A semidefinite relaxation procedure for fault-tolerant observer design

A fault-tolerant observer design methodology is proposed. The aim is to guarantee a minimum level of closed-loop performance under all possible sensor fault combinations while optimizing performance under the nominal, fault-free condition. A novel approach is proposed to tackle the combinatorial nature of the problem, which is computationally intractable even for a moderate number of sensors, by recasting the problem as a robust performance problem, where the uncertainty set is composed of all combinations of a set of binary variables. A procedure based on an elimination lemma and an extension of a semidefinite relaxation procedure for binary variables is then used to derive sufficient conditions (necessary and sufficient in the case of one binary variable) for the solution of the problem which significantly reduces the number of matrix inequalities needed to solve the problem. The procedure is illustrated by considering a fault-tolerant observer switching scheme in which the observer outputs track the actual sensor fault condition. A numerical example from an electric power application is presented to illustrate the effectiveness of the design

Towards a single-photon energy-sensitive pixel readout chip: pixel level ADCs and digital readout circuitry

Unlike conventional CMOS imaging, a single\ud photon imager detects each individual photon impinging on\ud a detector, accumulating the number of photons during a\ud certain time window and not the charge generated by the all\ud the photons hitting the detector during said time window.\ud The latest developments in the semiconductor industry\ud are allowing faster and more complex chips to be designed\ud and manufactured. With these developments in mind we are\ud working towards the next step in single photon X-ray imaging:\ud energy sensitive pixel readout chips. The goal is not only\ud to detect and count individual photons, but also to measure\ud the charge deposited in the detector by each photon, and\ud consequently determine its energy. Basically, we are aiming\ud at a spectrometer-in-a-pixel, or a “color X-ray camera”.\ud The approach we have followed towards this goal is the\ud design of small analog-to-digital-converters at the pixel level,\ud together with a very fast digital readout from the pixels to\ud the periphery of the chip, where the data will be transmitted\ud off-chip.\ud We will present here the design and measurement on prototype\ud chips of two different 4-bit pixel level ADCs. The\ud ADCs are optimized for very small area and low power, with\ud a resolution of 4-bits and a sample rate of 1 Msample/s. The\ud readout architecture is based around current-mode sense\ud amplifiers and asynchronous token-passing between the pixels.\ud This is done in order to achieve event-by-event readout\ud and, consequently, on-line imaging. We need to read eventby-\ud event (photon-by-photon), because we cannot have memory\ud on the pixels due to obvious size constraints. We use\ud current-mode sense amplifiers because they perform very\ud well in similar applications as very fast static-RAM readout

Real-time phase-shift detection of the surface plasmon resonance

We investigate a method to directly measure the phase of a laser beam reflected from a metallic film after excitation of surface plasmon polaritons. This method permits real time access to the phase information, it increases the possible speed of data acquisition, and it may thus prove useful for increasing the sensitivity of surface plasmon based sensors

Speech into Sign Language Statistical Translation System for Deaf People

This paper presents a set of experiments used to develop a statistical system from translating speech to sign language for deaf people. This system is composed of an Automatic Speech Recognition (ASR) system, followed by a statistical translation module and an animated agent that represents the different signs. Two different approaches have been used to perform the translations: a phrase-based system and a finite state transducer. For the evaluation, the followings figures have been considered: WER (Word Error Rate), BLEU and NIST. The paper presents translation results of reference sentences and sentences from the automatic speech recognizer. Also three different configurations have been evaluated for the speech recognizer. The best results were obtained with the finite state transducer, with a word error rate of 28.21% for the reference text, and 29.27% using the ASR output

Fully Automatic Expression-Invariant Face Correspondence

We consider the problem of computing accurate point-to-point correspondences among a set of human face scans with varying expressions. Our fully automatic approach does not require any manually placed markers on the scan. Instead, the approach learns the locations of a set of landmarks present in a database and uses this knowledge to automatically predict the locations of these landmarks on a newly available scan. The predicted landmarks are then used to compute point-to-point correspondences between a template model and the newly available scan. To accurately fit the expression of the template to the expression of the scan, we use as template a blendshape model. Our algorithm was tested on a database of human faces of different ethnic groups with strongly varying expressions. Experimental results show that the obtained point-to-point correspondence is both highly accurate and consistent for most of the tested 3D face models

Demanda de informação em sistemas agroflorestais para agricultura familiar sustentável no Nordeste paraense.

Práticas alternativas começam a ser vistas como uma garantia de preservação dos sistemas produtivos da agricultura familiar. O uso de sistemas alternativos para recuperação de áreas degradadas e/ou abandonadas é fundamental para alcançar sustentabilidade de unidades de produção familiar rurais, com propostas tecnológicas e baseadas no conhecimento e uso racional dos recursos naturais. Disponibilizar alternativas sustentáveis à recuperação de áreas degradadas com agricultura e pastagens com vistas ao uso sustentado da terra e melhoria de vida dos agricultores da Amazônia foi objetivo do projeto "Desenvolvimento e Validação de Estratégias Participativas de Recuperação de Áreas Agrícolas e Pastagens Degradadas na Amazônia", componente da Sub-Rede RECUPERAMAZ. Para viabilizar o processo de divulgação científica dos resultados de pesquisa, foi realizada uma ação de identificação de demanda por informação, aplicando-se metodologia apropriada e adaptada, para 81 agricultores familiares, representantes de 16 associações comunitárias rurais, distribuídos entre os municípios de Igarapé-Açu, Mãe do Rio e Concórdia do Pará, região Nordeste Paraense. Os resultados indicam que os agricultores apresentam um perfil que facilita o processo de divulgação dos resultados de pesquisas, com maior ou menor habilidade para uso de diferentes mídias e fontes. Demonstram interesse em "novos" conhecimentos, i.e. através das informações fornecidas por técnicos, pelas instituições governamentais e não-governamentais entre outros e demandam informações relacionadas às suas práticas agrícolas cotidianas para soluções de diferentes problemas

Dynamical principles in neuroscience

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?This work was supported by NSF Grant No. NSF/EIA-0130708, and Grant No. PHY 0414174; NIH Grant No. 1 R01 NS50945 and Grant No. NS40110; MEC BFI2003-07276, and Fundación BBVA