998 resultados para Invariant patterns
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Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.
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Stereotypies are repetitive and relatively invariant patterns of behavior, which are observed in a wide range of species in captivity. Stereotypic behavior occurs when environmental demands produce a physiological response that, if sustained for an extended period, exceeds the natural physiological regulatory capacity of the organism, particularly in situations that include unpredictability and uncontrollability. One hypothesis is that stereotypic behavior functions to cope with stressful environments, but the existing evidence is contradictory. To address the coping hypothesis of stereotypies, we triggered physiological reactions in 22 horses affected by stereotypic behavior (crib-biters) and 21 non-crib-biters (controls), using an ACTH challenge test. Following administration of an ACTH injection, we measured saliva cortisol every 30min and heart rate (HR) continuously for a period of 3h. We did not find any differences in HR or HR variability between the two groups, but crib-biters (Group CB) had significantly higher cortisol responses than controls (Group C; mean±SD: CB, 5.84±2.62ng/ml, C, 4.76±3.04ng/ml). Moreover, crib-biters that did not perform the stereotypic behavior during the 3-hour test period (Group B) had significantly higher cortisol levels than controls, which was not the case of crib-biters showing stereotypic behavior (Group A) (B, 6.44±2.38ng/ml A, 5.58±2.69ng/ml). Our results suggest that crib-biting is a coping strategy that helps stereotypic individuals to reduce cortisol levels caused by stressful situations. We conclude that preventing stereotypic horses from crib-biting could be an inappropriate strategy to control this abnormal behavior, as it prevents individuals from coping with situations that they perceive as stressful.
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In previous empirical and modelling studies of rare species and weeds, evidence of fractal behaviour has been found. We propose that weeds in modern agricultural systems may be managed close to critical population dynamic thresholds, below which their rates of increase will be negative and where scale-invariance may be expected as a consequence. We collected detailed spatial data on five contrasting species over a period of three years in a primarily arable field. Counts in 20×20 cm contiguous quadrats, 225,000 in 1998 and 84,375 thereafter, could be re-structured into a wide range of larger quadrat sizes. These were analysed using three methods based on correlation sum, incidence and conditional incidence. We found non-trivial scale invariance for species occurring at low mean densities and where they were strongly aggregated. The fact that the scale-invariance was not found for widespread species occurring at higher densities suggests that the scaling in agricultural weed populations may, indeed, be related to critical phenomena.
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Template matching is a technique widely used for finding patterns in digital images. A good template matching should be able to detect template instances that have undergone geometric transformations. In this paper, we proposed a grayscale template matching algorithm named Ciratefi, invariant to rotation, scale, translation, brightness and contrast and its extension to color images. We introduce CSSIM (color structural similarity) for comparing the similarity of two color image patches and use it in our algorithm. We also describe a scheme to determine automatically the appropriate parameters of our algorithm and use pyramidal structure to improve the scale invariance. We conducted several experiments to compare grayscale and color Ciratefis with SIFT, C-color-SIFT and EasyMatch algorithms in many different situations. The results attest that grayscale and color Ciratefis are more accurate than the compared algorithms and that color-Ciratefi outperforms grayscale Ciratefi most of the time. However, Ciratefi is slower than the other algorithms.
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Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented
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Models which define fitness in terms of per capita rate of increase of phenotypes are used to analyse patterns of individual growth. It is shown that sigmoid growth curves are an optimal strategy (i.e. maximize fitness) if (Assumption 1a) mortality decreases with body size; (2a) mortality is a convex function of specific growth rate, viewed from above; (3) there is a constraint on growth rate, which is attained in the first phase of growth. If the constraint is not attained then size should increase at a progressively reducing rate. These predictions are biologically plausible. Catch-up growth, for retarded individuals, is generally not an optimal strategy though in special cases (e.g. seasonal breeding) it might be. Growth may be advantageous after first breeding if birth rate is a convex function of G (the fraction of production devoted to growth) viewed from above (Assumption 5a), or if mortality rate is a convex function of G, viewed from above (Assumption 6c). If assumptions 5a and 6c are both false, growth should cease at the age of first reproduction. These predictions could be used to evaluate the incidence of indeterminate versus determinate growth in the animal kingdom though the data currently available do not allow quantitative tests. In animals with invariant adult size a method is given which allows one to calculate whether an increase in body size is favoured given that fecundity and developmental time are thereby increased.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In this paper, a modification for the high-order neural network (HONN) is presented. Third order networks are considered for achieving translation, rotation and scale invariant pattern recognition. They require however much storage and computation power for the task. The proposed modified HONN takes into account a priori knowledge of the binary patterns that have to be learned, achieving significant gain in computation time and memory requirements. This modification enables the efficient computation of HONNs for image fields of greater that 100 × 100 pixels without any loss of pattern information.
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Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^
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To characterize cumulative joint damage (CJD) patterns in rheumatoid arthritis (RA) and determine their associations with demographic/clinical features and HLA-DRB1 gene polymorphism. Hand and foot radiographs were obtained from 404 patients with RA. CJD patterns were determined by 3 derivations from Sharp/van der Heijde scores, obtained by the mathematical division of scores for hands/feet (Sharp-h/f score), fingers/wrists (Sharp-f/w score), and erosion/space narrowing (Sharp-e/sn score), respectively. DNA and serum were obtained for determination of HLA-DRB1 polymorphism, rheumatoid factor (RF), and anticitrullinated protein antibodies (ACPA). Patients with wrist-dominant CJD pattern were more likely to have severe RA than those with finger-dominant pattern (68.4% vs 46.0%; p = 0.036) as were those with foot-dominant vs hand-dominant CJD pattern (76.5% vs 56.4%; p = 0.044). HLA-DRB1 shared epitope (SE) alleles were associated with erosion-dominant CJD pattern (p = 0.021). Patients with erosion-dominant CJD pattern had higher levels of RF and ACPA than those with space-narrowing-dominant CJD pattern (median RF 71.35 U/ml vs 22.05 U/ml, respectively; p = 0.003; median ACPA 187.9 U/ml vs 143.2 U/ml, respectively; p < 0.001). The majority of triple-positive patients (SE+, RF+, ACPA+) had erosion-dominant CJD pattern (62.3%) while the majority of triple-negative patients (SE-, FR-, ACPA-) had space narrowing-dominant CJD pattern (75%; p = 0.017). ACPA was associated with HLA-DRB1 SE alleles (p < 0.05). Patients with foot-dominant CJD pattern were taller than those with hand-dominant CJD pattern (p = 0.002); those with erosion-dominant CJD pattern had higher weight and body mass index than those with space narrowing-dominant CJD pattern (p = 0.014, p = 0.001). CJD patterns were associated with disease severity, HLA-DRB1 SE status, presence and titer of ACPA and RF, and morphometric features.
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Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the (15)N:(14)N ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in (15)N than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.8°C, soil δ(15)N was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soil δ(15)N showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.
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Trees from tropical montane cloud forest (TMCF) display very dynamic patterns of water use. They are capable of downwards water transport towards the soil during leaf-wetting events, likely a consequence of foliar water uptake (FWU), as well as high rates of night-time transpiration (Enight) during drier nights. These two processes might represent important sources of water losses and gains to the plant, but little is known about the environmental factors controlling these water fluxes. We evaluated how contrasting atmospheric and soil water conditions control diurnal, nocturnal and seasonal dynamics of sap flow in Drimys brasiliensis (Miers), a common Neotropical cloud forest species. We monitored the seasonal variation of soil water content, micrometeorological conditions and sap flow of D. brasiliensis trees in the field during wet and dry seasons. We also conducted a greenhouse experiment exposing D. brasiliensis saplings under contrasting soil water conditions to deuterium-labelled fog water. We found that during the night D. brasiliensis possesses heightened stomatal sensitivity to soil drought and vapour pressure deficit, which reduces night-time water loss. Leaf-wetting events had a strong suppressive effect on tree transpiration (E). Foliar water uptake increased in magnitude with drier soil and during longer leaf-wetting events. The difference between diurnal and nocturnal stomatal behaviour in D. brasiliensis could be attributed to an optimization of carbon gain when leaves are dry, as well as minimization of nocturnal water loss. The leaf-wetting events on the other hand seem important to D. brasiliensis water balance, especially during soil droughts, both by suppressing tree transpiration (E) and as a small additional water supply through FWU. Our results suggest that decreases in leaf-wetting events in TMCF might increase D. brasiliensis water loss and decrease its water gains, which could compromise its ecophysiological performance and survival during dry periods.
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Objective Patients with mesial temporal lobe epilepsy (MTLE) may present unstable pattern of seizures. We aimed to evaluate the occurrence of relapse-remitting seizures in MTLE with (MTLE-HS) and without (MTLE-NL) hippocampal sclerosis. Method We evaluated 172 patients with MTLE-HS (122) or MTLE-NL (50). Relapse-remitting pattern was defined as periods longer than two years of seizure-freedom intercalated with seizure recurrence. Infrequent seizures was considered as up to three seizures per year and frequent seizures as any period of seizures higher than that. Results Thirty-seven (30%) MTLE-HS and 18 (36%) MTLE-NL patients had relapse-remitting pattern (X2, p = 0.470). This was more common in those with infrequent seizures (X2, p < 0.001). Twelve MTLE-HS and one MTLE-NL patients had prolonged seizure remission between the first and second decade of life (X2, p = 0.06). Conclusion Similar proportion of MTLE-HS or MTLE-NL patients present relapse-remitting seizures and this occurs more often in those with infrequent seizures.
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OBJECTIVE: Nutritional, immunological and psychological benefts of exclusive breastfeeding for the frst 6 months of life are unequivocally recognized. However, mothers should also be aware of the importance of breastfeeding for promoting adequate oral development. This study evaluated the association between breastfeeding and non-nutritive sucking patterns and the prevalence of anterior open bite in primary dentition. MATERIAL AND METHODS: Infant feeding and non-nutritive sucking were investigated in a 3-6 year-old sample of 1,377 children, from São Paulo city, Brazil. Children were grouped according to breastfeeding duration: G1 - non-breastfed, G2 - shorter than 6 months, G3 - interruption between 6 and 12 months, and G4 - longer than 12 months. Three calibrated dentists performed clinical examinations and classifed overbite into 3 categories: normal, anterior open bite and deep bite. Chi-square tests (p<0.05) with odds ratio (OR) calculation were used for intergroup comparisons. The impact of breastfeeding and non-nutritive sucking on the prevalence of anterior open bite was analyzed using binary logistic regression. RESULTS: The prevalence estimates of anterior open bite were: 31.9% (G1), 26.1% (G2), 22.1% (G3), and 6.2% (G4). G1 would have signifcantly more chances of having anterior open bite compared with G4; in the total sample (OR=7.1) and in the subgroup without history of non-nutritive sucking (OR=9.3). Prolonging breastfeeding for 12 months was associated with a 3.7 times lower chance of having anterior open bite. In each year of persistence with non-nutritive sucking habits, the chance of developing this malocclusion increased in 2.38 times. CONCLUSIONS: Breastfeeding and non-nutritive sucking durations demonstrated opposite effects on the prediction of anterior open bite. Non-breastfed children presented signifcantly greater chances of having anterior open bite compared with those who were breastfed for periods longer than 12 months, demonstrating the benefcial infuence of breastfeeding on dental occlusion.
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The aim of this work was to determine PAs levels in pith tissues and callus cultures from haploid and diploid tobacco plants, explanted from the apical and basal regions of the stem. These explants were cultured in an RM-64 medium supplied with IAA and kinetin, under light or in the dark, during successive subcultures. PAs levels followed a basipetal decrease in diploid and an increase in haploid, pith tissues. A similar pattern of total PAs (free + conjugated) was observed for the callus of diploid and haploid plants maintained in the light, and for the haploid callus in the dark, whereas the diploid callus in the dark showed a constant increase in total PAs levels until the end of culture. The PA increase in the diploid callus in the dark was related to free Put levels increase. The ploidy status of the plants could express different PA gradients together with the plant pith and in vitro callus cultures.