Estimation of signal subspace on hyperspectral data

Dimensionality reduction plays a crucial role in many hyperspectral data processing and analysis algorithms. This paper proposes a new mean squared error based approach to determine the signal subspace in hyperspectral imagery. The method first estimates the signal and noise correlations matrices, then it selects the subset of eigenvalues that best represents the signal subspace in the least square sense. The effectiveness of the proposed method is illustrated using simulated and real hyperspectral images.

Otimização da produção de biogás com recurso a redes neuronais artificiais

Numa Estação de Tratamento de Águas Residuais (ETAR), são elevados os custos não só de tratamento das águas residuais como também de manutenção dos equipamentos lá existentes, nesse sentido procura-se utilizar processos capazes de transformar os resíduos em produtos úteis. A Digestão Anaeróbia (DA) é um processo atualmente disponível capaz de contribuir para a redução da poluição ambiental e ao mesmo tempo de valorizar os subprodutos gerados. Durante o processo de DA é produzido um gás, o biogás, que pode ser utilizado como fonte de energia, reduzindo assim a dependência energética da ETAR e a emissão de gases com efeito de estufa para a atmosfera. A otimização do processo de DA das lamas é essencial para o aumento da produção de biogás, mas a complexidade do processo constitui um obstáculo à sua otimização. Neste trabalho, aplicaram-se Redes Neuronais Artificiais (RNA) ao processo de DA de lamas de ETAR. RNA são modelos simplificados inspirados no funcionamento das células neuronais humanas e que adquirem conhecimento através da experiência. Quando a RNA é criada e treinada, produz valores de output aproximadamente corretos para os inputs fornecidos. Foi esse o motivo para recorrer a RNA na otimização da produção de biogás no digestor I da ETAR Norte da SIMRIA, usando o programa NeuralToolsTM da PalisadeTM para desenvolvimento das RNA. Para tal, efetuou-se uma análise e tratamento de dados referentes aos últimos quatro anos de funcionamento do digestor. Os resultados obtidos permitiram concluir que as RNA modeladas apresentam boa capacidade de generalização do processo de DA. Considera-se que este caso de estudo é promissor, fornecendo uma boa base para o desenvolvimento de modelos eventualmente mais gerais de RNA que, aplicado conjuntamente com as características de funcionamento de um digestor e o processo de DA, permitirá otimizar a produção de biogás em ETAR.

A microscope for the data center

Nowadays, data centers are large energy consumers and the trend for next years is expected to increase further, considering the growth in the order of cloud services. A large portion of this power consumption is due to the control of physical parameters of the data center (such as temperature and humidity). However, these physical parameters are tightly coupled with computations, and even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in the cloud infrastructure hosted in the data center. Therefore, managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolution of the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center and with them, find opportunities to optimize energy consumptions. Having a high-resolution picture of the data center conditions, also enables minimizing local hot-spots, perform more accurate predictive maintenance (failures in all infrastructure equipments can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

Ferramenta Inteligente de Recolha de Dados

À medida que são feitas modificações nas legislações em vigor em relação às energias renováveis, de forma a incentivar o uso destas, surge a necessidade de sincronização do consumo da instalação com a sua própria produção. As empresas líderes de mercado já possuem soluções que permitem a recolha de dados das instalações fotovoltaicas para posterior monitorização e disponibilização ao cliente. Contudo, estas soluções possuem pontos negativos tais como o preço e limitações na potência instalada permitida. Neste contexto, este documento apresenta a descrição de uma solução que serve como uma alternativa muito mais barata às soluções apresentadas pelas principais marcas mundiais no âmbito desta área, além de ser a única solução disponível desenvolvida em território nacional. Como prova da funcionalidade da solução, são descritos e apresentados diferentes tipos de testes, que simulam a interação de um utilizador com a solução desenvolvida, levados a cabo em instalações solares fotovoltaicas reais, sendo os seus resultados analisados e evidenciando a facilidade de utilização desta solução.

Software development for estimation of optical clearing agent’s diffusion coefficients in biological tissues

The study of chemical diffusion in biological tissues is a research field of high importance and with application in many clinical, research and industrial areas. The evaluation of diffusion and viscosity properties of chemicals in tissues is necessary to characterize treatments or inclusion of preservatives in tissues or organs for low temperature conservation. Recently, we have demonstrated experimentally that the diffusion properties and dynamic viscosity of sugars and alcohols can be evaluated from optical measurements. Our studies were performed in skeletal muscle, but our results have revealed that the same methodology can be used with other tissues and different chemicals. Considering the significant number of studies that can be made with this method, it becomes necessary to turn data processing and calculation easier. With this objective, we have developed a software application that integrates all processing and calculations, turning the researcher work easier and faster. Using the same experimental data that previously was used to estimate the diffusion and viscosity of glucose in skeletal muscle, we have repeated the calculations with the new application. Comparing between the results obtained with the new application and with previous independent routines we have demonstrated great similarity and consequently validated the application. This new tool is now available to be used in similar research to obtain the diffusion properties of other chemicals in different tissues or organs.

Optimization of fMRI Processing Parameters for Simutaneous Acquisition of EEG/fMRI in Focal Epilepsy

In the context of focal epilepsy, the simultaneous combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) holds a great promise as a technique by which the hemodynamic correlates of interictal spikes detected on scalp EEG can be identified. The fact that traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the lobes, brings the need of mapping with more precision the epileptogenic cortical regions. On the other hand, fMRI suggested localizations more consistent with the ictal clinical manifestations detected. This study was developed in order to improve the knowledge about the way parameters involved in the physical and mathematical data, produced by the EEG/fMRI technique processing, would influence the final results. The evaluation of the accuracy was made by comparing the BOLD results with: the high resolution EEG maps; the malformative lesions detected in the T1 weighted MR images; and the anatomical localizations of the diagnosed symptomatology of each studied patient. The optimization of the set of parameters used, will provide an important contribution to the diagnosis of epileptogenic focuses, in patients included on an epilepsy surgery evaluation program. The results obtained allowed us to conclude that: by associating the BOLD effect with interictal spikes, the epileptogenic areas are mapped to localizations different from those obtained by the EEG maps representing the electrical potential distribution across the scalp (EEG); there is an important and solid bond between the variation of particular parameters (manipulated during the fMRI data processing) and the optimization of the final results, from which smoothing, deleted volumes, HRF (used to convolve with the activation design), and the shape of the Gamma function can be certainly emphasized.

Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Sistema de aquisição e comunicação para sensores magnetoelétricos

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

A linear algebra approach to OLAP

Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.

Pervasive adaptive data acquisition gateway for critical healthcare

The data acquisition process in real-time is fundamental to provide appropriate services and improve health professionals decision. In this paper a pervasive adaptive data acquisition architecture of medical devices (e.g. vital signs, ventilators and sensors) is presented. The architecture was deployed in a real context in an Intensive Care Unit. It is providing clinical data in real-time to the INTCare system. The gateway is composed by several agents able to collect a set of patients’ variables (vital signs, ventilation) across the network. The paper shows as example the ventilation acquisition process. The clients are installed in a machine near the patient bed. Then they are connected to the ventilators and the data monitored is sent to a multithreading server which using Health Level Seven protocols records the data in the database. The agents associated to gateway are able to collect, analyse, interpret and store the data in the repository. This gateway is composed by a fault tolerant system that ensures a data store in the database even if the agents are disconnected. The gateway is pervasive, universal, and interoperable and it is able to adapt to any service using streaming data.

Enhancing the vertical resolution of surface georadar data

There are far-reaching conceptual similarities between bi-static surface georadar and post-stack, "zero-offset" seismic reflection data, which is expressed in largely identical processing flows. One important difference is, however, that standard deconvolution algorithms routinely used to enhance the vertical resolution of seismic data are notoriously problematic or even detrimental to the overall signal quality when applied to surface georadar data. We have explored various options for alleviating this problem and have tested them on a geologically well-constrained surface georadar dataset. Standard stochastic and direct deterministic deconvolution approaches proved to be largely unsatisfactory. While least-squares-type deterministic deconvolution showed some promise, the inherent uncertainties involved in estimating the source wavelet introduced some artificial "ringiness". In contrast, we found spectral balancing approaches to be effective, practical and robust means for enhancing the vertical resolution of surface georadar data, particularly, but not exclusively, in the uppermost part of the georadar section, which is notoriously plagued by the interference of the direct air- and groundwaves. For the data considered in this study, it can be argued that band-limited spectral blueing may provide somewhat better results than standard band-limited spectral whitening, particularly in the uppermost part of the section affected by the interference of the air- and groundwaves. Interestingly, this finding is consistent with the fact that the amplitude spectrum resulting from least-squares-type deterministic deconvolution is characterized by a systematic enhancement of higher frequencies at the expense of lower frequencies and hence is blue rather than white. It is also consistent with increasing evidence that spectral "blueness" is a seemingly universal, albeit enigmatic, property of the distribution of reflection coefficients in the Earth. Our results therefore indicate that spectral balancing techniques in general and spectral blueing in particular represent simple, yet effective means of enhancing the vertical resolution of surface georadar data and, in many cases, could turn out to be a preferable alternative to standard deconvolution approaches.

Gestió d'un magatzem de fruits secs

Estudi i disseny de la implantació d'un ERP (Enterprise Resource Planning) en una fàbrica de fruits secs.

Planificació, anàlisi i disseny d'un programari de gestió d'un magatzem d'olives i conserves

Disseny d'un programari de gestió de magatzems on quedin reflectides les seves entrades, sortides i altres operacions pròpies dels magatzems. El programari ha de ser escalable i perdurar en el temps a més a més de permetre operacions d¿actualització, esborrat, addicció de dades i les operacionsfonamentals de consulta.

Implantación de una solución SIG para la ayuda a la toma dedecisiones para la explotación de recursos del subsuelo

L'objectiu és una aplicació que permeti realitzar el càlcul del volum de terres disponibles en el subsòl d'un àrea seleccionada. L'objectiu final del projecte serà crear un Sistema d'Informació Geogràfica SIG que ajudi a valorar quines parcel¿les de l'àrea seleccionada són les que disposen de més volum de terres per iniciar la seva explotació. Per a això, es disposa del programari gvSIG i les seves extensions (SEXTANTE) i de tota la informació que es pugui obtenir sobre els SIG, Cartografia, Geodèsia... Per dur a terme aquest projecte es necessita tenir experiència en Bases de dades, Programació Orientada a Objectes i seria recomanable tenir coneixements sobre Enginyeria del Programador. El projecte se centrarà en la utilització de gvSIG, com un exemple concret de programari SIG de lliure accés, solució desenvolupada per la ¿Conselleria d%o2019Obris Publiquis de la Generalitat Valenciana¿. Una part d'aquest projecte consistirà a avaluar aquest programari. El resultat final serà l'obtenció dels coneixements necessaris per poder treballar amb dades espacials a més d'una aplicació SIG per al càlcul del volum de terres d'un àrea seleccionada.

Interacció Humana amb els ordinadors :Usabilitat de dispositius mòbils SmartPhones

El que vol tractar aquest TFC son els aspectes referents a la usabilitat dels dispositius de mà anomenats Smartphone, comparant la usabilitat depenen del tipus d¿introducció de dades.