743 research outputs found
The Software Continuum Concept: Towards a Biologically Inspired Model for Robust E-Business Software Automation
This paper introduces a new concept, the software continuum concept based on the observation that exists a general parallelism between the software continuum from bits to business/Internet ecosystems and the natural continuum from particles to ecosystems. The general parallelism suggests that homeomorphisms may be identified and therefore some concepts, processes, and/or mechanisms in one continuum can be investigated for application in the other continuum. We argue that the homeomorphisms give rise to a biologically-inspired architectural framework for addressing robust control, robust intelligence, and robust autonomy issues in e-business software and other business-IT integration challenges. As application, we examine the mapping of a major enterprise-level architecture framework to the biologically-inspired framework. Design considerations for robust intelligence and autonomy in large-scale software automation and some major systemic features for flexible business-IT integration are also discussed
Outward Influence and Cascade Size Estimation in Billion-scale Networks
Estimating cascade size and nodes' influence is a fundamental task in social,
technological, and biological networks. Yet this task is extremely challenging
due to the sheer size and the structural heterogeneity of networks. We
investigate a new influence measure, termed outward influence (OI), defined as
the (expected) number of nodes that a subset of nodes will activate,
excluding the nodes in S. Thus, OI equals, the de facto standard measure,
influence spread of S minus |S|. OI is not only more informative for nodes with
small influence, but also, critical in designing new effective sampling and
statistical estimation methods.
Based on OI, we propose SIEA/SOIEA, novel methods to estimate influence
spread/outward influence at scale and with rigorous theoretical guarantees. The
proposed methods are built on two novel components 1) IICP an important
sampling method for outward influence, and 2) RSA, a robust mean estimation
method that minimize the number of samples through analyzing variance and range
of random variables. Compared to the state-of-the art for influence estimation,
SIEA is times faster in theory and up to several orders of
magnitude faster in practice. For the first time, influence of nodes in the
networks of billions of edges can be estimated with high accuracy within a few
minutes. Our comprehensive experiments on real-world networks also give
evidence against the popular practice of using a fixed number, e.g. 10K or 20K,
of samples to compute the "ground truth" for influence spread.Comment: 16 pages, SIGMETRICS 201
Importance Sketching of Influence Dynamics in Billion-scale Networks
The blooming availability of traces for social, biological, and communication
networks opens up unprecedented opportunities in analyzing diffusion processes
in networks. However, the sheer sizes of the nowadays networks raise serious
challenges in computational efficiency and scalability.
In this paper, we propose a new hyper-graph sketching framework for inflence
dynamics in networks. The central of our sketching framework, called SKIS, is
an efficient importance sampling algorithm that returns only non-singular
reverse cascades in the network. Comparing to previously developed sketches
like RIS and SKIM, our sketch significantly enhances estimation quality while
substantially reducing processing time and memory-footprint. Further, we
present general strategies of using SKIS to enhance existing algorithms for
influence estimation and influence maximization which are motivated by
practical applications like viral marketing. Using SKIS, we design high-quality
influence oracle for seed sets with average estimation error up to 10x times
smaller than those using RIS and 6x times smaller than SKIM. In addition, our
influence maximization using SKIS substantially improves the quality of
solutions for greedy algorithms. It achieves up to 10x times speed-up and 4x
memory reduction for the fastest RIS-based DSSA algorithm, while maintaining
the same theoretical guarantees.Comment: 12 pages, to appear in ICDM 2017 as a regular pape
Finding Community Structure with Performance Guarantees in Complex Networks
Many networks including social networks, computer networks, and biological
networks are found to divide naturally into communities of densely connected
individuals. Finding community structure is one of fundamental problems in
network science. Since Newman's suggestion of using \emph{modularity} as a
measure to qualify the goodness of community structures, many efficient methods
to maximize modularity have been proposed but without a guarantee of
optimality. In this paper, we propose two polynomial-time algorithms to the
modularity maximization problem with theoretical performance guarantees. The
first algorithm comes with a \emph{priori guarantee} that the modularity of
found community structure is within a constant factor of the optimal modularity
when the network has the power-law degree distribution. Despite being mainly of
theoretical interest, to our best knowledge, this is the first approximation
algorithm for finding community structure in networks. In our second algorithm,
we propose a \emph{sparse metric}, a substantially faster linear programming
method for maximizing modularity and apply a rounding technique based on this
sparse metric with a \emph{posteriori approximation guarantee}. Our experiments
show that the rounding algorithm returns the optimal solutions in most cases
and are very scalable, that is, it can run on a network of a few thousand nodes
whereas the LP solution in the literature only ran on a network of at most 235
nodes
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Cell viscoelasticity is linked to fluctuations in cell biomass distributions.
The viscoelastic properties of mammalian cells can vary with biological state, such as during the epithelial-to-mesenchymal (EMT) transition in cancer, and therefore may serve as a useful physical biomarker. To characterize stiffness, conventional techniques use cell contact or invasive probes and as a result are low throughput, labor intensive, and limited by probe placement. Here, we show that measurements of biomass fluctuations in cells using quantitative phase imaging (QPI) provides a probe-free, contact-free method for quantifying changes in cell viscoelasticity. In particular, QPI measurements reveal a characteristic underdamped response of changes in cell biomass distributions versus time. The effective stiffness and viscosity values extracted from these oscillations in cell biomass distributions correlate with effective cell stiffness and viscosity measured by atomic force microscopy (AFM). This result is consistent for multiple cell lines with varying degrees of cytoskeleton disruption and during the EMT. Overall, our study demonstrates that QPI can reproducibly quantify cell viscoelasticity
Regional Difference in Ethics Decision Making: A Study of IT Pre-professionals in China
Information and communications technology played a significant role in the recent economic growth of China, which now ranks as the second largest economy in the world. As a result, China faces many social and ethical challenges common to technology-advanced countries. Ethical reasoning and practices are often influenced by cultural expectations and regional norms. The purpose of this study is to investigate IT ethics decision making in different regions of China.An IT ethics survey was developed and administered in four regions in China with different degrees of westernization. The data were analyzed using standard cross tabulation and Chi-square test techniques. Preliminary results reveal observable differences among subjects from the four regions with respect to their decision choices, reasons for the choices, the scope of consideration, and the stage of their moral development. In particular, the subject group that was exposed to the strongest western influence, showed the highest degree of individualism in ethics decision making
Exclusive semileptonic decays of and mesons in the covariant confining quark model
Recently, the BESIII collaboration has reported numerous measurements of
various meson semileptonic decays with significantly improved
precision. Together with similar studies carried out at BABAR, Belle, and CLEO,
new windows to a better understanding of weak and strong interactions in the
charm sector have been opened. In light of new experimental data, we review the
theoretical description and predictions for the semileptonic decays of
to a pseudoscalar or a vector meson. This review is essentially an
extended discussion of our recently published results obtained in the framework
of the covariant confining quark model.Comment: 51 pages, 12 figures, 29 tables, to be submitted to Frontiers of
Physics as a revie
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