Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Species composition of arbuscular mycorrhizal fungi differ in semi-natural and intensively managed pastures in an isolated oceanic island (Terceira, Azores)

Copyright © Springer Science+Business Media Dordrecht 2014.

Unveiling the Biometric Potential of Finger-Based ECG Signals

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

A influência do acompanhamento em suporte digital na motivação dos alunos de saxofone: relatório de estágio

I (Prática pedagógica)- Esta secção do Relatório de Estágio pretende apresentar elementos referentes ao Estágio do Ensino Especializado da Música no ensino do saxofone, efectuado na Escola de Música Luís António Maldonado Rodrigues, no ano lectivo 2012/2013. Neste estágio foram envolvidos e analisados três alunos, em níveis distintos de desenvolvimento, mas com orientações semelhantes no que respeita à organização do trabalho. Para cada aluno foram realizados trinta planos de aula, uma planificação anual e três gravações vídeo/áudio em contexto de sala de aula, permitindo uma análise e reflexão mais profunda do trabalho docente. A secção é composta pela caracterização da escola onde se realizou o estágio, através da sua contextualização/funcionamento, dos seus espaços e equipamentos, recursos humanos existentes e organização pedagógica. Posteriormente é efectuada a caracterização dos três alunos envolvidos no estágio, baseada na experiência docente e nos conhecimentos fornecidos pelas Unidades Curriculares do Mestrado em Ensino da Música. Seguidamente descrevem-se as práticas lectivas desenvolvidas ao longo do ano lectivo por parte do docente, incorporando linhas orientadoras da docência aplicadas na prática pedagógica. É feita uma análise crítica da actividade docente no âmbito do estágio do Ensino Especializado da Música, e, por último, uma conclusão desta primeira secção. .

Implementing slot-based task-splitting multiprocessor scheduling

Consider the problem of scheduling a set of sporadic tasks on a multiprocessor system to meet deadlines using a task-splitting scheduling algorithm. Task-splitting (also called semi-partitioning) scheduling algorithms assign most tasks to just one processor but a few tasks are assigned to two or more processors, and they are dispatched in a way that ensures that a task never executes on two or more processors simultaneously. A particular type of task-splitting algorithms, called slot-based task-splitting dispatching, is of particular interest because of its ability to schedule tasks with high processor utilizations. Unfortunately, no slot-based task-splitting algorithm has been implemented in a real operating system so far. In this paper we discuss and propose some modifications to the slot-based task-splitting algorithm driven by implementation concerns, and we report the first implementation of this family of algorithms in a real operating system running Linux kernel version 2.6.34. We have also conducted an extensive range of experiments on a 4-core multicore desktop PC running task-sets with utilizations of up to 88%. The results show that the behavior of our implementation is in line with the theoretical framework behind it.

Incremental filter and wrapper approaches for feature discretization

Discrete data representations are necessary, or at least convenient, in many machine learning problems. While feature selection (FS) techniques aim at finding relevant subsets of features, the goal of feature discretization (FD) is to find concise (quantized) data representations, adequate for the learning task at hand. In this paper, we propose two incremental methods for FD. The first method belongs to the filter family, in which the quality of the discretization is assessed by a (supervised or unsupervised) relevance criterion. The second method is a wrapper, where discretized features are assessed using a classifier. Both methods can be coupled with any static (unsupervised or supervised) discretization procedure and can be used to perform FS as pre-processing or post-processing stages. The proposed methods attain efficient representations suitable for binary and multi-class problems with different types of data, being competitive with existing methods. Moreover, using well-known FS methods with the features discretized by our techniques leads to better accuracy than with the features discretized by other methods or with the original features. (C) 2013 Elsevier B.V. All rights reserved.

Logic functions based on optical bias controlled SIC Tandem devices

The purpose of this paper is the design of an optoelectronic circuit based on a-SiC technology, able to act simultaneously as a 4-bit binary encoder or a binary decoder in a 4-to-16 line configurations and show multiplexer-based logical functions. The device consists of a p-i'(a-SiC:H)-n/p-i(a-Si:H)-n multilayered structure produced by PECVD. To analyze it under information-modulated wave (color channels) and uniform irradiation (background) four monochromatic pulsed lights (input channels): red, green, blue and violet shine on the device. Steady state optical bias was superimposed separately from the front and the back sides, and the generated photocurrent was measured. Results show that the devices, under appropriate optical bias, act as reconfigurable active filters that allow optical switching and optoelectronic logic functions development providing the possibility for selective removal of useless wavelengths. The logic functions needed to construct any other complex logic functions are the NOT, and both or either an AND or an OR. Any other complex logic function that might be found can also be used as building blocks to achieve the functions needed for the retrieval of channels within the WDM communication link. (C) 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

ROM-less RNS-to-binary converter moduli {22N − 1, 22N + 1, 2N − 3, 2N + 3}

In this paper, a novel ROM-less RNS-to-binary converter is proposed, using a new balanced moduli set {22n-1, 22n + 1, 2n-3, 2n + 3} for n even. The proposed converter is implemented with a two stage ROM-less approach, which computes the value of X based only in arithmetic operations, without using lookup tables. Experimental results for 24 to 120 bits of Dynamic Range, show that the proposed converter structure allows a balanced system with 20% faster arithmetic channels regarding the related state of the art, while requiring similar area resources. This improvement in the channel's performance is enough to offset the higher conversion costs of the proposed converter. Furthermore, up to 20% better Power-Delay-Product efficiency metric can be achieved for the full RNS architecture using the proposed moduli set. © 2014 IEEE.

Compact SMB chromatography for binary separation

A thesis submitted for the degree of Doctor of Philosophy

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Development of an interface for ontology‐based transformation between features of different types

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Navegação de robôs móveis por marcas artificiais em ambientes semi-estruturados

Mestrado em engenharia electrotécnica e de computadores - Área de Especialização de Sistemas Autónomos

(E)xperimental study of the porosity and microstructure of self-compacting concrete (SCC) with binary and ternary mixes of fly ash and limestone filler

Self-compacting concrete (SCC) can soon be expected to replace conventional concrete due to its many advantages. Its main characteristics in the fresh state are achieved essentially by a higher volume of mortar (more ultrafine material) and a decrease of the coarse-aggregates. The use of over-large volumes of additions such as fly ash (FA) and/or limestone filler (LF) can substantially affect the concrete's pore structure and consequently its durability. In this context, an experimental programme was conducted to evaluate the effect on the concrete's porosity and microstructure of incorporating FA and LF in binary and ternary mixes of SCC. For this, a total of 11 SIX mixes were produced; 1 with cement only (C); 3 with C + FA in 30%, 60% and 70% substitution (fad); 3 with C + LF in 30%, 60% and 70% fad; 4 with C + FA + LF in combinations of 10-20%, 20-10%, 20-40% and 40-20% f(ad), respectively. The results enabled conclusions to be established regarding the SCC's durability, based on its permeability and the microstructure of its pore structure. The properties studied are strongly affected by the type and quantity of additions. The use of ternary mixes also proves to be extremely favourable, confirming the beneficial effect of the synergy between these additions. (C) 2015 Elsevier Ltd. All rights reserved.

Improving Assumption based Distributed Belief Revision

Belief revision is a critical issue in real world DAI applications. A Multi-Agent System not only has to cope with the intrinsic incompleteness and the constant change of the available knowledge (as in the case of its stand alone counterparts), but also has to deal with possible conflicts between the agents’ perspectives. Each semi-autonomous agent, designed as a combination of a problem solver – assumption based truth maintenance system (ATMS), was enriched with improved capabilities: a distributed context management facility allowing the user to dynamically focus on the more pertinent contexts, and a distributed belief revision algorithm with two levels of consistency. This work contributions include: (i) a concise representation of the shared external facts; (ii) a simple and innovative methodology to achieve distributed context management; and (iii) a reduced inter-agent data exchange format. The different levels of consistency adopted were based on the relevance of the data under consideration: higher relevance data (detected inconsistencies) was granted global consistency while less relevant data (system facts) was assigned local consistency. These abilities are fully supported by the ATMS standard functionalities.