771,991 research outputs found

    Biyolojik ve biyolojik olmayan ağlar üzerine

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    With a general classification, there are two types of networks in the world: Biological and non-biological networks. We are unable to change the structure of biological networks. However, for networks such as social networks, technological networks and transportation networks, the architectures of non-biological networks are designed and can be changed by people. Networks can be classified as random networks, small-world networks and scale-free networks. However, we have problems with small-world networks and scale free networks. As some authors ask, “how small is a small-world network and how does it compare to other models?” Even the issue of scale-free networks are whether abundant or rare is still debated. Our main goal in this study is to investigate whether biological and non-biological networks have basic defining features. Especially if we can determine the properties of biological networks in a detailed way, then we may have the chance to design more robust and efficient non-biological networks. However, this research results shows that discussions on the properties of biological networks are not yet complete

    Collaboration in an Open Data eScience: A Case Study of Sloan Digital Sky Survey

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    Current science and technology has produced more and more publically accessible scientific data. However, little is known about how the open data trend impacts a scientific community, specifically in terms of its collaboration behaviors. This paper aims to enhance our understanding of the dynamics of scientific collaboration in the open data eScience environment via a case study of co-author networks of an active and highly cited open data project, called Sloan Digital Sky Survey. We visualized the co-authoring networks and measured their properties over time at three levels: author, institution, and country levels. We compared these measurements to a random network model and also compared results across the three levels. The study found that 1) the collaboration networks of the SDSS community transformed from random networks to small-world networks; 2) the number of author-level collaboration instances has not changed much over time, while the number of collaboration instances at the other two levels has increased over time; 3) pairwise institutional collaboration become common in recent years. The open data trend may have both positive and negative impacts on scientific collaboration.Comment: iConference 201

    Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

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    CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5 degrees latitude by 0.5 degrees longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901-2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically

    A century of international affairs think tanks in historical perspective

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    This essay surveys the operations of foreign policy think tanks, and how they have functioned to create transnational knowledge networks, since their emergence in the early twentieth century, around the First World War. It discusses how patterns of linkages among foreign policy think tanks changed and evolved over time, and were linked to broader Anglo-American, imperial, and internationalist networks and relationships, and to the changing international political climate and configuration. It suggests some ways in which think tanks contributed to Cold War interchanges between different states, especially to Soviet bloc–Western relations and Asian–Western relations. It concludes by discussing the recent proliferation and frequent globalization of foreign policy think tanks, and suggests how such trends may develop in future. Keywordspostprin

    DOBBS: Towards a Comprehensive Dataset to Study the Browsing Behavior of Online Users

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    The investigation of the browsing behavior of users provides useful information to optimize web site design, web browser design, search engines offerings, and online advertisement. This has been a topic of active research since the Web started and a large body of work exists. However, new online services as well as advances in Web and mobile technologies clearly changed the meaning behind "browsing the Web" and require a fresh look at the problem and research, specifically in respect to whether the used models are still appropriate. Platforms such as YouTube, Netflix or last.fm have started to replace the traditional media channels (cinema, television, radio) and media distribution formats (CD, DVD, Blu-ray). Social networks (e.g., Facebook) and platforms for browser games attracted whole new, particularly less tech-savvy audiences. Furthermore, advances in mobile technologies and devices made browsing "on-the-move" the norm and changed the user behavior as in the mobile case browsing is often being influenced by the user's location and context in the physical world. Commonly used datasets, such as web server access logs or search engines transaction logs, are inherently not capable of capturing the browsing behavior of users in all these facets. DOBBS (DERI Online Behavior Study) is an effort to create such a dataset in a non-intrusive, completely anonymous and privacy-preserving way. To this end, DOBBS provides a browser add-on that users can install, which keeps track of their browsing behavior (e.g., how much time they spent on the Web, how long they stay on a website, how often they visit a website, how they use their browser, etc.). In this paper, we outline the motivation behind DOBBS, describe the add-on and captured data in detail, and present some first results to highlight the strengths of DOBBS

    Perturbation of coupling matrices and its effect on the synchronizability in arrays of coupled chaotic systems

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    In a recent paper, wavelet analysis was used to perturb the coupling matrix in an array of identical chaotic systems in order to improve its synchronization. As the synchronization criterion is determined by the second smallest eigenvalue λ2\lambda_2 of the coupling matrix, the problem is equivalent to studying how λ2\lambda_2 of the coupling matrix changes with perturbation. In the aforementioned paper, a small percentage of the wavelet coefficients are modified. However, this result in a perturbed matrix where every element is modified and nonzero. The purpose of this paper is to present some results on the change of λ2\lambda_2 due to perturbation. In particular, we show that as the number of systems nn \to \infty, perturbations which only add local coupling will not change λ2\lambda_2. On the other hand, we show that there exists perturbations which affect an arbitrarily small percentage of matrix elements, each of which is changed by an arbitrarily small amount and yet can make λ2\lambda_2 arbitrarily large. These results give conditions on what the perturbation should be in order to improve the synchronizability in an array of coupled chaotic systems. This analysis allows us to prove and explain some of the synchronization phenomena observed in a recently studied network where random coupling are added to a locally connected array. Finally we classify various classes of coupling matrices such as small world networks and scale free networks according to their synchronizability in the limit.Comment: 7 pages, 2 figures, 1 tabl

    When Protests go Virtual: How Organizing Social Protest in Virtual Worlds Changes the Nature of Organizing

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    In this paper, we introduce a case study of social protest that has occurred in the virtual world Second Life. This case is a labor strike that occurred against IBM by Italian employees and a large European labor union. We begin with identifying the four key elements in the protest organizing process: Identifying Supporters, Organizing and Establishing Hierarchy, Getting the Word Out, and Building Solidarity/Establishing Social Networks. Next, we briefly examine how non-virtual technologies have changed the protest organizing process. Finally, we present our case data and illustrate how moving a protest to a fully virtual environment changes the organizing process. We conclude by asserting that three aspects fundamentally change protest organizing: entertainment, costs, and culture

    Effects of a Pandemic on Supply Chain Networks

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    The outbreak of COVID-19 has had a colossal impact on the lives of people across the globe. Just like the lives of the people who have had to live through this pandemic, supply chains around the world have been disrupted and permanently changed as well. 94% of Fortune 1000 companies have experienced supply chain disruptions as a result of COVID-19. The effects of the pandemic on global supply chains has not gone unnoticed, as many people had to make adjustments in their shopping to account for items that are always expected to be available suddenly not being able to be purchased. This project focuses on exploring why supply chain networks were disrupted by the pandemic and the consequences these disruptions had on the companies as well as their customers. I analyze three global supply chain networks that were challenged greatly by the pandemic and break down why the supply chain broke down, how the supply chain network originally should have been set up to avoid the risk of breaking down, and how the company attempted to fix their logistics after the disruption. This analysis provides a deeper understanding of how to properly set up a supply chain network to avoid the risk of a disruption by researching these real world examples, as well as how supply chain management will change in the future as a result of the pandemic
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