Identification of Lossy Y-Type Two-Port Circuit Models under Measurement Uncertainties: Closed-Form Solution and Statistical-Perturbative Characterization

The present paper treats a black-box estimation of the three independent parameters of a reciprocal lossy two-port network whose terminals are supposed to be accessible to an impedance measurement device. The discussed estimation method is based on the availability of a number of data pairs made of external load admittances paired to equivalent external admittances affected by measurement errors. The proposed method is framed as a squared-estimation-error minimization problem that leads to a system of three nonlinear equations in the three unknown parameters. A key observation is, however, that a core subsystem of two equations may be turned exactly to a linear form and hence may be solved in closed form. The purely real-valued case is treated first since it serves to clarify the optimization problem at hand and the structure of its solution. In the purely real-valued case, a statistical analysis is carried out as well, which affords the evaluation of the effects of the measurement errors. The results of the statistical analysis afford quantifying the dependence of the estimation errors from the number of samples and from the variance of the measurement errors. Subsequently, the full complex-valued case is treated. Results of numerical simulations complement and illustrate the theoretical findings. The obtained numerical results confirm the statistical analysis and that the proposed external identification method is effective

Design and Simulation of a Neuroevolutionary Controller for a Quadcopter Drone

The problem addressed in the present paper is the design of a controller based on an evolutionary neural network for autonomous flight in quadrotor systems. The controller's objective is to govern the quadcopter in such a way that it reaches a specific position, bearing on attitude limitations during flight and upon reaching a target. Given the complex nature of quadcopters, an appropriate neural network architecture and a training algorithm were designed to guide a quadcopter toward a target. The designed controller was implemented as a single multi-layer perceptron. On the basis of the quadcopter's current state, the developed neurocontroller produces the correct rotor speed values, optimized in terms of both attitude-limitation compliance and speed. The neural network training was completed using a custom evolutionary algorithm whose design put particular emphasis on the cost function's definition. The developed neurocontroller was tested in simulation to drive a quadcopter to autonomously follow a complex path. The obtained simulated results show that the neurocontroller manages to effortlessly follow several types of paths with adequate precision while maintaining low travel times

Simulation of hydrogenated graphene Field-Effect Transistors through a multiscale approach

In this work, we present a performance analysis of Field Effect Transistors based on recently fabricated 100% hydrogenated graphene (the so-called graphane) and theoretically predicted semi-hydrogenated graphene (i.e. graphone). The approach is based on accurate calculations of the energy bands by means of GW approximation, subsequently fitted with a three-nearest neighbor (3NN) sp3 tight-binding Hamiltonian, and finally used to compute ballistic transport in transistors based on functionalized graphene. Due to the large energy gap, the proposed devices have many of the advantages provided by one-dimensional graphene nanoribbon FETs, such as large Ion and Ion/Ioff ratios, reduced band-to-band tunneling, without the corresponding disadvantages in terms of prohibitive lithography and patterning requirements for circuit integration

Study of sequential semileptonic decays of b hadrons produced at the Tevatron

We present a study of rates and kinematical properties of lepton pairs contained in central jets with transverse energy E_T > 15 GeV that are produced at the Fermilab Tevatron collider. We compare the data to a QCD prediction based on the HERWIG and QQ Monte Carlo generator programs.We find that the data are poorly described by the simulation, in which sequential semileptonic decays of single b quarks (b --> l c X with c --> l s X) are the major source of such lepton pairs.Comment: 25 pages, 8 figures. Some typos were fixed in the text and bibliography. Submitted to Phys. Rev.

Phytotoxicity to and uptake of flumequine used in intensive aquaculture on the aquatic weed, Lythrum salicaria L.

Phytotoxicity of Flumequine on the aquatic weed Lythrum salicaria L. was determined by two laboratory models: a single concentration test, by which the effects of 100 mg l(-1) were evaluated after 10, 20, 30 days and a multiple concentration test, by which the effects of 5000-1000-500-100-50 mu g l(-1) were evaluated after 35-day exposure. 100 mg l(-1) are highly toxic and significantly decrease the growth of plants; this effect increases with time. Concentrations between 5000 and 50 mu g l(-1) induced hormesis in plants, by significantly increasing mean number and dimension of leaves and secondary roots. The effect is the highest at 50 mu g l(-1) and decreases with increase in concentration. Both toxic effect and hormesis can be related to plant drug uptake, quite high, in the order of mu g g(-1). The ecological implication of Flumequine contamination in aquatic environments and the possible use of Lythrum salicaria for bioremediation and/ or monitoring technique are discussed. (C) 2000 Elsevier Science Ltd. All rights reserved

RT-Kubernetes - Containerized Real-Time Cloud Computing

This paper presents RT-Kubernetes, a software architecture with the ability to deploy real-time software components within containers in cloud infrastructures. The deployment of containers with guaranteed CPU scheduling is obtained by using a hierarchical real-time scheduler based on the Linux SCHED_DEADLINE policy. Preliminary experimental results provide evidence that this new framework succeeds in providing timeliness guarantees in the target responsiveness range, while achieving strong temporal isolation among containers co-located on the same physical hosts

MANGANESE MINERALISATIONS AT THE BASE OF MIOCENE SEDIMENTS IN NORTHERN SARDINIA (ITALY)

During the eastward drift of the Palaeozoic-Mesozoic block formed by Sardinia and Corsica in the Oligocene-Miocene, calc-alkaline volcanism developed mostly in the western part of the island. Most Tertiary metallogenic phoenomena are related to hydrothermal activity associated with this volcanism. Following volcanic and related hydrothermal activity, sediments were deposited during the Oligocene-Miocene as a consequence of a marine transgression. The basal part of this series is clastic and includes elements derived from erosion of unaltered volcanics as well as hydrothermally altered rocks and hydrothermal vein quartz. Inside the Tertiary volcanics manganese ore-minerals occur as nodules, veinlets, and stockworks and mainly include Mn and Fe oxides; quartz in different forms is the most common gangue mineral. The mineralisations at the contact between volcanics and Miocene sediments are the most homogeneous, the ore-minerals occur in the cement, but also as fairly continuous thin beds, nodules and veinlets containing pyrolusite, frequent ramsdellite, less frequent manganite, psilomelane, cryptomelane-manjiroite, rare ranciéite, and todorokite. The nature of the ore-bearing beds indicate a near-shore clastic environment along the ancient coastal lines of the Miocene sea. Genetic considerations point to a supergenic transport and redeposition after erosion of primary dispersion and residual concentrations of Mn in the volcanics