Adquiridor de dades analògiques

L’empresa TER és una empresa dedicada al disseny i la construcció de projectes electrònics. La necessitat de comprovar el funcionament dels seus dissenys ha motivat a realitzar un projecte capaç de recollir dades significatives de diferents àmbits com pressió, voltatge, intensitat, temperatura etc. En el mercat les dos maneres més freqüents de recollir aquestes dades són per sensors que donen una equivalència d’un paràmetre físic a un rang de voltatge (0 a 10v) o per corrent (4 a 20mA). Aquestes dades seran adquirides i processades periòdicament per un microcontrolador que les emmagatzemarà una a una per posteriorment visualitzar-les en un LCD o en un programa fet per Visual Basic capaç de generar un document que guardi les dades en Excel. Com a conclusions es pot dir que s’han assolit els objectius, tant els personals com els proposats, per tal de tenir un prototip funcional

The Importance of Semantics: Visual World Studies on Drawing Inferences and Resolving Anaphors

The present thesis investigated the importance of semantics in generating inferences during discourse processing. Three aspects of semantics, gender stereotypes, implicit causality information and proto-role properties, were used to investigate whether semantics is activated elaboratively during discourse comprehension and what its relative importance is in backward inferencing compared to discourse/structural cues. Visual world eye-tracking studies revealed that semantics plays an important role in both backward and forward inferencing: Gender stereotypes and implicit causality information is activated elaboratively during online discourse comprehension. Moreover, gender stereotypes, implicit causality and proto-role properties of verbs are all used in backward inferencing. Importantly, the studies demonstrated that semantic cues are weighed against discourse/structural cues. When the structural cues consist of a combination of cues that have been independently shown to be important in backward inferencing, semantic effects may be masked, whereas when the structural cues consist of a combination of fewer prominent cues, semantics can have an earlier effect than structural factors in pronoun resolution. In addition, the type of inference matters, too: During anaphoric inferencing semantics has a prominent role, while discourse/structural salience attains more prominence during non-anaphoric inferencing. Finally, semantics exhibits a strong role in inviting new inferences to revise earlier made inferences even in the case the additional inference is not needed to establish coherence in discourse. The findings are generally in line with the Mental Model approaches. Two extended model versions are presented that incorporate the current findings into the earlier literature. These models allow both forward and backward inferencing to occur at any given moment during the course of processing; they also allow semantic and discourse/structural cues to contribute to both of these processes. However, while the Mental Model 1 does not assume interactions between semantic and discourse/structural factors in forward inferencing, the Mental Model 2 does assume such a link.

Advancing towards inclusive social research: visual methods as opportunities for people with severe mental illness to participate in research

This article explores the possibilities offered by visual methods in the move towards inclusive research, reviewing some methodological implications of said research and reflecting on the potential of visual methods to meet these methodological requirements. A study into the impact of work on social inclusion and the social relationships of people suffering from severe mental illness (SMI) serves to illustrate the use of visual methods such as photo elicitation and graphic elicitation in the context of in-depth interviews with the aim of improving the aforementioned target group’s participation in research, participation understood as one of the basic elements of inclusive approaches. On the basis of this study, we reflect on the potential of visual methods to improve the inclusive approach to research and conclude that these methods are open and flexible in awarding participantsa voice, allowingpeople with SMI to express their needs, and therefore adding value to said approach

Uma experiência didática de corrosão usando colorimetria visual

In this paper, a simple and rapid method of evaluating galvanized steel sheet corrosion in a CuSO4 solution, as an experimentation proposal for corrosion teaching. Galvanized steel corrosion is present in tanks and tubing by leading of natural or industrial waters which contain soluble copper compounds. This was the rationale for choosing the Cu2+ ions solution as an oxidizing agent. The method principle is based on visual colorimetry because the used oxidant has an intense blue color. Thus, a change in its concentration as a result of the corrosive process can be followed by a color intensity change in the solution thereby allowing evaluation of the corrosion rate.

Visual demonstration of the ionic strength effect in the classroom: the Debye-Hückel limiting law

The effects of ionic strength on ions in aqueous solutions are quite relevant, especially for biochemical systems, in which proteins and amino acids are involved. The teaching of this topic and more specifically, the Debye-Hückel limiting law, is central in chemistry undergraduate courses. In this work, we present a description of an experimental procedure based on the color change of aqueous solutions of bromocresol green (BCG), driven by addition of electrolyte. The contribution of charge product (z+|z-|) to the Debye-Hückel limiting law is demonstrated when the effects of NaCl and Na2SO4 on the color of BCG solutions are compared.

Demonstration Platform for Visual Quality Metrics

This thesis presents two graphical user interfaces for the project DigiQ - Fusion of Digital and Visual Print Quality, a project for computationally modeling the subjective human experience of print quality by measuring the image with certain metrics. After presenting the user interfaces, methods for reducing the computation time of several of the metrics and the image registration process required to compute the metrics, and details of their performance are given. The weighted sample method for the image registration process was able to signifigantly decrease the calculation times while resulting in some error. The random sampling method for the metrics greatly reduced calculation time while maintaining excellent accuracy, but worked with only two of the metrics.

Nematode community, trophic structure and population fluctuation in soybean fields

Temporal (monthly in three fields for 12 months) and spatial (once in 23 fields during March-April) samplings were conducted in the major soybean (Glycine max)-growing region of the Brazilian Federal District. Fifty-three nematode genera were found in both samplings, but 13 were detected only by the temporal sampling, and one only by the spatial sampling. Fifty-three percent were plant-parasites, 35% were bacterivores, and about 12% were fungivores, predators and omnivores constituted the community that was dominated by the genera Helicotylenchus (40% of total abundance), Acrobeles (15%), Cephalobus (7.6%), Meloidogyne(5.6%) and Pratylenchus (4.9%). Heterodera glycines was not found in this study. There were no differences in ten ecological measurements [Ds, H', Es, T, FF/BF, (FF+BF)/PP, MI, PPI, mMI, and Dorylaimida (%)] between the two sampling types, but differences in indexes d and J'. Plant parasite populations dropped at the end of the crop cycle, remained at low levels during the dry season and the seedling period, then increased again in the crop-growing season. Fungivores maintained their low populations throughout the year, increasing only in June and July, the post-harvest period, when soil fungi decomposed root tissue. The population of bacterivores slightly declined during the dry season and the initial rainy season, but peaked in the middle of the rainy season, apparently associated with soil humidity. In the five most abundant nematodes, those of Acrobeles and Pratylenchus were more populous in wet soils, Cephalobus and Meloidogyne adapted well in dry soils, but Helicotylenchus survived abundantly in a wide range of soil moisture.

Virulence pattern of Pyricularia grisea isolates from farmers' fields on newly released upland rice cultivars

The virulence pattern of the isolates of Pyricularia grisea from commercial fields of the upland rice (Oryza sativa) cultivars 'Primavera' and 'BRS Bonança' was analyzed. A hundred and seventy monoconidial isolates of the pathogen virulent to 'Primavera' and 139 to 'BRS Bonança' collected from eight fields, during two years (2001-2003) were tested, under greenhouse conditions, on six newly released rice cultivars. Differences in virulence pattern were observed in pathogenic populations of 'Primavera' and 'BRS Bonança'. Isolates with virulence to improved cultivars were common in samples from farmers' fields in the absence of aloinfection. The virulence frequency of P. grisea isolates collected from 'Primavera'' to cultivars 'BRS Vencedora', 'BRS Colosso', 'BRS Liderança', 'BRS Soberana', 'BRS Curinga' and 'BRS Talento', was high in descending order. On the other hand, in the fungus population of 'BRS BRS Bonança' virulence frequency was high in 'BRS Talento', followed by 'BRS Curinga', 'BRS Vencedora', 'BRS Liderança', 'BRS Colosso' and 'BRS Soberana'. While virulence to 'BRS Talento' was rare among isolates from 'Primavera', it was most frequent in isolates of 'BRS Bonança'. The six improved rice cultivars permitted to differentiating agriculturally important virulences in the pathogen population which can be utilized in selecting breeding lines for specific resistance, in rice blast improvement program.

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Determinação do tamanho ótimo da parcela experimental pelos métodos da máxima curvatura modificado, do coeficiente de correlação intraclasse e da análise visual em testes clonais de eucalipto

O objetivo deste trabalho foi determinar o tamanho ótimo da parcela experimental em testes clonais de eucalipto, por meio dos métodos da máxima curvatura modificado, do coeficiente de correlação intraclasse e da análise visual, com base nas características de crescimento em altura, dap e volume. A partir de quatro testes clonais, dispostos no delineamento em blocos ao acaso, com quatro repetições e parcela experimental quadrada de 25 plantas (5 x 5), foram simulados diferentes tamanhos de parcela com 2, 3, 4, 5, 9, 10, 15, 20 e 25 plantas, visando determinar o tamanho ótimo da parcela pelos métodos de máxima curvatura modificado, do coeficiente de correlação intraclasse e da análise visual. Pôde-se concluir que em programas iniciais para seleção de clones parcelas de cinco a dez plantas proporcionam boa precisão experimental, sendo recomendadas, principalmente, em situação com limitações de mudas, teste de grande número de clones e avaliações de cunho preliminar e em idades precoces.

Propriedades mecânicas de peças com dimensões estruturais de Pinus spp: correlação entre resistência à tração e classificação visual

A redução da disponibilidade de espécies de madeiras nativas e seus efeitos na economia, associada ao fortalecimento dos conceitos de preservação ambiental, criou a necessidade de desenvolvimento de alternativas viáveis para utilização racional de espécies de reflorestamento. E uma das opções é a realização de classificação visual das peças. Autores de trabalhos desenvolvidos nessa linha de pesquisa verificaram a adequação das regras de classificação visual do Southern Pine Inspection Bureau (SPIB) dos EUA à madeira de Pinus do Brasil e apresentaram proposta para normalizar o processo de classificação visual dessa madeira. Nessa classificação, os aspectos com maior influência são: presença de nós, desvio de grã em relação ao eixo da peça e densidade de anéis de crescimento. Assim, esta pesquisa apresenta um estudo experimental que consistiu na classificação visual e determinação da resistência à tração de 85 peças de Pinus spp e um estudo teórico, que propôs uma equação para determinar a resistência à tração média de peças estruturais em função da classificação visual. Com este trabalho, foi possível observar a influência dos nós e dos anéis de crescimento sobre a resistência à tração das peças analisadas.

Natural regeneration in abandoned fields following intensive agricultural land use in an Atlantic Forest Island, Brazil

The time required to regrowth a forest in degraded areas depends on how the forest is removed and on the type of land use following removal. Natural regeneration was studied in abandoned old fields after intensive agricultural land use in areas originally covered by Brazilian Atlantic Forests of the Anchieta Island, Brazil in order to understand how plant communities reassemble following human disturbances as well as to determine suitable strategies of forest restoration. The fields were classified into three vegetation types according to the dominant plant species in: 1) Miconia albicans (Sw.) Triana (Melastomataceae) fields, 2) Dicranopteris flexuosa (Schrader) Underw. (Gleicheniaceae) thickets, and 3) Gleichenella pectinata (Willd.) Ching. (Gleicheniaceae) thickets. Both composition and structure of natural regeneration were compared among the three dominant vegetation types by establishing randomly three plots of 1 x 3 m in five sites of the island. A gradient in composition and abundance of species in natural regeneration could be observed along vegetation types from Dicranopteris fern thickets to Miconia fields. The gradient did not accurately follow the pattern of spatial distribution of the three dominant vegetation types in the island regarding their proximity of the remnant forests. A complex association of biotic and abiotic factors seems to be affecting the seedling recruitment and establishment in the study plots. The lowest plant regeneration found in Dicranopteris and Gleichenella thickets suggests that the ferns inhibit the recruitment of woody and herbaceous species. Otherwise, we could not distinguish different patterns of tree regeneration among the three vegetation types. Our results showed that forest recovery following severe anthropogenic disturbances is not direct, predictable or even achievable on its own. Appropriated actions and methods such as fern removal, planting ground covers, and enrichment planting with tree species were suggested in order to restore the natural forest regeneration process in the abandoned old fields.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.