Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning

Federated learning is a distributed framework for training machine learning models over the data residing at mobile devices, while protecting the privacy of individual users. A major bottleneck in scaling federated learning to a large number of users is the overhead of secure model aggregation across many users. In particular, the overhead of the state-of-the-art protocols for secure model aggregation grows quadratically with the number of users. In this paper, we propose the first secure aggregation framework, named Turbo-Aggregate, that in a network with $N$ users achieves a secure aggregation overhead of $O(N\log{N})$, as opposed to $O(N^2)$, while tolerating up to a user dropout rate of $50\%$. Turbo-Aggregate employs a multi-group circular strategy for efficient model aggregation, and leverages additive secret sharing and novel coding techniques for injecting aggregation redundancy in order to handle user dropouts while guaranteeing user privacy. We experimentally demonstrate that Turbo-Aggregate achieves a total running time that grows almost linear in the number of users, and provides up to $40\times$ speedup over the state-of-the-art protocols with up to $N=200$ users. Our experiments also demonstrate the impact of model size and bandwidth on the performance of Turbo-Aggregate

D0D^0 production rate measurement in neutrino interactions and a limit on muon neutrino to tau neutrino oscillations

The CHORUS experiment was designed to search for \nu_\mu---> \nu_\tau oscillations. Recently, Phase I analysis has been completed and no \tau candidate is found. The second phase of the CHORUS analysis was recently started with new scanning systems. The big improvements in the scanning system and methods allow the CHORUS experiment to study also charm physics with large statistics. In this work, D^0 production rate in neutrino charged-current interactions has been evaluated using 122 D^0 candidates found in 8028 located \nu_\mu charged-current interactions in the collaboration, as; \sigma(\nu_mu N--> D^0\mu^-X)/sigma(\nu_mu N--> \mu^-X)= 1.998 \pm 0.223%. The achived precision of the production rate exceeds that of the previous experiments

OPERA neutrino oscillation results

The OPERA experiment was designed to perform the first detection of νμ → ντ neutrino oscillations in a direct appearance mode. We present the analysis results of the 2008–2009 statistics corresponding to 4.88 × 1019 p.o.t. In this sample, one ντ candidate event has been observed in the τ → h channel. The statistical significance of this observation is estimated to be 95%

Effect of feeding regime on fatty acid composition and conjugated linoleic acid content of perirenal, omental and tail fat in Akkaraman lambs

In this study, the effect of feeding regime on fatty acid composition including conjugated linoleic acid (CLA) of omental, perirenal and tail fat from Akkaraman lambs, the most widespread sheep breed in central Anatolia, was investigated. Forty-five suckling lambs, born in the same farm, were fed mainly maternal milk from birth to weaning and then the lambs were divided into three groups. One group (maternal milk-fed group) of the lambs was directly slaughtered after weaning. A second group (pasture group) was allowed to graze a natural pasture and slaughtered at three months after weaning. Third group (concentrate group) was fed concentrate ad-libitum together with 150 g/day alfalfa and slaughtered at three months after weaning. In all feeding regime, the predominant fatty acids were C 16:0 palmitic and C 18:0 stearic acid as saturated fatty acid (SFA), C 18:1ω9 oleic acid as monounsaturated fatty acid (MUFA) and C 18:2 ω6 linoleic acid as polyunsaturated fatty acid (PUFA). Omental, perirenal and tail fat of the pasture-fed lambs contained more total CLA, total ω3, ω3/ω6ratio compared with that of the concentrate-fed lambs. Moreover, omental, perirenal and tail fat of concentrate-fed lambs had higher ω6/ω3 ratio and this ratio was decreased by pasture feeding.Key words: Akkaraman lambs, pasture, suckling, concentrate, fatty acid composition, conjugated linoleic acid

Predicting Shear Capacity of RC Beams Strengthened with NSM FRP Using Neural Networks

This research aims to predict the shear capacity of NSM FRP beams using the neural network method. The study investigates the key considerations and the necessary analysis for this prediction. NSM FRP beams are reinforced concrete beams that are strengthened with near-surface mounted (NSM) fiber-reinforced polymer (FRP) composites. Accurately predicting their shear capacity is important for ensuring their safety and reliability in real-world applications. The neural network method is a machine learning approach that is increasingly used in engineering analysis and design. The study explores how this method can be used to predict the shear capacity of NSM FRP beams and what factors should be taken into account in this analysis. The research also discusses the analytical approach required for this prediction, highlighting the necessary steps for obtaining accurate results. Overall, this study provides valuable insights into the use of the neural network method for predicting the shear capacity of NSM FRP beams. The findings can help inform future research and practical applications in the field of structural engineering, contributing to the development of safer and more reliable structures

Indentation of a free beam resting on an elastic substrate with an internal lengthscale

The plane strain problem of a slender and weightless beam-plate loaded by a transversal point force in unilateral contact with a couple stress elastic foundation is investigated. The study aims to explore the consequences of the material internal lengthscale on the contact mechanics. In particular, compatibility between the beam and the foundation surface demands that both displacement and rotation match along the contact line. To this aim, couple tractions are exchanged besides the traditional contact pressure until separation between the beam and the foundation occurs. The problem is formulated making use of the Green's functions for a point force and a point couple acting atop of a couple stress elastic half-plane. A pair of coupled integral equations is thus derived, that governs the distribution of contact pressure and couple tractions, with one of them being immediately solved to provide an explicit relation between the two unknowns. In this sense, we retrieve the concept of a mechanically equivalent action, as it is the case of the Kirchhoff shear for plates. The remaining integral equation sets a cubic eigenvalue problem, whose linear term accounts for the microstructure. Its numerical solution is sought by expanding the equivalent contact pressure in series of Chebyshev polynomials vanishing at the contact region ends points, namely the lift-off points, and then applying a collocation strategy. The contact length, the distributions of contact pressure and couple tractions under the beam and the shearing force and bending moment along the beam are then obtained as a function of the material characteristic length. Results clearly indicate that accounting for the material internal lengthscale is mainly realized through exchange of the couple tractions, in the lack of which results much resemble those of the classical solution. Specifically, greater contact lengths and a stronger focusing effect about the loading point are encountered, which become very significant when the contact length approaches the internal lengthscale

High precision determination of the Q2Q^2-evolution of the Bjorken Sum

We present a significantly improved determination of the Bjorken Sum for 0.6$\leq Q^{2}\leq$4.8 GeV$^{2}$ using precise new $g_{1}^{p}$ and $g_{1}^{d}$ data taken with the CLAS detector at Jefferson Lab. A higher-twist analysis of the $Q^{2}$-dependence of the Bjorken Sum yields the twist-4 coefficient $f_{2}^{p-n}=-0.064 \pm0.009\pm_{0.036}^{0.032}$. This leads to the color polarizabilities $\chi_{E}^{p-n}=-0.032\pm0.024$ and $\chi_{B}^{p-n}=0.032\pm0.013$. The strong force coupling is determined to be \alpha_{s}^{\overline{\mbox{ MS}}}(M_{Z}^{2})=0.1124\pm0.0061, which has an uncertainty a factor of 1.5 smaller than earlier estimates using polarized DIS data. This improvement makes the comparison between $\alpha_{s}$ extracted from polarized DIS and other techniques a valuable test of QCD.Comment: Published in Phys. Rev. D. V1: 8 pages, 3 figures. V2: Updated references; Included threshold matching in \alpha_s evolution. Corrected a typo on the uncertainty for \Lambda_QCD. V3: Published versio

Non-cooperative joint replenishment under asymmetric information

Cataloged from PDF version of article.We consider jointly replenishing n ex-ante identical firms that operate under an EOQ like setting using a non-cooperative game under asymmetric information. In this game, each firm, upon being privately informed about its demand rate (or inventory cost rate), submits a private contribution to an intermediary that specifies how much it is willing to pay for its replenishment per unit of time and the intermediary determines the maximum feasible frequency for the joint orders that would finance the fixed replenishment cost. We show that a Bayesian Nash equilibrium exists and characterize the equilibrium in this game. We also show that the contributions are monotone increasing in each firm’s type. We finally conduct a numerical study to compare the equilibrium to solutions obtained under independent and cooperative ordering, and under full information. The results show that while information asymmetry eliminates free-riding in the contributions game, the resulting aggregate contributions are not as high as under full information, leading to higher aggregate costs. 2013 Elsevier B.V. All rights reserved