51 resultados para Coarse-to-fine processing


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Whole fresh goat's milk was heat treated at 135 degrees C for 4 s using a miniature UHT plant. The temperature of the milk in the preheating and sterilizer sections, and the milk flow rate were monitored to evaluate the overall heat transfer coefficient (OHTC). The decrease in OHTC was used to estimate the extent of fouling. Goat's milk fouled very quickly and run times of the UHT plant were short. The use of sodium hexametaphosphate, trisodium citrate and cation exchange resins to reduce ionic calcium prior to UHT processing, increased the pH and alcohol stability of the milk and markedly increased the run time of the UHT plant.

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The aim of this review is to illustrate how physical properties are important to food processing and quality. Three food products, flakes, porridge and bread, in addition to oat groats are used to show the influence of water and heat-treatments on the mechanical properties. The hydrothermal history of ingredients is shown to affect product quality. Water acts as a plasticiser and solvent in these foods, whilst heat modifies the conformation and interactions of macromolecular components. Structure as well as chemical composition is shown to govern texture.

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The study examined: (a) the role of phonological, grammatical, and rapid automatized naming (RAN) skills in reading and spelling development; and (b) the component processes of early narrative writing skills. Fifty-seven Turkish-speaking children were followed from Grade 1 to Grade 2. RAN was the most powerful longitudinal predictor of reading speed and its effect was evident even when previous reading skills were taken into account. Broadly, the phonological and grammatical skills made reliable contributions to spelling performance but their effects were completely mediated by previous spelling skills. Different aspects of the narrative writing skills were related to different processing skills. While handwriting speed predicted writing fluency, spelling accuracy predicted spelling error rate. Vocabulary and working memory were the only reliable longitudinal predictors of the quality of composition content. The overall model, however, failed to explain any reliable variance in the structural quality of the compositions

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A novel partitioned least squares (PLS) algorithm is presented, in which estimates from several simple system models are combined by means of a Bayesian methodology of pooling partial knowledge. The method has the added advantage that, when the simple models are of a similar structure, it lends itself directly to parallel processing procedures, thereby speeding up the entire parameter estimation process by several factors.

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Previous research has indicated a potential discontinuity between monkey and human ventral premotor-parietal mirror systems, namely that monkey mirror systems process only transitive (object-directed) actions, whereas human mirror systems may also process intransitive (non-object-directed) actions. The present study investigated this discontinuity by seeking evidence of automatic imitation of intransitive actions—hand opening and closing—in humans using a simple reaction time (RT), stimulus–response compatibility paradigm. Left–right and up–down spatial compatibility were controlled by ensuring that stimuli were presented and responses executed in orthogonal planes, and automatic imitation was isolated from simple and complex orthogonal spatial compatibility by varying the anatomical identity of the stimulus hand and response hemispace, respectively. In all conditions, action compatible responding was faster than action incompatible responding, and no effects of spatial compatibility were observed. This experiment therefore provides evidence of automatic imitation of intransitive actions, and support for the hypothesis that human and monkey mirror systems differ with respect to the processing of intransitive actions.

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The application of automatic segmentation methods in lesion detection is desirable. However, such methods are restricted by intensity similarities between lesioned and healthy brain tissue. Using multi-spectral magnetic resonance imaging (MRI) modalities may overcome this problem but it is not always practicable. In this article, a lesion detection approach requiring a single MRI modality is presented, which is an improved method based on a recent publication. This new method assumes that a low similarity should be found in the regions of lesions when the likeness between an intensity based fuzzy segmentation and a location based tissue probabilities is measured. The usage of a normalized similarity measurement enables the current method to fine-tune the threshold for lesion detection, thus maximizing the possibility of reaching high detection accuracy. Importantly, an extra cleaning step is included in the current approach which removes enlarged ventricles from detected lesions. The performance investigation using simulated lesions demonstrated that not only the majority of lesions were well detected but also normal tissues were identified effectively. Tests on images acquired in stroke patients further confirmed the strength of the method in lesion detection. When compared with the previous version, the current approach showed a higher sensitivity in detecting small lesions and had less false positives around the ventricle and the edge of the brain

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This paper presents a completely new design of a bogie-frame made of glass fibre reinforced composites and its performance under various loading conditions predicted by finite element analysis. The bogie consists of two frames, with one placed on top of the other, and two axle ties connecting the axles. Each frame consists of two side arms and a transom between. The top frame is thinner and more compliant and has a higher curvature compared with the bottom frame. Variable vertical stiffness can be achieved before and after the contact between the two frames at the central section of the bogie to cope with different load levels. Finite element analysis played a very important role in the design of this structure. Stiffness and stress levels of the full scale bogie presented in this paper under various loading conditions have been predicted by using Marc provided by MSC Software. In order to verify the finite element analysis (FEA) models, a fifth scale prototype of the bogie has been made and tested under quasi-static loading conditions. Results of testing on the fifth scale bogie have been used to fine tune details like contact and friction in the fifth scale FEA models. These conditions were then applied to the full scale models. Finite element analysis results show that the stress levels in all directions are low compared with material strengths.

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A number of critiques have been published drawing attention to the gaps in research methods applied to issues surrounding homelessness and service utilisation in Britain. This paper discusses the use of social identity, a theory drawn from the field of applied social psychology, and synthesises it with the pathways model, thereby providing a framework to further explore service utilisation. The synthesised framework was used to predict the uptake of outreach services in a prospective study of 121 homeless people in a major UK city. In general, homeless people's use of intervention services was affected by the extent to which they identified with the support services themselves. The study demonstrates the central role of social identity in understanding service utilisation patterns, and shows the importance of applying fresh techniques to fine-tune our understanding of uptake in the long term.

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Objective: This work investigates the nature of the comprehension impairment in Wernicke’s aphasia, by examining the relationship between deficits in auditory processing of fundamental, non-verbal acoustic stimuli and auditory comprehension. Wernicke’s aphasia, a condition resulting in severely disrupted auditory comprehension, primarily occurs following a cerebrovascular accident (CVA) to the left temporo-parietal cortex. Whilst damage to posterior superior temporal areas is associated with auditory linguistic comprehension impairments, functional imaging indicates that these areas may not be specific to speech processing but part of a network for generic auditory analysis. Methods: We examined analysis of basic acoustic stimuli in Wernicke’s aphasia participants (n = 10) using auditory stimuli reflective of theories of cortical auditory processing and of speech cues. Auditory spectral, temporal and spectro-temporal analysis was assessed using pure tone frequency discrimination, frequency modulation (FM) detection and the detection of dynamic modulation (DM) in “moving ripple” stimuli. All tasks used criterion-free, adaptive measures of threshold to ensure reliable results at the individual level. Results: Participants with Wernicke’s aphasia showed normal frequency discrimination but significant impairments in FM and DM detection, relative to age- and hearing-matched controls at the group level (n = 10). At the individual level, there was considerable variation in performance, and thresholds for both frequency and dynamic modulation detection correlated significantly with auditory comprehension abilities in the Wernicke’s aphasia participants. Conclusion: These results demonstrate the co-occurrence of a deficit in fundamental auditory processing of temporal and spectrotemporal nonverbal stimuli in Wernicke’s aphasia, which may have a causal contribution to the auditory language comprehension impairment Results are discussed in the context of traditional neuropsychology and current models of cortical auditory processing.

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In this paper, we will address the endeavors of three disciplines, Psychology, Neuroscience, and Artificial Neural Network (ANN) modeling, in explaining how the mind perceives and attends information. More precisely, we will shed some light on the efforts to understand the allocation of attentional resources to the processing of emotional stimuli. This review aims at informing the three disciplines about converging points of their research and to provide a starting point for discussion.

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This article argues that a native-speaker baseline is a neglected dimension of studies into second language (L2) performance. If we investigate how learners perform language tasks, we should distinguish what performance features are due to their processing an L2 and which are due to their performing a particular task. Having defined what we mean by “native speaker,” we present the background to a research study into task features on nonnative task performance, designed to include native-speaker data as a baseline for interpreting nonnative-speaker performance. The nonnative results, published in this journal (Tavakoli & Foster, 2008) are recapitulated and then the native-speaker results are presented and discussed in the light of them. The study is guided by the assumption that limited attentional resources impact on L2 performance and explores how narrative design features—namely complexity of storyline and tightness of narrative structure— affect complexity, fluency, accuracy, and lexical diversity in language. The results show that both native and nonnative speakers are prompted by storyline complexity to use more subordinated language, but narrative structure had different effects on native and nonnative fluency. The learners, who were based in either London or Tehran, did not differ in their performance when compared to each other, except in lexical diversity, where the learners in London were close to native-speaker levels. The implications of the results for the applicability of Levelt’s model of speaking to an L2 are discussed, as is the potential for further L2 research using native speakers as a baseline.

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The functional networks of cultured neurons exhibit complex network properties similar to those found in vivo. Starting from random seeding, cultures undergo significant reorganization during the initial period in vitro, yet despite providing an ideal platform for observing developmental changes in neuronal connectivity, little is known about how a complex functional network evolves from isolated neurons. In the present study, evolution of functional connectivity was estimated from correlations of spontaneous activity. Network properties were quantified using complex measures from graph theory and used to compare cultures at different stages of development during the first 5 weeks in vitro. Networks obtained from young cultures (14 days in vitro) exhibited a random topology, which evolved to a small-world topology during maturation. The topology change was accompanied by an increased presence of highly connected areas (hubs) and network efficiency increased with age. The small-world topology balances integration of network areas with segregation of specialized processing units. The emergence of such network structure in cultured neurons, despite a lack of external input, points to complex intrinsic biological mechanisms. Moreover, the functional network of cultures at mature ages is efficient and highly suited to complex processing tasks.

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In recent years, the importance of the corporate brand (e.g. P&G, Nestlé, Unilever) has grown significantly and companies increasingly strive to strengthen their corporate brand. One way to strengthen the corporate brand is portfolio advertisement, in which the corporate brand is presented alongside with several product brands of its portfolio (e.g. VW with its product brands Touareg, Touran, Golf and Polo). The aim of portfolio advertising is to generate a positive image spill-over effect from the product brands onto the corporate brand in order to enhance the consumers’ perceived competence of the corporate brand. In four experimental settings Christian Boris Brunner demonstrates the great potential of portfolio advertising and highlights the risks associated with portfolio advertising in practice. In a first experiment, he compares portfolio advertising with single brand advertisements. Moreover, in case of portfolio advertising he manipulates the fit between the product brands, because the consumer has to establish a logical coherence between the individual brands. However, asconsumers have limited capacity for processing information, special attention should be paid to the number of product brands and to the processing depth of the consumer during confrontation with portfolio advertising. These key factors are taken into consideration in a second extensive experiment involving fictitious corporate and product brands. The effects of portfolio advertising on a product brand are also examined. Furthermore, the strength of product brands, i.e. brand knowledge as well as brand image and consumer’s knowledge of the brands, must be taken into consideration. In a third experiment, both the brand strength of real product brands as well as the fit between product brands are manipulated. Portfolio advertising could also have a positive image spill-over effect when companies introduce a new product brand under the umbrella of the corporate brand while communicating all product brands together. Based on considerations, in a fourth experiment, Christian Boris Brunner shows that portfolio advertising could also have a positive image spill-over effect on a new (unknown) product brand. Concluding his work, Christian Boris Brunner provides implications for future research concerning portfolio advertising as well as the management of a corporate brand in complex brand architectures. Concerning practical implications, these four experiments underline a high relevance to marketing and brand managers, who could increase corporate and product brands’ potential by means of portfolio advertising.

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Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

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Recent studies suggest that learning and using a second language (L2) can affect brain structure, including the structure of white matter (WM) tracts. This observation comes from research looking at early and older bilingual individuals who have been using both their first and second languages on an everyday basis for many years. This study investigated whether young, highly immersed late bilinguals would also show structural effects in the WM that can be attributed to everyday L2 use, irrespective of critical periods or the length of L2 learning. Our Tract-Based Spatial Statistics analysis revealed higher fractional anisotropy values for bilinguals vs. monolinguals in several WM tracts that have been linked to language processing and in a pattern closely resembling the results reported for older and early bilinguals. We propose that learning and actively using an L2 after childhood can have rapid dynamic effects on WM structure, which in turn may assist in preserving WM integrity in older age.