986 resultados para Recognition Memory


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The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination.

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Large area hydrogenated amorphous silicon single and stacked p-i-n structures with low conductivity doped layers are proposed as monochrome and color image sensors. The layers of the structures are based on amorphous silicon alloys (a-Si(x)C(1-x):H). The current-voltage characteristics and the spectral sensitivity under different bias conditions are analyzed. The output characteristics are evaluated under different read-out voltages and scanner wavelengths. To extract information on image shape, intensity and color, a modulated light beam scans the sensor active area at three appropriate bias voltages and the photoresponse in each scanning position ("sub-pixel") is recorded. The investigation of the sensor output under different scanner wavelengths and varying electrical bias reveals that the response can be tuned, thus enabling color separation. The operation of the sensor is exemplified and supported by a numerical simulation.

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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.

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This paper aims at developing the topic of identity and the narration of the self through the other in Harold Pinter’s plays Old Times, Betrayal and A Kind of Alaska. In these plays Pinter deploys strategies to convey multiple implications which are based on the power of memory in which the structure of the plays is concocted.

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The main idea of the article is to consider the interdependence between Politics of Memory (as a type of narrating the Past) and Stereotyping. The author suggests that, in a time of information revolution, we are still constructing images of others on the basis of simplification, overestimation of association between features, and illusory correlations, instead of basing them on knowledge and personal contact. The Politics of Memory, national remembrance, and the historical consciousness play a significant role in these processes, because – as the author argues – they transform historically based 'symbolic analogies' into 'illusory correlations' between national identity and the behavior of its members. To support his theoretical investigation, the author presents results of his draft experiment and two case studies: (a) a social construction of images of neighbors based on Polish narrations about the Past; and (b) various processes of stereotyping based on the Remembrance of the Holocaust. All these considerations lead him to state that the Politics of Memory should be recognized as an influential source of commonly shared stereotypes on other cultures and nations.

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In this paper, we propose a new technique that can identify transaction-local memory (i.e. captured memory), in managed environments, while having a low runtime overhead. We implemented our proposal in a well known STM framework (Deuce) and we tested it in STMBench7 with two different STMs: TL2 and LSA. In both STMs the performance improved significantly (4 times and 2.6 times, respectively). Moreover, running the STAMP benchmarks with our approach shows improvements of 7 times in the best case for the Vacation application.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

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The indiscriminate use of antibiotics in foodproducing animals has received increasing attention as a contributory factor in the international emergence of antibiotic- resistant bacteria (Woodward in Pesticide, veterinary and other residues in food, CRC Press, Boca Raton, 2004). Numerous analytical methods for quantifying antibacterial residues in edible animal products have been developed over years (Woodward in Pesticide, veterinary and other residues in food, CRC Press, Boca Raton, 2004; Botsoglou and Fletouris in Handbook of food analysis, residues and other food component analysis, Marcel Dekker, Ghent, 2004). Being Amoxicillin (AMOX) one of those critical veterinary drugs, efforts have been made to develop simple and expeditious methods for its control in food samples. In literature, only one AMOX-selective electrode has been reported so far. In that work, phosphotungstate:amoxycillinium ion exchanger was used as electroactive material (Shoukry et al. in Electroanalysis 6:914–917, 1994). Designing new materials based on molecularly imprinted polymers (MIPs) which are complementary to the size and charge of AMOX could lead to very selective interactions, thus enhancing the selectivity of the sensing unit. AMOXselective electrodes used imprinted polymers as electroactive materials having AMOX as target molecule to design a biomimetic imprinted cavity. Poly(vinyl chloride), sensors of methacrylic acid displayed Nernstian slopes (60.7 mV/decade) and low detection limits (2.9×10-5 mol/L). The potentiometric responses were not affected by pH within 4–5 and showed good selectivity. The electrodes were applied successfully to the analysis of real samples.

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As a result of the stressful conditions in aquaculture facilities there is a high risk of bacterial infections among cultured fish. Chlortetracycline (CTC) is one of the antimicrobials used to solve this problem. It is a broad spectrum antibacterial active against a wide range of Gram-positive and Gram-negative bacteria. Numerous analytical methods for screening, identifying, and quantifying CTC in animal products have been developed over the years. An alternative and advantageous method should rely on expeditious and efficient procedures providing highly specific and sensitive measurements in food samples. Ion-selective electrodes (ISEs) could meet these criteria. The only ISE reported in literature for this purpose used traditional electro-active materials. A selectivity enhancement could however be achieved after improving the analyte recognition by molecularly imprinted polymers (MIPs). Several MIP particles were synthesized and used as electro-active materials. ISEs based in methacrylic acid monomers showed the best analytical performance according to slope (62.5 and 68.6 mV/decade) and detection limit (4.1×10−5 and 5.5×10−5 mol L−1). The electrodes displayed good selectivity. The ISEs are not affected by pH changes ranging from 2.5 to 13. The sensors were successfully applied to the analysis of serum, urine and fish samples.

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Learning and teaching processes, like all human activities, can be mediated through the use of tools. Information and communication technologies are now widespread within education. Their use in the daily life of teachers and learners affords engagement with educational activities at any place and time and not necessarily linked to an institution or a certificate. In the absence of formal certification, learning under these circumstances is known as informal learning. Despite the lack of certification, learning with technology in this way presents opportunities to gather information about and present new ways of exploiting an individual’s learning. Cloud technologies provide ways to achieve this through new architectures, methodologies, and workflows that facilitate semantic tagging, recognition, and acknowledgment of informal learning activities. The transparency and accessibility of cloud services mean that institutions and learners can exploit existing knowledge to their mutual benefit. The TRAILER project facilitates this aim by providing a technological framework using cloud services, a workflow, and a methodology. The services facilitate the exchange of information and knowledge associated with informal learning activities ranging from the use of social software through widgets, computer gaming, and remote laboratory experiments. Data from these activities are shared among institutions, learners, and workers. The project demonstrates the possibility of gathering information related to informal learning activities independently of the context or tools used to carry them out.

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The application of information technologies (specially the Internet, Web 2.0 and social tools) make informal learning more visible. This kind of learning is not linked to an institution or a period of time, but it is important enough to be taken into account. On the one hand, learners should be able to communicate to the institutions they are related to, what skills they possess, whether they were achieved in a formal or informal way. On the other hand the companies and educational institutions need to have a deeper knowledge about the competencies of their staff. The TRAILER project provides a methodology supported by a technological framework to facilitate communication about informal learning between businesses, employees and learners. The paper presents the project and some of the work carried out, an exploratory analysis about how informal learning is considered and the technological framework proposed. Whilst challenges remain in terms of establishing the meaningfulness of technological engagement for employees and businesses, the continuing transformation of the social, technological and educational environment is likely to lead to greater emphasis for the effective exploitation of informal learning.

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Pesticide exposure during brain development could represent an important risk factor for the onset of neurodegenerative diseases. Previous studies investigated the effect of permethrin (PERM) administered at 34 mg/kg, a dose close to the no observable adverse effect level (NOAEL) from post natal day (PND) 6 to PND 21 in rats. Despite the PERM dose did not elicited overt signs of toxicity (i.e. normal body weight gain curve), it was able to induce striatal neurodegeneration (dopamine and Nurr1 reduction, and lipid peroxidation increase). The present study was designed to characterize the cognitive deficits in the current animal model. When during late adulthood PERM treated rats were tested for spatial working memory performances in a T-maze-rewarded alternation task they took longer to choose for the correct arm in comparison to age matched controls. No differences between groups were found in anxiety-like state, locomotor activity, feeding behavior and spatial orientation task. Our findings showing a selective effect of PERM treatment on the T-maze task point to an involvement of frontal cortico-striatal circuitry rather than to a role for the hippocampus. The predominant disturbances concern the dopamine (DA) depletion in the striatum and, the serotonin (5-HT) and noradrenaline (NE) unbalance together with a hypometabolic state in the medial prefrontal cortex area. In the hippocampus, an increase of NE and a decrease of DA were observed in PERM treated rats as compared to controls. The concentration of the most representative marker for pyrethroid exposure (3-phenoxybenzoic acid) measured in the urine of rodents 12 h after the last treatment was 41.50 µ/L and it was completely eliminated after 96 h.

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The recent trends of chip architectures with higher number of heterogeneous cores, and non-uniform memory/non-coherent caches, brings renewed attention to the use of Software Transactional Memory (STM) as a fundamental building block for developing parallel applications. Nevertheless, although STM promises to ease concurrent and parallel software development, it relies on the possibility of aborting conflicting transactions to maintain data consistency, which impacts on the responsiveness and timing guarantees required by embedded real-time systems. In these systems, contention delays must be (efficiently) limited so that the response times of tasks executing transactions are upper-bounded and task sets can be feasibly scheduled. In this paper we assess the use of STM in the development of embedded real-time software, defending that the amount of contention can be reduced if read-only transactions access recent consistent data snapshots, progressing in a wait-free manner. We show how the required number of versions of a shared object can be calculated for a set of tasks. We also outline an algorithm to manage conflicts between update transactions that prevents starvation.

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The usage of COTS-based multicores is becoming widespread in the field of embedded systems. Providing realtime guarantees at design-time is a pre-requisite to deploy real-time systems on these multicores. This necessitates the consideration of the impact of the contention due to shared low-level hardware resources on the Worst-Case Execution Time (WCET) of the tasks. As a step towards this aim, this paper first identifies the different factors that make the WCET analysis a challenging problem in a typical COTS-based multicore system. Then, we propose and prove, a mathematically correct method to determine tight upper bounds on the WCET of the tasks, when they are co-scheduled on different cores.