Learning dependent sources using mixtures of Dirichlet: applications on hyperspectral unmixing

This paper is an elaboration of the DECA algorithm [1] to blindly unmix hyperspectral data. The underlying mixing model is linear, meaning that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. The proposed method, as DECA, is tailored to highly mixed mixtures in which the geometric based approaches fail to identify the simplex of minimum volume enclosing the observed spectral vectors. We resort then to a statitistical framework, where the abundance fractions are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. With respect to DECA, we introduce two improvements: 1) the number of Dirichlet modes are inferred based on the minimum description length (MDL) principle; 2) The generalized expectation maximization (GEM) algorithm we adopt to infer the model parameters is improved by using alternating minimization and augmented Lagrangian methods to compute the mixing matrix. The effectiveness of the proposed algorithm is illustrated with simulated and read data.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

A teaching-learning sequence of colour informed by history and philosophy of science

In this work, we present a teaching-learning sequence on colour intended to a pre-service elementary teacher programme informed by History and Philosophy of Science. Working in a socio-constructivist framework, we made an excursion on the history of colour. Our excursion through history of colour, as well as the reported misconception on colour helps us to inform the constructions of the teaching-learning sequence. We apply a questionnaire both before and after each of the two cycles of action-research in order to assess students’ knowledge evolution on colour and to evaluate our teaching-learning sequence. Finally, we present a discussion on the persistence of deep-rooted alternative conceptions.

Learning and Knowledge in the Context of Absorptive Capacity

Develop a new model of Absorptive Capacity taking into account two variables namely Learning and knowledge to explain how companies transform information into knowledge

Qualified intervention/qualifying formation

An education promoting scientific literacy (SL) that prepares the citizens to a responsible citizenship has persisted as an argument across discussions on curricula design. The ubiquity of science and technology on contemporary societies and the ideological requirement of informed democratic participation led to the identification of relevant categories that drive curriculum reforms towards a humanistic approach of school science. The category ‘Science as culture’ acquires in the current work a major importance: it enlightens the meaning of scientific literacy. Looking closely to the French term, culture scientifique et tecnologique, turns science simultaneously into a cultural object and product that can be both received and worked at different levels and within several approaches by the individuals and the communities. On the other hand, nonformal and informal education spaces gain greater importance. Together with the formal school environment these spaces allow for an enrichment and diversification of learning experiences. Examples of nonformal spaces where animators can develop their work may be science museums or botanical gardens; television and internet can be regarded as informal education spaces. Due to the above mentioned impossibility of setting apart the individual or community-based experiences from Science and Technology (S&T), the work in nonformal and informal spaces sets an additional challenge to the preparation of socio-cultural animators. Socio-scientific issues take, at times, heavily relevance within the communities. Pollution, high tension lines, spreading of diseases, food contamination or natural resources conservation are among the socio-scientific issues that often call upon arguments and emotions. In the context of qualifying programmes on socio-cultural animation (social education and community development) within European Higher Education Area (EHEA) the present study describes the Portuguese framework. The comparison of programmes within Portugal aims to contribute to the discussion on the curriculum design for a socio-cultural animator degree (1st cycle of Bologna process). In particular, this study intends to assess how the formation given complies with enabling animators to work, within multiple scenarios, with communities in situations of socio-scientific relevance. A set of themes, issues and both current and potential fields of action, not described or insufficiently described in literature, is identified and analysed in the perspective of a qualified intervention of animators. One of these examples is thoroughly discussed. Finally, suggestions are made about curriculum reforms in order, if possible, to strongly link the desired qualified intervention with a qualifying formation.

BAM framework for OMS using open source technologies

No início da década de 90, as empresas começaram a sentir a necessidade de melhorar o acesso à informação das suas actividades para auxiliar na tomada de decisões. Desta forma, no mundo da informática, emergiu o sector Business Intelligence (BI) composto inicialmente por data warehousing e ferramentas de geração de relatórios. Ao longo dos anos o conceito de BI evoluiu de acordo com as necessidades empresariais, tornando a análise das actividades e do desempenho das organizações em aspectos críticos na gestão das mesmas. A área de BI abrange diversos sectores, sendo o de geração de relatórios e o de análise de dados aqueles que melhor preenchem os requisitos pretendidos no controlo de acesso à informação do negócio e respectivos processos. Actualmente o tempo e a informação são vantagens competitivas e por esse mesmo motivo as empresas estão cada vez mais preocupadas com o facto de o aumento do volume de informação estar a tornar-se insustentável na medida que o tempo necessário para processar a informação é cada vez maior. Por esta razão muitas empresas de software, tais como Microsoft, IBM e Oracle estão numa luta por um lugar neste mercado de BI em expansão. Para que as empresas possam ser competitivas, a sua capacidade de previsão e resposta às necessidades de mercado em tempo real é requisito principal, em detrimento da existência apenas de uma reacção a uma necessidade que peca por tardia. Os produtos de BI têm fama de trabalharem apenas com dados históricos armazenados, o que faz com que as empresas não se possam basear nessas soluções quando o requisito de alguns negócios é de tempo quase real. A latência introduzida por um data warehouse é demasiada para que o desempenho seja aceitável. Desta forma, surge a tecnologia Business Activity Monitoring (BAM) que fornece análise de dados e alertas em tempo quase real sobre os processos do negócio, utilizando fontes de dados como Web Services, filas de mensagens, etc. O conceito de BAM surgiu em Julho de 2001 pela organização Gartner, sendo uma extensão orientada a eventos da área de BI. O BAM define-se pelo acesso em tempo real aos indicadores de desempenho de negócios com o intuito de aumentar a velocidade e eficácia dos processos de negócio. As soluções BAM estão a tornar-se cada vez mais comuns e sofisticadas.

(Virtual) Agents for running electricity markets

This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, named TEMMAS (The Electricity Market Multi-Agent Simulator), explores the integration of two design constructs: (i) the specification of the environmental physical market properties and (ii) the specification of the decision-making (deliberative) and reactive agents. TEMMAS is materialized in an experimental setup involving distinct power generator companies that operate in the market and search for the trading strategies that best exploit their generating units' resources. The experimental results show a coherent market behavior that emerges from the overall simulated environment.

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.

Framework genérica de business intelligence para suporte financeiro

Actualmente, não existem ferramentas open source de Business Intelligence (BI) para suporte à gestão e análise financeira nas empresas, de acordo com o sistema de normalização contabilística (SNC). As diferentes características de cada negócio, juntamente com os requisitos impostos pelo SNC, tornam complexa a criação de uma Framework financeira genérica, que satisfaça, de forma eficiente, as análises financeiras necessárias à gestão das empresas. O objectivo deste projecto é propor uma framework baseada em OLAP, capaz de dar suporte à gestão contabilística e análise financeira, recorrendo exclusivamente a software open source na sua implementação, especificamente, a plataforma Pentaho. Toda a informação contabilística, obtida através da contabilidade geral, da contabilidade analítica, da gestão orçamental e da análise financeira é armazenada num Data mart. Este Data mart suportará toda a análise financeira, incluindo a análise de desvios orçamentais e de fluxo de capitais, permitindo às empresas ter uma ferramenta de BI, compatível com o SNC, que as ajude na tomada de decisões.

Statistical motion learning for improved transform domain Wyner-Ziv video coding

Wyner - Ziv (WZ) video coding is a particular case of distributed video coding (DVC), the recent video coding paradigm based on the Slepian - Wolf and Wyner - Ziv theorems which exploits the source temporal correlation at the decoder and not at the encoder as in predictive video coding. Although some progress has been made in the last years, WZ video coding is still far from the compression performance of predictive video coding, especially for high and complex motion contents. The WZ video codec adopted in this study is based on a transform domain WZ video coding architecture with feedback channel-driven rate control, whose modules have been improved with some recent coding tools. This study proposes a novel motion learning approach to successively improve the rate-distortion (RD) performance of the WZ video codec as the decoding proceeds, making use of the already decoded transform bands to improve the decoding process for the remaining transform bands. The results obtained reveal gains up to 2.3 dB in the RD curves against the performance for the same codec without the proposed motion learning approach for high motion sequences and long group of pictures (GOP) sizes.

Overview of the tuning template for radiography in Europe

HENRE II (Higher Education Network for Radiography in Europe)

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.

Dynamic equilibrium through reinforcement learning

Reinforcement Learning is an area of Machine Learning that deals with how an agent should take actions in an environment such as to maximize the notion of accumulated reward. This type of learning is inspired by the way humans learn and has led to the creation of various algorithms for reinforcement learning. These algorithms focus on the way in which an agent’s behaviour can be improved, assuming independence as to their surroundings. The current work studies the application of reinforcement learning methods to solve the inverted pendulum problem. The importance of the variability of the environment (factors that are external to the agent) on the execution of reinforcement learning agents is studied by using a model that seeks to obtain equilibrium (stability) through dynamism – a Cart-Pole system or inverted pendulum. We sought to improve the behaviour of the autonomous agents by changing the information passed to them, while maintaining the agent’s internal parameters constant (learning rate, discount factors, decay rate, etc.), instead of the classical approach of tuning the agent’s internal parameters. The influence of changes on the state set and the action set on an agent’s capability to solve the Cart-pole problem was studied. We have studied typical behaviour of reinforcement learning agents applied to the classic BOXES model and a new form of characterizing the environment was proposed using the notion of convergence towards a reference value. We demonstrate the gain in performance of this new method applied to a Q-Learning agent.

Advanced side information creation techniques and framework for Wyner-Ziv video coding

Recently, several distributed video coding (DVC) solutions based on the distributed source coding (DSC) paradigm have appeared in the literature. Wyner-Ziv (WZ) video coding, a particular case of DVC where side information is made available at the decoder, enable to achieve a flexible distribution of the computational complexity between the encoder and decoder, promising to fulfill novel requirements from applications such as video surveillance, sensor networks and mobile camera phones. The quality of the side information at the decoder has a critical role in determining the WZ video coding rate-distortion (RD) performance, notably to raise it to a level as close as possible to the RD performance of standard predictive video coding schemes. Towards this target, efficient motion search algorithms for powerful frame interpolation are much needed at the decoder. In this paper, the RD performance of a Wyner-Ziv video codec is improved by using novel, advanced motion compensated frame interpolation techniques to generate the side information. The development of these type of side information estimators is a difficult problem in WZ video coding, especially because the decoder only has available some reference, decoded frames. Based on the regularization of the motion field, novel side information creation techniques are proposed in this paper along with a new frame interpolation framework able to generate higher quality side information at the decoder. To illustrate the RD performance improvements, this novel side information creation framework has been integrated in a transform domain turbo coding based Wyner-Ziv video codec. Experimental results show that the novel side information creation solution leads to better RD performance than available state-of-the-art side information estimators, with improvements up to 2 dB: moreover, it allows outperforming H.264/AVC Intra by up to 3 dB with a lower encoding complexity.

e-learning in the classroom?

As teachers, we are challenged everyday to solve pedagogical problems and we have to fight for our students’ attention in a media rich world. I will talk about how we use ICT in Initial Teacher Training and give you some insight on what we are doing. The most important benefit of using ICT in education is that it makes us reflect on our practice. There is no doubt that our classrooms need to be updated, but we need to be critical about every peace of hardware, software or service that we bring into them. It is not only because our budgets are short, but also because e‐learning is primarily about learning, not technology. Therefore, we need to have the knowledge and skills required to act in different situations, and choose the best tool for the job. Not all subjects are suitable for e‐learning, nor do all students have the skills to organize themselves their own study times. Also not all teachers want to spend time programming or learning about instructional design and metadata. The promised land of easy use of authoring tools (e.g. eXe and Reload) that will lead to all teachers become Learning Objects authors and share these LO in Repositories, all this failed, like previously HyperCard, Toolbook and others. We need to know a little bit of many different technologies so we can mobilize this knowledge when a situation requires it: integrate e‐learning technologies in the classroom, not a flipped classroom, just simple tools. Lecture capture, mobile phones and smartphones, pocket size camcorders, VoIP, VLE, live video broadcast, screen sharing, free services for collaborative work, save, share and sync your files. Do not feel stressed to use everything, every time. Just because we have a whiteboard does not mean we have to make it the centre of the classroom. Start from where you are, with your preferred subject and the tools you master. Them go slowly and try some new tool in a non‐formal situation and with just one or two students. And you don’t need to be alone: subscribe a mailing list and share your thoughts with other teachers in a dedicated forum, even better if both are part of a community of practice, and share resources. We did that for music teachers and it was a success, in two years arriving at 1.000 members. Just do it.