1,069 research outputs found

    An Improved Traffic Matrix Decomposition Method with Frequency-Domain Regularization

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    We propose a novel network traffic matrix decomposition method named Stable Principal Component Pursuit with Frequency-Domain Regularization (SPCP-FDR), which improves the Stable Principal Component Pursuit (SPCP) method by using a frequency-domain noise regularization function. An experiment demonstrates the feasibility of this new decomposition method.Comment: Accepted to IEICE Transactions on Information and System

    Mercury methylation in boreal peatlands: Influence of geochemistry and biology

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    Methylmercury (MeHg) is a neurotoxin mainly produced by microorganisms in suboxic and anoxic environments such as peatlands. Peatlands are an important source of MeHg in adjacent aquatic ecosystems, thus increasing the risk of human and wildlife exposure to this toxic compound. An improved understanding of factors limiting microbial net MeHg formation in peatlands could benefit the management and mitigation of this toxic compound particularly in peatland-rich landscapes. In this thesis, a chronosequence trophic gradient of peatlands within the space of a few kilometers, all subjected to similar atmospheric deposition, underlying geology and climate patterns, was studied to determine the influence of biogeochemical factors on net MeHg formation in peat. Along the peatland chronosequence, higher net MeHg formation in peat soil of the younger peatlands was attributed to more nutrient rich conditions (Paper I). The same trend in net MeHg formation was observed in porewater, which was deemed more related to the shifts in the availability of electron acceptors for methylating microorganisms than to the abundance of electron donors (Paper II). The results of modeling the solubility of Hg(II) suggest that the net MeHg formation along the chronosequence could also be influenced by the supply of bioavailable Hg(II) to methylating organisms (Paper II). The microbial community composition was significantly correlated to net MeHg formation along the chronosequence, with spatial patterns driven by environmental factors (Paper IV). Laboratory incubations with a combination of amended inhibitors/stimulators revealed the presence of different microbial processes in relation to the biogeochemistry. These differences are suggested to contribute to net MeHg formation along the chronosequence (Paper III). Quantitative gene expressions of specific microbial functional groups suggest that the role of SRB in net MeHg formation varied across the chronosequence, while methanogenic archaea were important for this across all the peatlands (Paper IV)

    Strain-engineered magnetic order in (LaMnO3_{3})n_n/(SrMnO3_{3})2n_{2n} superlattices

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    Using first-principles calculations based on the density functional theory, we show a strong strain dependence of magnetic order in (LaMnO3_{3})n_n/(SrMnO3_{3})2n_{2n} (001) superlattices with n=1,2n=1,2. The epitaxial strain lifts the degeneracy of Mn ege_{g} orbitals, thus inducing an inherent orbital order, which in turn strongly affects the ferromagnetic double exchange of itinerant ege_{g} electrons, competing with the antiferromagnetic superexchange of localized t2gt_{2g} electrons. For the case of tensile strain induced by SrTiO3_3 (001) substrate, we find that the ground state is A-type antiferromagnetic and dx2−y2d_{x^2-y^2} orbital ordered, which is in excellent agreement with recent experiments [S. J. May {\it et al.}, Nature Materials {\bf 8}, 892 (2009)]. Instead, for the case of compressive strain induced by LaAlO3_3 (001) substrate, we predict that the ground state is C-type antiferromagnetic and d3z2−r2d_{3z^2-r^2} orbital ordered.Comment: The paper is accepted for publication in Phys. Rev.

    Sliding mode control of a 2-DOF manipulator with random base vibration based on modified exponential reaching law

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    To solve the precise position control problem of a two degree of freedom (2-DOF) manipulator with random base vibration, a sliding mode control method based on modified exponential reaching law is studied. The dynamic model of manipulator is established by using the second kind Lagrange equation. The nonlinear term generated by base random vibration is presented as external disturbance term. Based on dynamic models, the sliding mode control using improved exponential reaching law is applied in the manipulator system. It is verified by the simulation result that the control method can effectively suppress the influence of base random vibration, and bring the manipulator from a given initial state to a prescribed terminal state rapidly and precisely

    Structural Analysis of Network Traffic Matrix via Relaxed Principal Component Pursuit

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    The network traffic matrix is widely used in network operation and management. It is therefore of crucial importance to analyze the components and the structure of the network traffic matrix, for which several mathematical approaches such as Principal Component Analysis (PCA) were proposed. In this paper, we first argue that PCA performs poorly for analyzing traffic matrix that is polluted by large volume anomalies, and then propose a new decomposition model for the network traffic matrix. According to this model, we carry out the structural analysis by decomposing the network traffic matrix into three sub-matrices, namely, the deterministic traffic, the anomaly traffic and the noise traffic matrix, which is similar to the Robust Principal Component Analysis (RPCA) problem previously studied in [13]. Based on the Relaxed Principal Component Pursuit (Relaxed PCP) method and the Accelerated Proximal Gradient (APG) algorithm, we present an iterative approach for decomposing a traffic matrix, and demonstrate its efficiency and flexibility by experimental results. Finally, we further discuss several features of the deterministic and noise traffic. Our study develops a novel method for the problem of structural analysis of the traffic matrix, which is robust against pollution of large volume anomalies.Comment: Accepted to Elsevier Computer Network
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