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The problem of recovering from nonlinear oscillations in a PID-controlled drug delivery system for the neuromuscular blockade (NMB) in closed-loop anesthesia is considered. The NMB system dynamics portrayed by a Wiener model can exhibit sustained nonlinear oscillations for physiologically feasible values of the model parameters and realistic PID gains. Such oscillations, also repeatedly observed in...
There are several kinds of envisioned vehicular applications: video delivery, accidents detection, dissemination of traffic announcements, and so forth. Such applications demand minimal (and possibly distinct) QoS guarantees that must couple the vehicular network. Given that vehicular networks will soon become reality, we demand strategies for planning and managing such networks. In this work we propose...
The energy resource management is becoming increasingly important and complex, because of the growing use of distributed generators and electric vehicles connected to the distribution network. This paper presents a platform to be used by virtual power players regarding the energy resource management in smart grids and considering day-ahead, hour-ahead, and real-time time-horizons. This method considers...
The management of intermittent energy resources by a microgrid operator (MGO) are a key aspect of future smart grids. A microgrid allows act as a single controllable entity and can operate in both grid-connected or in islanded mode. The present paper proposes a platform to be used by MGO regarding the energy resource management in smart grids and considering day-ahead and hour-ahead time-horizons...
The Ocean is vast and of difficult access. Recent technological advances have brought us to a new era in ocean research (physical / biological / chemical / geological) one in which an Integrated network of Ocean Observing Systems (IOOS), involving strong developments in systems engineering and informatics, provides researchers with a continuous scientific presence in the ocean. These initiatives are...
This paper presents a digital low-IF Gaussian frequency-shift keying (GFSK) demodulator. The demodulator is based on a phase-shift quadrature discriminator. A preamble detector controls the sequencing of the blocks operation to minimize power consumption. An IF input signal of 1 MHz is used, the same of the data rate, hence, allowing a low-power receiver implementation. The implementation is fully...
Companies and researchers involved in developing miniaturized electronic devices face the basic problem of the needed batteries size, finite life of time and environmental pollution caused by their final deposition. The current trends to overcome this situation point towards Energy Harvesting technology. These harvesters (or scavengers) store the energy from sources present in the ambient (as wind,...
Ultrasound non-destructive testing is widely applied to identify defects in structures and equipment as it combines simplicity, fast execution and high efficiency in the detection of flaws. However, in many practical evaluations the accuracy of the obtained results relies on the experience of the operator. Some automatic decision support systems have been proposed in the literature aiming at helping...
The goal of this work is to detect structural damage using vibration-based damage identification approaches even when the damage-sensitive features are camouflaged by the presence of operational and environmental conditions. For feature classification purposes, four machine learning algorithms are applied based on the principal component analysis (PCA), nonlinear PCA, kernel PCA and greedy kernel...
Optimisation during the design of large manufacturing systems is a key issue. An adequate modelling formalism to express the intricate interleaving of competition and cooperation relationships is needed first. Moreover, robust and efficient optimisation techniques are necessary. This paper presents an integrated tool for the automated optimisation of DEDS, with application to manufacturing systems...
The minimum cost initial distributed state problem. Minimum Initial Marking (MIM) problem in Petri nets, is very important for the design of many discrete event dynamic systems (DEDSs). This paper considers MIM for Timed strongly connected Marked Graphs (MG). Unfortunately, even for the untimed MG subclass the problem is NP-hard. A suboptimal two phases approach for timed MGs (TMG) is developed. The...
We address the problem of signal separation using space-time blind equalization techniques. A novel blind algorithm, denoted ACMA (Accelerated Constant Modulus Algorithm), is proposed. It minimizes the constant modulus cost function and is based on a tuner used in adaptive control that sets the second derivative (“acceleration ”) of the coefficient estimates. Both the convergence speed and computational...
This paper proposes an adaptive approach to improve the performance of Target Controlled Infusion (TCI) based strategies. The method determines an adequate drug dose profile that drives the drug effect on the individual patient to a desired target in a prespecified period of time. It combines an optimal variance constrained drug dose design with a hybrid identification of the individual patient dynamics...
A Novel Three-Phase Rectifier topology based on the integration of a Buck type Rectifier and a Current Fed Full-Bridge is proposed. The main contribution of this rectifier topology with galvanic isolation is the integration of two stages, sharing the inductor, and the reduction of the inductor current ripple. The circuit is analyzed in detail. A 2 kW demonstrator prototype has been designed, built...
This paper presents a case study about a PV plant installed on the Mineiräo world cup stadium located in Belo Horizonte, Brazil. An unstable behavior on the line to neutral voltage has been identified on the commissioning of the inverters threatening the loads connected to the transformer and the equipment of the power systems. The root cause of the problem has been identified and a solution to it...
Deep architectures have been used in transfer learning applications, with the aim of improving the performance of networks designed for a given problem by reusing knowledge from another problem. In this work we addressed the transfer of knowledge between deep networks used as classifiers of digit and shape images, considering cases where only the set of class labels, or only the data distribution,...
We present the design and fabrication process for an electrochemical “electronic nose” type sensor. This metal oxide based system focuses on the detection of ammonia as a possible sign of Ammonium nitrate based explosives, the main ingredients used by Armed Groups outside the law in Colombia for their Improvised Explosive Devices. The characterization of the conductivity variations of the zinc oxide...
This work presents our research and implementation of the School Bus Routing Problem applied to the rural area of a brazilian city. We use a complete set of real georeferenced data containing a sample of 944 students, 23 schools, and the full road network of a city of population of 280,000 inhabitants occupying an area of 2,348 km2. Our goal is to optimize the daily transportation of students considering...
Transfer learning is a process that allows reusing a learning machine trained on a problem to solve a new problem. Transfer learning studies on shallow architectures show low performance as they are generally based on hand-crafted features obtained from experts. It is therefore interesting to study transference on deep architectures, known to directly extract the features from the input data. A Stacked...
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