On symmetric continuum opinion dynamics

This paper investigates the asymptotic behavior of some common opinion dynamic models in a continuum of agents. We show that as long as the interactions among the agents are symmetric, the distribution of the agents' opinion converges. We also investigate whether convergence occurs in a stronger sense than merely in distribution, namely, whether the opinion of almost every agent converges. We show that while this is not the case in general, it becomes true under plausible assumptions on inter-agent interactions, namely that agents with similar opinions exert a non-negligible pull on each other, or that the interactions are entirely determined by their opinions via a smooth function.Comment: 28 pages, 2 figures, 3 file

Privacy-Friendly Collaboration for Cyber Threat Mitigation

Sharing of security data across organizational boundaries has often been advocated as a promising way to enhance cyber threat mitigation. However, collaborative security faces a number of important challenges, including privacy, trust, and liability concerns with the potential disclosure of sensitive data. In this paper, we focus on data sharing for predictive blacklisting, i.e., forecasting attack sources based on past attack information. We propose a novel privacy-enhanced data sharing approach in which organizations estimate collaboration benefits without disclosing their datasets, organize into coalitions of allied organizations, and securely share data within these coalitions. We study how different partner selection strategies affect prediction accuracy by experimenting on a real-world dataset of 2 billion IP addresses and observe up to a 105% prediction improvement.Comment: This paper has been withdrawn as it has been superseded by arXiv:1502.0533

Distributed anonymous function computation in information fusion and multiagent systems

We propose a model for deterministic distributed function computation by a network of identical and anonymous nodes, with bounded computation and storage capabilities that do not scale with the network size. Our goal is to characterize the class of functions that can be computed within this model. In our main result, we exhibit a class of non-computable functions, and prove that every function outside this class can at least be approximated. The problem of computing averages in a distributed manner plays a central role in our development

Distributed anonymous discrete function computation

We propose a model for deterministic distributed function computation by a network of identical and anonymous nodes. In this model, each node has bounded computation and storage capabilities that do not grow with the network size. Furthermore, each node only knows its neighbors, not the entire graph. Our goal is to characterize the class of functions that can be computed within this model. In our main result, we provide a necessary condition for computability which we show to be nearly sufficient, in the sense that every function that satisfies this condition can at least be approximated. The problem of computing suitably rounded averages in a distributed manner plays a central role in our development; we provide an algorithm that solves it in time that grows quadratically with the size of the network

Matrix P-norms are NP-hard to approximate if p \neq 1,2,\infty

We show that for any rational p \in [1,\infty) except p = 1, 2, unless P = NP, there is no polynomial-time algorithm for approximating the matrix p-norm to arbitrary relative precision. We also show that for any rational p\in [1,\infty) including p = 1, 2, unless P = NP, there is no polynomial-time algorithm approximates the \infty, p mixed norm to some fixed relative precision.Comment: 12 page

Origin of band gaps in 3d perovskite oxides

With their broad range of magnetic, electronic and structural properties, transition metal perovskite oxides ABO3 have long served as a platform for testing condensed matter theories. In particular, their insulating character - found in most compounds - is often ascribed to dynamical electronic correlations through the celebrated Mott-Hubbard mechanism where gaping arises from a uniform, symmetry-preserving electron repulsion mechanism. However, structural distortions are ubiquitous in perovskites and their relevance with respect to dynamical correlations in producing this rich array of properties remains an open question. Here, we address the origin of band gap opening in the whole family of 3d perovskite oxides. We show that a single-determinant mean-field approach such as density functional theory (DFT) successfully describes the structural, magnetic and electronic properties of the whole series, at low and high temperatures. We find that insulation occurs via energy-lowering crystal symmetry reduction (octahedral rotations, Jahn-Teller and bond disproportionation effects), as well as intrinsic electronic instabilities, all lifting orbital degeneracies. Our work therefore suggests that whereas ABO3 oxides may be complicated, they are not necessarily strongly correlated. It also opens the way towards systematic investigations of doping and defect physics in perovskites, essential for the full realization of oxide-based electronics

Mott gapping in 3d ABO3 perovskites without Mott-Hubbard interelectronic U

The existence of band gaps in Mott insulators such as perovskite oxides with partially filled 3d shells has been traditionally explained in terms of strong, dynamic inter-electronic repulsion codified by the on-site repulsion energy U in the Hubbard Hamiltonian. The success of the "DFT+U approach" where an empirical on-site potential term U is added to the exchange-and correlation Density Functional Theory (DFT) raised questions on whether U in DFT+U represents interelectronic correlation in the same way as it does in the Hubbard Hamiltonian, and if empiricism in selecting U can be avoided. Here we illustrate that ab-initio DFT without any U is able to predict gapping trends and structural symmetry breaking (octahedra rotations, Jahn-Teller modes, bond disproportionation) for all ABO3 3d perovskites from titanates to nickelates in both spin-ordered and spin disordered paramagnetic phases. We describe the paramagnetic phases as a supercell where individual sites can have different local environments thereby allowing DFT to develop finite moments on different sites as long as the total cell has zero moment. We use a recently developed exchange and correlation functional ("SCAN") that is sanctioned by the usual single-determinant, mean-field DFT paradigm with static correlations, but has a more precise rendering of self-interaction cancelation. Our results suggest that strong dynamic electronic correlations are not playing a universal role in gapping of 3d ABO3 Mott insulators, and opens the way for future applications of DFT for studying a plethora of complexity effects that depend on the existence of gaps, such as doping, defects, and band alignment in ABO3 oxides

Opioid Abuse as a Result of Work Related Trauma

Our studies examine and observe the widespread impact that prescription opioids have left on the United States, with a specific focus on working-class Americans and veterans. By narrowing our reach to Americans who are forced to handle large amounts of physical labor we have found a strong correlation between these workers getting injured on the job and opioid abuse. Finding that the it is generally attributed to overprescription and unnecessary prescription from physicians. The information was drawn from studies, surveys, dissertations and censuses. Observing these works on injuries/trauma caused by these occupations has yielded important information to the origin of this epidemic. These works can lead to understanding the problems associated with this correlation and further look for potential fixes that can be implemented. Although the number of prescriptions has lowered in recent years the number of prescriptions is still far too high to warrant neglecting this topic.https://orb.binghamton.edu/research_days_posters_spring2020/1086/thumbnail.jp