912 resultados para 280200 Artificial Intelligence and Signal and Image Processing


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Two experiments investigated the conditions under which majority and minority sources instigate systematic processing of their messages. Both experiments crossed source status (majority vs. minority) with message quality (strong vs. weak arguments). In each experiment, message elaboration was manipulated by varying either motivational (outcome relevance, Experiment 1) or cognitive (orientating tasks, Experiment 2) factors. The results showed that when either motivational or cognitive factors encouraged low message elaboration, there was heuristic acceptance of the majority position without detailed message processing. When the level of message elaboration was intermediate, there was message processing only for the minority source. Finally, when message elaboration was high, there was message processing for both source conditions. These results show that majority and minority influence is sensitive to motivational and cognitive factors that constrain or enhance message elaboration and that both sources can lead to systematic processing under specific circumstances. © 2007 by the Society for Personality and Social Psychology, Inc.

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This paper examined the joint predictive effects of trait emotional intelligence (trait-EI), Extraversion, Conscientiousness, and Neuroticism on 2 facets of general well-being and job satisfaction. An employed community sample of 123 individuals from the Indian subcontinent participated in the study, and completed measures of the five-factor model of personality, trait-EI, job satisfaction, and general well-being facets worn-out and up-tight. Trait-EI was related but distinct from the 3 personality variables. Trait-EI demonstrated the strongest correlation with job satisfaction, but predicted general well-being no better than Neuroticism. In regression analyses, trait-EI predicted between 6% and 9% additional variance in the well-being criteria, beyond the 3 personality traits. It was concluded that trait-EI may be useful in examining dispositional influences on psychological well-being.

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In a group of adult dyslexics word reading and, especially, word spelling are predicted more by what we have called lexical learning (tapped by a paired-associate task with pictures and written nonwords) than by phonological skills. Nonword reading and spelling, instead, are not associated with this task but they are predicted by phonological tasks. Consistently, surface and phonological dyslexics show opposite profiles on lexical learning and phonological tasks. The phonological dyslexics are more impaired on the phonological tasks, while the surface dyslexics are equally or more impaired on the lexical learning tasks. Finally, orthographic lexical learning explains more variation in spelling than in reading, and subtyping based on spelling returns more interpretable results than that based on reading. These results suggest that the quality of lexical representations is crucial to adult literacy skills. This is best measured by spelling and best predicted by a task of lexical learning. We hypothesize that lexical learning taps a uniquely human capacity to form new representations by recombining the units of a restricted set.

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The aim of this Interdisciplinary Higher Degrees project was the development of a high-speed method of photometrically testing vehicle headlamps, based on the use of image processing techniques, for Lucas Electrical Limited. Photometric testing involves measuring the illuminance produced by a lamp at certain points in its beam distribution. Headlamp performance is best represented by an iso-lux diagram, showing illuminance contours, produced from a two-dimensional array of data. Conventionally, the tens of thousands of measurements required are made using a single stationary photodetector and a two-dimensional mechanical scanning system which enables a lamp's horizontal and vertical orientation relative to the photodetector to be changed. Even using motorised scanning and computerised data-logging, the data acquisition time for a typical iso-lux test is about twenty minutes. A detailed study was made of the concept of using a video camera and a digital image processing system to scan and measure a lamp's beam without the need for the time-consuming mechanical movement. Although the concept was shown to be theoretically feasible, and a prototype system designed, it could not be implemented because of the technical limitations of commercially-available equipment. An alternative high-speed approach was developed, however, and a second prototype syqtem designed. The proposed arrangement again uses an image processing system, but in conjunction with a one-dimensional array of photodetectors and a one-dimensional mechanical scanning system in place of a video camera. This system can be implemented using commercially-available equipment and, although not entirely eliminating the need for mechanical movement, greatly reduces the amount required, resulting in a predicted data acquisiton time of about twenty seconds for a typical iso-lux test. As a consequence of the work undertaken, the company initiated an 80,000 programme to implement the system proposed by the author.

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Multi-agent systems are complex systems comprised of multiple intelligent agents that act either independently or in cooperation with one another. Agent-based modelling is a method for studying complex systems like economies, societies, ecologies etc. Due to their complexity, very often mathematical analysis is limited in its ability to analyse such systems. In this case, agent-based modelling offers a practical, constructive method of analysis. The objective of this book is to shed light on some emergent properties of multi-agent systems. The authors focus their investigation on the effect of knowledge exchange on the convergence of complex, multi-agent systems.

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Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

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Purpose: To compare graticule and image capture assessment of the lower tear film meniscus height (TMH). Methods: Lower tear film meniscus height measures were taken in the right eyes of 55 healthy subjects at two study visits separated by 6 months. Two images of the TMH were captured in each subject with a digital camera attached to a slit-lamp biomicroscope and stored in a computer for future analysis. Using the best of two images, the TMH was quantified by manually drawing a line across the tear meniscus profile, following which the TMH was measured in pixels and converted into millimetres, where one pixel corresponded to 0.0018 mm. Additionally, graticule measures were carried out by direct observation using a calibrated graticule inserted into the same slit-lamp eyepiece. The graticule was calibrated so that actual readings, in 0.03 mm increments, could be made with a 40× ocular. Results: Smaller values of TMH were found in this study compared to previous studies. TMH, as measured with the image capture technique (0.13 ± 0.04 mm), was significantly greater (by approximately 0.01 ± 0.05 mm, p = 0.03) than that measured with the graticule technique (0.12 ± 0.05 mm). No bias was found across the range sampled. Repeatability of the TMH measurements taken at two study visits showed that graticule measures were significantly different (0.02 ± 0.05 mm, p = 0.01) and highly correlated (r = 0.52, p < 0.0001), whereas image capture measures were similar (0.01 ± 0.03 mm, p = 0.16), and also highly correlated (r = 0.56, p < 0.0001). Conclusions: Although graticule and image analysis techniques showed similar mean values for TMH, the image capture technique was more repeatable than the graticule technique and this can be attributed to the higher measurement resolution of the image capture (i.e. 0.0018 mm) compared to the graticule technique (i.e. 0.03 mm). © 2006 British Contact Lens Association.

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The aging responses of 2124 Al-SiC p metal matrix composite (MMC) and unreinforced matrix alloy are studied and related to variations in tensile properties. The MMC is aged from Wo starting conditions: (i) stretched and naturally aged and (ii) re-solution treated. Accelerated aging occurs in both MMC conditions compared with unreinforced alloy. Tensile strengths and elastic moduli are improved in the MMC compared with the alloy, but ductility is reduced. Stretched MMC exhibits higher strength but lower ductility and modulus than re-solutioned MMC. The re-solutioned MMC fails by microvoid coalescence in low aging conditions, and by void nucleation and shear in high aging conditions. Failure of the stretched MMC initiates at the surface at specimen shoulders, illustrating the increased notch sensitivity of this condition, and propagates via a zigzag shear fracture mode. Zigzag facet size increases on gross aging. Particle fracture occurs during tensile failure, but also before testing as a result of the manufacturing process. © 1995 The Institute of Materials.

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We compare two methods in order to predict inflation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture is evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

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This paper compares two methods to predict in°ation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture are evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

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A student-centred approach to teaching has been conceptualized as a key driver in higher education to facilitate understanding of concepts and improve attainment. The occurrence of student study team behaviours is diagnostic of this approach to teaching. However, the extent to which team behaviours are performed outside the parameters of formal teacher-learner environments remains under-researched. This is problematic as it is unclear whether study teams are maintained outside the confines of lectures, and the extent to which they impact on individual student grades. A naturalistic observational study was carried out that utilized short message text service communication as a means to record the frequency of team behaviours within informal environments. The findings suggest the frequency of team behaviours: 1) were positively associated with student grades; 2) increased after lectures independently rated as low in employing a student-centred focus; and 3) were facilitated by students' trait emotional intelligence.

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In this report we summarize the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiments with machine-learning classifiers, the observation is made that existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we made a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although language dependent features are incorporated in all levels of the speech signal and play as a strong discriminative function in human perception. Based on several results in related domains, we have suggested that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and the use of additional information from visual (expression) features.

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In this report we will explain some earlier papers [1, 2] which are about definition of Artificial Intelligence and about perfect AI. The definition of AI is intuitive in [1] and formal in [2]. The perfect AI is a program that satisfies the definition for AI but which is absolutely useless because of the combinatory explosion. Most people do not understand these papers because they never saw AI and that is why for them the notion of AI is too abstract. In this report we will make parallel between definition of chess playing program and definition of AI. Of course, the definition of chess playing program is useless because people already know what this is. Anyway, we will give you this definition because its construction follows closely the construction of the definition of AI. Also the results are almost the same with the only difference that we can optimise the perfect chess playing program in order to obtain a real chess playing program, but for the moment we cannot optimise the perfect AI in order to obtain a real AI. In this report we will not speak about AI. The only matter which we will observe will be about chess playing programs. If you understand the construction and the results about chess playing programs then you can read the papers [1, 2] and to see similar results about AI.