Browsing by Type "Conference Proceeding"

Next generation wireless and mobile networks will utilize millimeter-wave (mmWave) communication to achieve significantly increased data rates. However, since mmWave radio signals experience high path loss, the operation of mmWave networks will require accurate channel models designed for specific deployment sites. In this paper, we focus on the deployment area of the PAWR COSMOS testbed [1, 2] in New York City and report extensive 28 GHz channel measurements. These include over 24 million power measurements collected from over 1,500 links on 13 sidewalks in 3 different sites and in different settings during March–June, 2019. Using these measurements, we study the effects of the setup and environments (e.g., transmitter height and seasonal effects). We then discuss the obtained path gain values and their fitted lines, and the resulting effective azimuth beamforming gain. Based on these results, we also study the link SNR values that can be supported on individual sidewalks and the corresponding theoretically achievable data rates. We believe that the results can inform the COSMOS testbed deployment process and provide a benchmark for other deployment efforts in dense urban areas.

In this paper, we develop a filtering algorithm for Wiener systems written in state-space form which considers correlated noise sources. The output non-linearity is approximated by using a piece-wise linear function. The probability function of the output signal conditioned to the system state is written as a Gaussian mixture distribution. A Gaussian sum filter algorithm to obtain the a posteriori probability density function of the state given the current and past output is developed. The associated statistics of the system state are obtained. The benefits of our proposal are illustrated via numerical simulations.

Fluid-structure interaction models are of special interest for studying the energy transfer between the moving fluid and the mechanical structure in contact. The vocal folds are an example of a fluid-structure system, where the mechanical structure is usually modeled as a mass-spring-damper system. In particular, the estimation of the collision forces of the vocal folds is of high interest in the diagnosis of phonotraumatic voice pathologies. In this context, the port-Hamiltonian modeling framework focuses on the energy flux in the model and the interacting forces. In this paper, we develop a port-Hamiltonian fluid-structure interaction model based on the interconnection methodology proposed by Lopes and Hélie (2016).

In this paper, we propose a novel joint approach to solve the regeneration placement, routing, modulation level, and spectrum assignment (RP-RMLSA) problem using a binary integer program (BIP) model. Using a mock and real-world network topology, we conduct extensive numerical experiments testing the proposed optimization model’s performance and analyzing the characteristics of the solutions found. Our results show that considering only an optimal solution occurs when signals in need of regeneration are concentrated in one regeneration node when considering the regeneration devices’ capital and operational expenditure.

The behavior of a fluid in pipes with irregular geometries is studied. Departing from the partial differential equations that describe mass and momentum balances a scalable lumped-parameter model is proposed. To this end the framework of port-Hamiltonian systems is instrumental to derive a modular system which upon interconnection describes segments with different cross sections and dissipation effects. In order to perform the interconnection between different segments the incompressibility hypothesis is relaxed in some infinitesimal section to admit density variations and energy transference between segments. Numerical simulations are performed in order to illustrate the model.

In this paper we consider the physical-based modeling of 3D and 2D Newtonian fluids including thermal effects in order to cope with the first and second principles of thermodynamics. To describe the energy fluxes of non-isentropic fluids we propose a pseudo port-Hamiltonian formulation, which includes the rate of irreversible entropy creation by heat flux. For isentropic fluids, the conversion of kinetic energy into heat by viscous friction is considered as an energy dissipation associated with the rotation and compression of the fluid. Then, a dissipative port-Hamiltonian formulation is derived for this class of fluids. In the 2D case we modify the vorticity operators in order to preserve the structure of the proposed models. Moreover, we show that a description for inviscid or irrotational fluids can be derived from the proposed models under the corresponding assumptions leading to a pseudo or dissipative port-Hamiltonian structures.

Inverse filtering of oral airflow using closed-phase linear prediction is expected to preserve the effects of source-filter interactions in the glottal airflow pulse. Under incomplete glottal closure, the glottal airflow estimation is more challenging due to a lowered glottal impedance, increased subglottal coupling, and violated all-pole assumption. To account for these effects, a model-based inverse filtering scheme allowing for coupling between glottis and upper and lower airways was developed. Acoustic transmission in the tracts used a frequency-domain transmission line. A linearized, time-varying expression was used for the glottal impedance, along with a dipole representation. Synthetic vowels sounds and actual recordings were used to evaluate the proposed scheme. Subject-specific model parameters were obtained from simultaneous aerodynamic, acoustic, and high-speed videoendoscopic recordings of normal subjects uttering vowels with various degrees of glottal closure. Results illustrated that, even under incomplete glottal closure, the airflow entering the vocal tract preserved source-filter interactions and was comparable to that obtained using closed-phase linear prediction. The scheme also yielded an uncoupled glottal airflow that exhibited a clear pulse de-skewing, making it proportional to the glottal area. Cases with larger glottal gaps exhibited lower mean impedances and less pulse skewing, with airflow estimates proportional to the transglottal pressure drop.

The Cherenkov Telescope Array (CTA) observatory is the next generation of ground-based imaging atmospheric Cherenkov telescopes (IACTs). Building on the strengths of current IACTs, CTA is designed to achieve an order of magnitude improvement in sensitivity, with unprecedented angular and energy resolution. CTA will also increase the energy reach of IACTs, observing photons in the energy range from 20 GeV to beyond 100 TeV. These advances in performance will see CTA heralding in a new era for high-energy astrophysics, with the emphasis shifting from source discovery, to population studies and precision measurements. In this talk we discuss CTA’s ability to conduct source population studies of W-ray bright active galactic nuclei and how this ability will enhance our understanding on the redshift evolution of this dominant W-ray source class.

This paper concerns the identification of continuous-time systems in state-space form that are subject to Lebesgue sampling. Contrary to equidistant (Riemann) sampling, Lebesgue sampling consists of taking measurements of a continuous-time signal whenever it crosses fixed and regularly partitioned thresholds. The knowledge of the intersample behavior of the output data is exploited in this work to derive an expectation-maximization (EM) algorithm for parameter estimation of the state-space and noise covariance matrices. For this purpose, we use the incremental discrete-time equivalent of the system, which leads to EM iterations of the continuous-time state-space matrices that can be computed by standard filtering and smoothing procedures. The effectiveness of the identification method is tested via Monte Carlo simulations.

This paper presents a novel identification method for stochastic continuous-time systems applied to Adaptive Optics. We consider a discrete-time sampled-data model of a linear combination of continuous-time second-order systems for modelling disturbances. The Maximum Likelihood framework is used in time and frequency domain to develop an estimation algorithm with sampled-data. We propose an estimation algorithm where we write the likelihood function in the frequency domain in terms of the discrete-time output spectrum (Whittle's log-likelihood function). An approximation for the discrete-time spectrum is used in order to reduce the computational load. A comparative analysis of the proposed method and some available methods is illustrated via numerical simulations.

An irreversible port-Hamiltonian system formulation of a class of piezoelectric actuator with non-negligible entropy increase is proposed. The proposed model encompasses the hysteresis and the irreversible thermodynamic changes due to mechanical friction, electrical resistance and heat exchange between the actuator and the environment. The electromechanical dynamic of the actuator is modeled using a non-linear resistive-capacitive-inductor circuit coupled with a mass-spring-damper system, while the non-linear hysteresis is characterized using hysterons. The thermodynamic behavior of the model is constructed by making the electromechanical coupling temperature dependent, and by characterizing the entropy produced by the irreversible phenomena. By means of numerical simulations it is shown that the proposed model is capable of reproducing the expected behaviors and is in line with reported experimental results.

The aim of this research is to simulate the performance of a solar chimney located in different macro-zones in Ecuador. The proposed solar chimney model was simulated using a python script in order to predict the temperature distribution and the mass flow over time. The results obtained were firstly compared with experimental data for dry-warm climate. Then, the model was evaluated and tested in real weather conditions: dry-warm, moist-warm and rainycold. In addition, the assumed chimney dimensions were chosen according to the literature for the studied conditions. In spite of evaluating the best nightly ventilation, different chimney wall materials were tested: solid brick, common brick and reinforced concrete. The results showed that concrete in a dry-warm climate, a metallic layer on the gap with solid brick in a moist–warm climate and reinforced concrete in a rainy cold climate used for the absorbent wall improve the thermal inertia of the social housing.

ANDES (Agua Negra Deep Experiment Site) is an underground laboratory, proposed to be built inside the Agua Negra road tunnel that will connect Chile (IV Region) with Argentina (San Juan Province) under the Andes Mountains. The Laboratory will be 1750 meters under the rock, becoming the 3rd deepest underground laboratory of this kind in the world, and the first in the Southern Hemisphere. ANDES will be an international Laboratory, managed by a Latin American consortium. The laboratory will host experiments in Particle and Astroparticle Physics, such as Neutrino and Dark Matter searches, Seismology, Geology, Geophysics and Biology. It will also be used for the development of low background instrumentation and related services. Here we present the general features of the proposed laboratory, the current status of the proposal and some of its opportunities for science.

A comparative study of passivity based boundary control design for a class of infinite dimensional port-Hamiltonian system using two different model reduction approaches is presented. The first approach is based on a direct low order structure preserving discretization while the second approach arise from the structure preserving model reduction of a high order discretzed model. Two passivity-based control techniques, namely control by interconnection and damping injection, are used to change the equilibrium point and the convergence rate of the closed-loop system. An Euler-Bernoulli beam example is used to illustrate the findings by means of discussion and numerical simulations.

We study the static quantum potential for a theory of anti-symmetric tensor fields that results from the condensation of topological defects, within the framework of the gauge-invariant but path-dependent variables formalism. Our calculations show that the interaction energy is the sum of a Yukawa and a linear potentials, leading to the confinement of static probe charges.

This paper introduces a study on the charging infrastructures, integrated with distributed energy sources, showing their ability to support the electric and hybrid mobility in a smart grid scenario. This analysis starts from a description of the main AC and DC architecture and then goes through the advantages derived by the integration of renewable energy sources within the existing electric power network. A section of this paper is then dedicated to the main technologies of energy storage systems, which allow and support the integration of unpredictable energy sources into the grid. Finally, the power on-board and off-board vehicle charging devices are analyzed with specific focus on PWM control schemes, for the regulation of AC/DC and DC/DC power converters, and on grid operations (V2G) related to different aggregation schemes.

Studying proton-proton scattering at 7 TeV, the ALICE collaboration found the unexpected result that the D meson multiplicity increases more than linear as a function of the charged particle multiplicity. We try to understand this behavior using the EPOS3 approach. Two issues play an important role in this context: multiple scattering, in particular its impact on multiplicity fluctuations, and the collective hydrodynamic expansion. These data contain therefore valuable information about very basic features of the reaction mechanism in protonproton collisions.

Given the success of Graph Neural Networks (GNNs) for structure-aware machine learning, many studies have explored their use for text classification, but mostly in specific domains with limited data characteristics. Moreover, some strategies prior to GNNs relied on graph mining and classical machine learning, making it difficult to assess their effectiveness in modern settings. This work extensively investigates graph representation methods for text classification, identifying practical implications and open challenges. We compare different graph construction schemes using a variety of GNN architectures and setups across five datasets, encompassing short and long documents as well as unbalanced scenarios in diverse domains. Two Transformer-based large language models are also included to complement the study. The results show that i) although the effectiveness of graphs depends on the textual input features and domain, simple graph constructions perform better the longer the documents are, ii) graph representations are especially beneficial for longer documents, outperforming Transformer-based models, iii) graph methods are particularly efficient at solving the task.

The aim of this paper is to study the value function of a time-continuous linear quadratic optimal control problem with input and state constraints. No coercive assumptions are made, which leads to optimal control problems whose trajectories are of bounded variation rather than merely absolutely continuous. Our approach is based on classical convex analysis, and we establish a Legendre-Fenchel type equality between the value function of the linear quadratic problem and its dual problem.

In this paper, a coordination control algorithm based on hierarchical scheme is presented to coordinate several non-linear model predictive controllers (NMPC) working in parallel, with an upper layer, where a price-driven coordination technique is used to drive the controllers in such a way that some global constraints are satisfied. To coordinate the lower layers, it is used a price-adjustment algorithm based on Newton's method, in which a reformulation of Fiacco's work is used in order to obtain the sensitivity analysis for a nonlinear system no matter the set of active constraints. The efficiency of the scheme is evaluated using a simulation of a four-tank benchmark.