Automatic synthesis of VHDL Hardware Components from IOPT Petri Net models

Conferência: 39th Annual Conference of the IEEE Industrial-Electronics-Society (IECON), Vienna, Austria, Nov 10-14, 2013

Remote operation of embedded controllers designed using IOPT Petri-nets

This paper presents a new communication architecture to enable the remote control, monitoring and debug of embedded-system controllers designed using IOPT Petri nets. IOPT Petri nets and the related tools (http://gres.uninova.pt) have been used as a rapid prototyping and development framework, including model-checking, simulation and automatic code generation tools. The new architecture adds remote operation capabilities to the controllers produced by the automatic code generators, enabling quasi-real-time remote debugging and monitoring using the IOPT simulator tool. Furthermore, it enables the creation of graphical user interfaces for remote operation and the development of distributed systems where a Petri net model running on a central system supervises the actions of multiple remote subsystems. © 2015 IEEE.

A flexible side information generation framework for distributed video coding

One of the most efficient approaches to generate the side information (SI) in distributed video codecs is through motion compensated frame interpolation where the current frame is estimated based on past and future reference frames. However, this approach leads to significant spatial and temporal variations in the correlation noise between the source at the encoder and the SI at the decoder. In such scenario, it would be useful to design an architecture where the SI can be more robustly generated at the block level, avoiding the creation of SI frame regions with lower correlation, largely responsible for some coding efficiency losses. In this paper, a flexible framework to generate SI at the block level in two modes is presented: while the first mode corresponds to a motion compensated interpolation (MCI) technique, the second mode corresponds to a motion compensated quality enhancement (MCQE) technique where a low quality Intra block sent by the encoder is used to generate the SI by doing motion estimation with the help of the reference frames. The novel MCQE mode can be overall advantageous from the rate-distortion point of view, even if some rate has to be invested in the low quality Intra coding blocks, for blocks where the MCI produces SI with lower correlation. The overall solution is evaluated in terms of RD performance with improvements up to 2 dB, especially for high motion video sequences and long Group of Pictures (GOP) sizes.

Automatic assignment of absolute configuration from 1D NMR data

Opposite enantiomers exhibit different NMR properties in the presence of an external common chiral element, and a chiral molecule exhibits different NMR properties in the presence of external enantiomeric chiral elements. Automatic prediction of such differences, and comparison with experimental values, leads to the assignment of the absolute configuration. Here two cases are reported, one using a dataset of 80 chiral secondary alcohols esterified with (R)-MTPA and the corresponding 1H NMR chemical shifts and the other with 94 13C NMR chemical shifts of chiral secondary alcohols in two enantiomeric chiral solvents. For the first application, counterpropagation neural networks were trained to predict the sign of the difference between chemical shifts of opposite stereoisomers. The neural networks were trained to process the chirality code of the alcohol as the input, and to give the NMR property as the output. In the second application, similar neural networks were employed, but the property to predict was the difference of chemical shifts in the two enantiomeric solvents. For independent test sets of 20 objects, 100% correct predictions were obtained in both applications concerning the sign of the chemical shifts differences. Additionally, with the second dataset, the difference of chemical shifts in the two enantiomeric solvents was quantitatively predicted, yielding r2 0.936 for the test set between the predicted and experimental values.

Learning techniques for automatic email message tagging

A organização automática de mensagens de correio electrónico é um desafio actual na área da aprendizagem automática. O número excessivo de mensagens afecta cada vez mais utilizadores, especialmente os que usam o correio electrónico como ferramenta de comunicação e trabalho. Esta tese aborda o problema da organização automática de mensagens de correio electrónico propondo uma solução que tem como objectivo a etiquetagem automática de mensagens. A etiquetagem automática é feita com recurso às pastas de correio electrónico anteriormente criadas pelos utilizadores, tratando-as como etiquetas, e à sugestão de múltiplas etiquetas para cada mensagem (top-N). São estudadas várias técnicas de aprendizagem e os vários campos que compõe uma mensagem de correio electrónico são analisados de forma a determinar a sua adequação como elementos de classificação. O foco deste trabalho recai sobre os campos textuais (o assunto e o corpo das mensagens), estudando-se diferentes formas de representação, selecção de características e algoritmos de classificação. É ainda efectuada a avaliação dos campos de participantes através de algoritmos de classificação que os representam usando o modelo vectorial ou como um grafo. Os vários campos são combinados para classificação utilizando a técnica de combinação de classificadores Votação por Maioria. Os testes são efectuados com um subconjunto de mensagens de correio electrónico da Enron e um conjunto de dados privados disponibilizados pelo Institute for Systems and Technologies of Information, Control and Communication (INSTICC). Estes conjuntos são analisados de forma a perceber as características dos dados. A avaliação do sistema é realizada através da percentagem de acerto dos classificadores. Os resultados obtidos apresentam melhorias significativas em comparação com os trabalhos relacionados.

Modelling of n-stage Blumlein stacked lines for bipolar pulse generation

A Blumlein line is a particular Pulse Forming Line, PFL, configuration that allows the generation of high-voltage sub-microsecond square pulses, with the same voltage amplitude as the dc charging voltage, into a matching load. By stacking n Blumlein lines one can multiply in theory by n the input dc voltage charging amplitude. In order to understand the operating behavior of this electromagnetic system and to further optimize its operation it is fundamental to theoretically model it, that is to calculate the voltage amplitudes at each circuit point and the time instant that happens. In order to do this, one needs to define the reflection and transmission coefficients where impedance discontinuity occurs. The experimental results of a fast solid-state switch, which discharges a three stage Blumlein stack, will be compared with theoretical ones.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Mantle source heterogeneity, magma generation and magmatic evolution at Terceira Island (Azoresarchipelago): Constraints from elemental and isotopic (Sr, Nd, Hf, and Pb) data

This work addresses the present-day (<100 ka) mantle heterogeneity in the Azores region through the study of two active volcanic systems from Terceira Island. Our study shows that mantle heterogeneities are detectable even when "coeval" volcanic systems (Santa Barbara and Fissural) erupted less than 10 km away. These volcanic systems, respectively, reflect the influence of the Terceira and D. Joao de Castro Bank end-members defined by Beier et at (2008) for the Terceira Rift Santa Barbara magmas are interpreted to be the result of mixing between a HIMU-type component, carried to the upper mantle by the Azores plume, and the regional depleted MORB magmas/source. Fissural lavas are characterized by higher Ba/Nb and Nb/U ratios and less radiogenic Pb-206/Pb-204, Nd-143/Nd-144 and Hf-176/Hf-177, requiring the small contribution of delaminated sub-continental lithospheric mantle residing in the upper mantle. Published noble gas data on lavas from both volcanic systems also indicate the presence of a relatively undegassed component, which is interpreted as inherited from a lower mantle reservoir sampled by the ascending Azores plume. As inferred from trace and major elements, melting began in the garnet stability field, while magma extraction occurred within the spinel zone. The intra-volcanic system's chemical heterogeneity is mainly explained by variable proportions of the above-mentioned local end-members and by crystal fractionation processes. (C) 2011 Elsevier By. All rights reserved.

Methods for automatic and assisted image annotation

Personal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.

Solid State Marx Modulator with Blumlein Stack for Bipolar Pulse Generation

Sub-nanosecond bipolar high voltage pulses are a very important tool for food processing, medical treatment, waste water and exhaust gas processing. A Hybrid Modulator for sub-microsecond bipolar pulse generation, comprising an unipolar solid-state Marx generator connected to a load through a stack Blumlein system that produces bipolar pulses and further multiplies the pulse voltage amplitude, is presented. Experimental results from an assembled prototype show the generation of 1000 V amplitude bipolar pulses with 100 ns of pulse width and 1 kHz repetition rate.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Controlo clássico vs. preditivo na regulação de frequência em sistemas de potência

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Automação e Electrónica Industrial

Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterization

Liver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.

Optimizing the renewable generation mix in the Portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Micro-generation Evaluation of the Zero Emissions Technologies in the Portuguese Market

Micro-generation is the small scale production of heat and/or electricity from a low carbon source and can be a powerful driver for carbon reduction, behavior change, security of supply and economic value. The energy conversion technologies can include photovoltaic panels, micro combined heat and power, micro wind, heat pumps, solar thermal systems, fuel cells and micro hydro schemes. In this paper, a small research of the availability of the conversion apparatus and the prices for the micro wind turbines and photovoltaic systems is made and a comparison between these two technologies is performed in terms of the availability of the resource and costs. An analysis of the new legal framework published in Portugal is done to realize if the incentives to individualspsila investment in sustainable and local energy production is worth for their point of view. An economic evaluation for these alternatives, accounting with the governmentpsilas incentives should lead, in most cases, into attractive return rates for the investment. Apart from the attractiveness of the investment there are though other aspects that should be taken into account and those are the benefits that these choices have to us all. The idea is that micro-generation will not only make a significant direct contribution to carbon reduction targets, it will also trigger a multiplier effect in behavior change by engaging hearts and minds, and providing more efficient use of energy by householders. The diversified profile of power generation by micro-generators, both in terms of location and timing, should reduce the impact of intermittency or plant failures with significant gains for security of supply.