than previously thought. © 2006 Wiley Periodicals, Inc. Complexity 12: 59–63, 2006

Particle Identification in High Energy Collisions at RHIC

This article provides a technical introduction to the study of collider physics by focusing on the concept of particle identification (PID). Through a general overview of the Relativistic Heavy Ion Collider (RHIC) and the Pioneering High Energy Nuclear Interaction Experiment (PHENIX), the author discusses the role of Vanderbilt University researchers in collaborative work at the Brookhaven National Laboratory. After explaining the concept of event reconstruction and centrality with graphical images of experimental results, the author outlines the time-of-flight method of particle identification in high energy physics. A final presentation of the design concept for the Multi-Gap Resistive Plate Chamber (MRPC) integrates the more traditional foundations of theoretical physics with the next generation of physics experimentation in the field.

LexRank: Graph-based Lexical Centrality as Salience in Text Summarization

We introduce a stochastic graph-based method for computing relative importance of textual units for Natural Language Processing. We test the technique on the problem of Text Summarization (TS). Extractive TS relies on the concept of sentence salience to identify the most important sentences in a document or set of documents. Salience is typically defined in terms of the presence of particular important words or in terms of similarity to a centroid pseudo-sentence. We consider a new approach, LexRank, for computing sentence importance based on the concept of eigenvector centrality in a graph representation of sentences. In this model, a connectivity matrix based on intra-sentence cosine similarity is used as the adjacency matrix of the graph representation of sentences. Our system, based on LexRank ranked in first place in more than one task in the recent DUC 2004 evaluation. In this paper we present a detailed analysis of our approach and apply it to a larger data set including data from earlier DUC evaluations. We discuss several methods to compute centrality using the similarity graph. The results show that degree-based methods (including LexRank) outperform both centroid-based methods and other systems participating in DUC in most of the cases. Furthermore, the LexRank with threshold method outperforms the other degree-based techniques including continuous LexRank. We also show that our approach is quite insensitive to the noise in the data that may result from an imperfect topical clustering of documents.

Hyper-edges and multidimensional centrality

Abstract Many social transactions are supra-dyadic; they either involve more than two participants (buyer, seller, broker) or they involve important aspects of the interaction’s setting, tike its timing or its location. Standard network techniques do not adequately plumb these networks. Using the concept of a hypergraph [Berge, C. 1973, Graphs and Hypergraphs], this paper shows how the concept of network centrality can be adapted to supra-dyadic networks. Use of the technique is illustrated with data on attacks by inhabitants of Caribbean islands on Spanish settlements in the period 1509–1700.

Centers in Connected Undirected Graphs: An Axiomatic Approach

A center is a function that associates with every finite connected and undirected graph a nonempty subset of its vertices. These functions play an important role in networks such as social or interorganizational networks. Centers capture notions like: being a focal point of communication, being strategically located, ability and willingness to participate in strategic alliances, and the like. We focus on the conceptual issue of what makes a position in a graph a central one and investigate some possible concepts of centrality in relation to various properties. Characterizations of the uncovered center, the median, and degree center are presented, where each of these centers is defined for arbitrary connected undirected simple, and possibly cyclic, graphs.

Distance, dissimilarity index, and network community structure

We address the question of finding the community structure of a complex network. In an earlier effort [H. Zhou, Phys. Rev. E 67, 041908 (2003)], the concept of network random walking is introduced and a distance measure defined. Here we calculate, based on this distance measure, the dissimilarity index between nearest-neighboring vertices of a network and design an algorithm to partition these vertices into communities that are hierarchically organized. Each community is characterized by an upper and a lower dissimilarity threshold. The algorithm is applied to several artificial and real-world networks, and excellent results are obtained. In the case of artificially generated random modular networks, this method outperforms the algorithm based on the concept of edge betweenness centrality. For yeast's protein-protein interaction network, we are able to identify many clusters that have well defined biological functions.

Fast Polyhedral Adaptive Conjoint Estimation

Web-based customer panels and web-based multimedia capabilities offer the potential to get information from customers rapidly and iteratively based on virtual product profiles. However, web-based respondents are impatient and wear out more quickly. At the same time, in commercial applications, conjoint analysis is being used to screen large numbers of product features. Both of these trends are leading to a demand for conjoint analysis methods that provide reasonable estimates with fewer questions in problems involving many parameters. In this paper we propose and test new adaptive conjoint analysis methods that attempt to reduce respondent burden while simultaneously improving accuracy. We draw on recent interior-point developments in mathematical programming which enable us to quickly select those questions that narrow the range of feasible partworths as fast as possible. We then use recent centrality concepts (the analytic center) to estimate partworths. These methods are efficient, run with no noticeable delay in web-based questionnaires, and have the potential to provide estimates of the partworths with fewer questions than extant methods. After introducing these we implement one such algorithm and test it with Monte Carlo simulation against benchmarks such as efficient (fixed) designs and Adaptive Conjoint Analysis (ACA). While no method dominates in all situations, the polyhedral algorithm appears to hold significant potential when (a) profile comparisons are more accurate than the self-explicated importance measures used in ACA, (b) when respondent wear out is a concern, and (c) when the product development and marketing teams wish to screen many features quickly. We also test a hybrid method that combines polyhedral question selection with ACA estimation and show that it, too, has the potential to improve predictions in many contexts. The algorithm we test helps to illustrate how polyhedral methods can be combined effectively and synergistically with the wide variety of existing conjoint analysis methods. We close with suggestions on how polyhedral algorithms can be used in other preference measurement contexts (e.g., choice-based conjoint analysis) and other marketing problems.

Virtual Reality and the Person–Environment Experience

This paper discusses how a projected virtual reality system that uses video gesture recognition technology can influence the person-environment process. The psychosocial concepts of embodiment, environmental centralization, and environmental personalization are illustrated with examples of virtual reality applications with children with disabilities. Through these, the advantages of using virtual reality to influence the person-environment relationship are discussed. Disadvantages of implementing this virtual reality approach are also presented as well as recommendations for future work in this area.

Using centrality modeling in network surveys

In a well-known paper [Social Networks 1 (1979) 215] Linton Freeman clarified the importance of the centrality concept in network analysis. There are a variety of centrality measures available, and they are mainly used as descriptive statistics in various network studies. For instance, actor centrality measured by vertex degree captures those aspects of centrality that have an impact on contacts given or received by the actor. The approach taken here is to consider actor centrality as a latent property that manifests itself in generating a particular network structure, and in order to measure centrality we are bound to rely on observable features of this network. By borrowing ideas from recent link-tracing survey methodology, we illustrate how probabilistic network models with centrality parameters can be used to improve on estimators and predictors of various actor attributes related to centrality.

A Graph Partitioning Scheme and Applications to Fault Tolerant Computing

Abstract Abstract This paper presents a method for finding a partition of a graph that can be applied to many problems related to fault-tolerant computing. The applications range from computer networks to distributed software design. All applications have in common that specific nodes should be selected for the placement of entities such as servers or objects. The method is based on the well known Cut Trees and centrality concepts on graphs. Acknowledgements I would like to express my gratitude to Elias P. Duarte Jr. for constantly motivating my research and for all valuable advice.

PRESIDENTIAL INFLUENCE AND CENTRALIZATION: THE CASE OF NIXON AND GEORGE ROMNEY

Political scientists have always been interested in presidential influence in American politics, but they have rarely explored the process of centralization as a mechanism for presidents to exert their influence. To date, Terry Moe has developed the best conceptual framework for understanding presidential influence in general and centralization in particular. We rely on and go beyond Moe's concept of centralization in a study of fair housing policy during the Nixon administration. Though we conclude that centralization may potentially be detrimental to existing democratic structures, there are cases where centralization may be the only viable alternative for a president to secure policy outputs in accordance with his desired outcomes.

Fast Polyhedral Adaptive Conjoint Estimation

Web-based customer panels and web-based multimedia capabilities offer the potential to get information from customers rapidly and iteratively based on virtual product profiles. However, web-based respondents are impatient and wear out more quickly. At the same time, in commercial applications, conjoint analysis is being used to screen large numbers of product features. Both of these trends are leading to a demand for conjoint analysis methods that provide reasonable estimates with fewer questions in problems involving many parameters. In this paper we propose and test new adaptive conjoint analysis methods that attempt to reduce respondent burden while simultaneously improving accuracy. We draw on recent interior-point developments in mathematical programming which enable us to quickly select those questions that narrow the range of feasible partworths as fast as possible. We then use recent centrality concepts (the analytic center) to estimate partworths. These methods are efficient, run with no noticeable delay in web-based questionnaires, and have the potential to provide estimates of the partworths with fewer questions than extant methods. After introducing these we implement one such algorithm and test it with Monte Carlo simulation against benchmarks such as efficient (fixed) designs and Adaptive Conjoint Analysis (ACA). While no method dominates in all situations, the polyhedral algorithm appears to hold significant potential when (a) profile comparisons are more accurate than the self-explicated importance measures used in ACA, (b) when respondent wear out is a concern, and (c) when the product development and marketing teams wish to screen many features quickly. We also test a hybrid method that combines polyhedral question selection with ACA estimation and show that it, too, has the potential to improve predictions in many contexts. The algorithm we test helps to illustrate how polyhedral methods can be combined effectively and synergistically with the wide variety of existing conjoint analysis methods. We close with suggestions on how polyhedral algorithms can be used in other preference measurement contexts (e.g., choice-based conjoint analysis) and other marketing problems.

Founder Centrality and Strategic Behavior in the Family-Owned Firm

This paper explores how founders influence strategic management in the family business. The authors suggest it is essential to consider the central influence of a family firm's founder on the top management group and on the firm's strategic values, goals, and behavior. They further posit that a founder can be expected to shape the family firm's interactions with the external environment. The authors explore the central role that a founder plays in a family business from a social network perspective and establish the basis for the founder centrality concept. Further, they develop a framework and propositions from which the founder's influence on strategic behavior and performance may be studied.

House design by surname in Feng Shui

Feng Shui is an exclusive Chinese cultural achievement and experience in architecture. This paper reviews one special Feng Shui model for the selection of auspicious orientations for house elements such as the main entrance, kitchen, or bedrooms, based on the classification of surnames. Investigation of original references and historical literature reveals that this model has been mentioned, but never analysed in detail. Four significant Feng Shui concepts forming the theoretical aspect of the model have been revealed. These four concepts are the Five Elements, the Magic Square, the concept of centrality and the layout of the Chinese courtyard house.

Preface

NetworksVolume 34, Issue 4 p. 243-243 Preface Fred Buckley, Fred Buckley Mathematics Department, Baruch College (CUNY), New York, NY 10010Search for more papers by this author Fred Buckley, Fred Buckley Mathematics Department, Baruch College (CUNY), New York, NY 10010Search for more papers by this author First published: 05 November 1999 https://doi.org/10.1002/(SICI)1097-0037(199912)34:4<243::AID-NET1>3.0.CO;2-RCitations: 1AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article.Citing Literature Volume34, Issue4Special Issue: Centrality Concepts in Network LocationDecember 1999Pages 243-243 RelatedInformation

Finite algebras of finite complexity

We develop a new centrality concept and apply it to solve certain outstanding problems about finite algebras. In particular, we describe all finite algebras of finite complexity and all finite strongly abelian algebras which generate residually small varieties.

The lost centre: Magnitogorsk revisited

The following article sketches the history of Magnitogorsk, once the most exciting new industrial city in the Soviet Union under Stalin, and recently experiencing the problems of a city in transition. It is argued that even under a rigid planned economy city development is shaped by continuously changing paradigms. It is interesting to find the political and economic history of the city expressed in its design, and to note its richness in urban fabric and architectural detail. It is shown that the city, once outlined for the socialist way of life, nowadays has to adapt radically to the capitalist economy. This process can best be studied by looking at the central functions of the city. Magnitogorsk is an interesting example of a city that creates an unusual pattern of centres as a result of its history and the ongoing adaptation. The pattern is interpreted by looking closely at the concept of centrality. Finally, the potential of the city that lies in the central lake — separating and connecting at the same time — is illustrated.