Mobile Crowdsensing (MCS) is a paradigm where a crowdsourcer recruits a set of workers through a campaign to collect data using sensors in their mobile device. This process greatly reduces the costs of data collection...
Mobile Crowdsensing (MCS) is a paradigm where a crowdsourcer recruits a set of workers through a campaign to collect data using sensors in their mobile device. This process greatly reduces the costs of data collection processes; however, most of the historically proposed systems are centralized. Since this makes the MCS platform a single point of failure, there is an increasing interest in decentralized blockchain-based solutions; regardless, most of the current proposals have a vertical focus and do not account for the heterogeneity of MCS. We propose a decentralized high-level architecture for MCS, based on Distributed Ledger technology (DLT), that is adaptable to most MCS deployments. We then implement our architecture using the IOTA protocols and evaluate its performance over a real deployment in terms of scalability, showing its advantages over classic blockchains for MCS data.
Nanoparticle-based plasmonic optical fiber sensors can exhibit high sensing performance,in terms of refractive index sensitivities(RISs).However,a comprehensive understanding of the factors governing the RIS in this t...
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Nanoparticle-based plasmonic optical fiber sensors can exhibit high sensing performance,in terms of refractive index sensitivities(RISs).However,a comprehensive understanding of the factors governing the RIS in this type of sensor remains limited,with existing reports often overlooking the presence of surface plasmon resonance(SPR)phenomena in nanoparticle(NP)assemblies and attributing high RIS to plasmonic coupling or waveguiding ***,using plasmonic optical fiber sensors based on spherical Au nanoparticles,we investigate the basis of their enhanced RIS,both experimentally and *** bulk behavior of assembled Au NPs on the optical fiber was investigated using an effective medium approximation(EMA),specifically the gradient effective medium approximation(GEMA).Our findings demonstrate that the Au-coated optical fibers can support the localized surface plasmon resonance(LSPR)as well as SPR in particular ***,we found that the nanoparticle sizes and surface coverage dictate which effect takes precedence in determining the RIS of the *** data,in line with numerical simulations,revealed that increasing the Au NP diameter from 20 to 90 nm(15%surface coverage)led to an RIS increase from 135 to 6998 nm/RIU due to a transition from LSPR to SPR ***,increasing the surface coverage of the fiber from 9%to 15%with 90 nm Au nanoparticles resulted in anincrease in RIS from 1297(LSPR)to 6998 nm/RIU(SPR).Hence,we ascribe the exceptional performance of these plasmonic optical fibers primary to SPR effects,as evidenced by the nonlinear RIS *** outstanding RIS of these plasmonic optical fibers was further demonstrated in the detection of thrombin protein,achieving very low limits of *** findings support broader applications of high-performance NP-based plasmonic optical fiber sensors in areas such as biomedical diagnostics,environmental monitoring,and chemical analysis.
We propose a digital twin using multiplane light conversion and neural networks for a digitally programmable multiplexer for space division multiplexing. The new approach is promising for few-mode fiber communication....
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Noncollinear magnetic structures and multiple magnetic phase transitions in a sawtooth lattice antiferromagnet consisting of Cr3+ are experimentally identified in this work, thereby proposing the scenario of magnetism...
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Noncollinear magnetic structures and multiple magnetic phase transitions in a sawtooth lattice antiferromagnet consisting of Cr3+ are experimentally identified in this work, thereby proposing the scenario of magnetism-driven ferroelectricity in a sawtooth lattice. The title compound, BeCr2O4, displays three magnetic phase transitions at low temperatures—at TN1≈7.5 K, at TN2≈25 K, and at TN3≈26 K—revealed through magnetic susceptibility, specific heat, and neutron diffraction in this work. These magnetic phase transitions are found to be influenced by externally applied magnetic fields. Isothermal magnetization curves at low temperatures below the magnetic transitions indicate the antiferromagnetic nature of BeCr2O4 with two spin-flop-like transitions occurring at Hc1≈29 kOe and Hc2≈47 kOe. Our high-resolution x-ray and neutron diffraction studies, performed on single crystal and powder samples, unambiguously determined the crystal structure as orthorhombic Pbnm. By performing the magnetic superspace group analysis of the neutron diffraction data at low temperatures, the magnetic structure in the temperature range TN3,N2
We discover and discuss the giant oscillations of stable soliton-molecules as induced by the violation of the action-reaction principle in optical systems ruled by competing nonlinear nonlocal interactions. CLEO 2024 ...
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Tunneling spectroscopy is an important tool for the study of both real- and momentum-space electronic structure of correlated electron systems. However, such measurements often yield noisy data. Machine learning provi...
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Tunneling spectroscopy is an important tool for the study of both real- and momentum-space electronic structure of correlated electron systems. However, such measurements often yield noisy data. Machine learning provides techniques to reduce the noise in postprocessing, but traditionally requires noiseless examples which are unavailable for scientific experiments. In this work we adapt the unsupervised Noise2Noise and self-supervised Noise2Self algorithms, which allow for denoising without clean examples, to denoise quasiparticle interference data. We first apply the techniques on simulated data, and demonstrate that we are able to reduce the noise while preserving finer details, all while outperforming more traditional denoising techniques. We then apply the Noise2Self technique to experimental data from an overdoped cuprate [(Pb,Bi)2Sr2CuO6+δ] sample. Denoising enhances the clarity of quasiparticle interference patterns, and helps to obtain a precise extraction of electronic structure parameters. Self-supervised denoising is a promising tool for denoising quasiparticle interference data, facilitating deeper insights into the physics of complex materials.
This research conducts a comprehensive numerical assessment of wind energy potential across Brazil, utilizing six decades of wind speed data collected from 27 cities to analyze Probability Density Function (PDF) param...
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Recent advances in nuclear theory and new astrophysical observations have led to the need for specific theoretical models applicable to dense-matter physics *** chromodynamics(QCD)predicts the existence of non-nucleon...
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Recent advances in nuclear theory and new astrophysical observations have led to the need for specific theoretical models applicable to dense-matter physics *** chromodynamics(QCD)predicts the existence of non-nucleonic degrees of freedom at high densities in neutron-star matter,such as quark *** a confining quark matter model,which consists of homogeneous,neutral 3-flavor interacting quark matter with O(m_(s)^(4))corrections,we examine the structure of compact stars composed of a charged perfect fluid in the context of f(R,T)*** system of differential equations describing the structure of charged compact stars has been derived and numerically solved for a gravity model with f(R,T)=R+2β*** simplicity,we assumed that the charge density is proportional to the energy density,namely,ρ_(ch)=αρ.It is demonstrated that the matter-geometry coupling constant β and charge parameter α affect the total gravitational mass and the radius of the star.
A technology is proposed for estimating the probability that the share price will leave the established corridor by a given point in time. The exact expression is obtained for the required probability under the assump...
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ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981
A technology is proposed for estimating the probability that the share price will leave the established corridor by a given point in time. The exact expression is obtained for the required probability under the assumption that the behavior of the share price is described by the well-known model of Samuelson, according to which the relative change in price is the sum of the non-random trend and the Wiener process.
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