901 resultados para Cognitive approach


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In this paper, we present a machine learning approach for subject independent human action recognition using depth camera, emphasizing the importance of depth in recognition of actions. The proposed approach uses the flow information of all 3 dimensions to classify an action. In our approach, we have obtained the 2-D optical flow and used it along with the depth image to obtain the depth flow (Z motion vectors). The obtained flow captures the dynamics of the actions in space time. Feature vectors are obtained by averaging the 3-D motion over a grid laid over the silhouette in a hierarchical fashion. These hierarchical fine to coarse windows capture the motion dynamics of the object at various scales. The extracted features are used to train a Meta-cognitive Radial Basis Function Network (McRBFN) that uses a Projection Based Learning (PBL) algorithm, referred to as PBL-McRBFN, henceforth. PBL-McRBFN begins with zero hidden neurons and builds the network based on the best human learning strategy, namely, self-regulated learning in a meta-cognitive environment. When a sample is used for learning, PBLMcRBFN uses the sample overlapping conditions, and a projection based learning algorithm to estimate the parameters of the network. The performance of PBL-McRBFN is compared to that of a Support Vector Machine (SVM) and Extreme Learning Machine (ELM) classifiers with representation of every person and action in the training and testing datasets. Performance study shows that PBL-McRBFN outperforms these classifiers in recognizing actions in 3-D. Further, a subject-independent study is conducted by leave-one-subject-out strategy and its generalization performance is tested. It is observed from the subject-independent study that McRBFN is capable of generalizing actions accurately. The performance of the proposed approach is benchmarked with Video Analytics Lab (VAL) dataset and Berkeley Multimodal Human Action Database (MHAD). (C) 2013 Elsevier Ltd. All rights reserved.

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Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.

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We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.

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In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

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This paper takes a new look at an old question: what is the human self? It offers a proposal for theorizing the self from an enactive perspective as an autonomous system that is constituted through interpersonal relations. It addresses a prevalent issue in the philosophy of cognitive science: the body-social problem. Embodied and social approaches to cognitive identity are in mutual tension. On the one hand, embodied cognitive science risks a new form of methodological individualism, implying a dichotomy not between the outside world of objects and the brain-bound individual but rather between body-bound individuals and the outside social world. On the other hand, approaches that emphasize the constitutive relevance of social interaction processes for cognitive identity run the risk of losing the individual in the interaction dynamics and of downplaying the role of embodiment. This paper adopts a middle way and outlines an enactive approach to individuation that is neither individualistic nor disembodied but integrates both approaches. Elaborating on Jonas' notion of needful freedom it outlines an enactive proposal to understanding the self as co-generated in interactions and relations with others. I argue that the human self is a social existence that is organized in terms of a back and forth between social distinction and participation processes. On this view, the body, rather than being identical with the social self, becomes its mediator

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This thesis investigates the optimisation of Coarse-Fine (CF) spectrum sensing architectures under a distribution of SNRs for Dynamic Spectrum Access (DSA). Three different detector architectures are investigated: the Coarse-Sorting Fine Detector (CSFD), the Coarse-Deciding Fine Detector (CDFD) and the Hybrid Coarse-Fine Detector (HCFD). To date, the majority of the work on coarse-fine spectrum sensing for cognitive radio has focused on a single value for the SNR. This approach overlooks the key advantage that CF sensing has to offer, namely that high powered signals can be easily detected without extra signal processing. By considering a range of SNR values, the detector can be optimised more effectively and greater performance gains realised. This work considers the optimisation of CF spectrum sensing schemes where the security and performance are treated separately. Instead of optimising system performance at a single, constant, low SNR value, the system instead is optimised for the average operating conditions. The security is still provided such that at the low SNR values the safety specifications are met. By decoupling the security and performance, the system’s average performance increases whilst maintaining the protection of licensed users from harmful interference. The different architectures considered in this thesis are investigated in theory, simulation and physical implementation to provide a complete overview of the performance of each system. This thesis provides a method for estimating SNR distributions which is quick, accurate and relatively low cost. The CSFD is modelled and the characteristic equations are found for the CDFD scheme. The HCFD is introduced and optimisation schemes for all three architectures are proposed. Finally, using the Implementing Radio In Software (IRIS) test-bed to confirm simulation results, CF spectrum sensing is shown to be significantly quicker than naive methods, whilst still meeting the required interference probability rates and not requiring substantial receiver complexity increases.

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The past two decades have seen substantial gains in our understanding of the complex processes underlying disturbed brain-gut communication in disorders such as irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). Despite a growing understanding of the neurobiology of brain-gut axis dysfunction, there is a relative paucity of investigations into how the various factors involved in dysregulating the brain-gut axis, including stress, immune activation and pain, could impact on fundamental brain processes such as cognitive performance. To this end, we proposed a cognitive neurobiology of brain-gut axis dysfunction and took a novel approach to examine how disturbed brain-gut interactions may manifest as altered cognitive performance in IBS and IBD, both cross-sectionally and prospectively. We have demonstrated that, disorders of the brain-gut axis are characterised by stable deficits in specific cognitive domains. Specifically, patients with IBS exhibit a consistent hippocampal mediated visuospatial memory impairment. In addition we have found evidence to suggest a similar visuospatial impairment in IBD. However, our most consistent finding within this population was that patients with Crohn’s disease exhibit impaired selective attention/ response inhibition on the classic Stroop interference test. These cognitive deficits may serve to perpetuate and sustain brain-gut axis dysfunction. Furthermore, this research has shed light on some of the underlying neurobiological mechanisms that may be mediating cognitive dysfunction in IBS. Our findings may have significant implications for the individual who suffers from a brain-gut axis disorder and may also inform future treatment strategies. Taken together, these findings can be incorporated into existing neurobiological models of brain-gut axis dysfunction, to develop a more comprehensive model accounting for the cognitive-neurobiology of brain-gut axis disorders. This has furthered our understanding of disease pathophysiology and may ultimately aid in both the diagnosis and treatment of these highly prevalent, but poorly understood disorders.

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BACKGROUND: Hypertension and cognitive impairment are prevalent in older people. It is known that hypertension is a direct risk factor for vascular dementia and recent studies have suggested hypertension also impacts upon prevalence of Alzheimer's disease. The question is therefore whether treatment of hypertension lowers the rate of cognitive decline. OBJECTIVES: To assess the effects of blood pressure lowering treatments for the prevention of dementia and cognitive decline in patients with hypertension but no history of cerebrovascular disease. SEARCH STRATEGY: The trials were identified through a search of CDCIG's Specialised Register, CENTRAL, MEDLINE, EMBASE, PsycINFO and CINAHL on 27 April 2005. SELECTION CRITERIA: Randomized, double-blind, placebo controlled trials in which pharmacological or non-pharmacological interventions to lower blood pressure were given for at least six months. DATA COLLECTION AND ANALYSIS: Two independent reviewers assessed trial quality and extracted data. The following outcomes were assessed: incidence of dementia, cognitive change from baseline, blood pressure level, incidence and severity of side effects and quality of life. MAIN RESULTS: Three trials including 12,091 hypertensive subjects were identified. Average age was 72.8 years. Participants were recruited from industrialised countries. Mean blood pressure at entry across the studies was 170/84 mmHg. All trials instituted a stepped care approach to hypertension treatment, starting with a calcium-channel blocker, a diuretic or an angiotensin receptor blocker. The combined result of the three trials reporting incidence of dementia indicated no significant difference between treatment and placebo (Odds Ratio (OR) = 0.89, 95% CI 0.69, 1.16). Blood pressure reduction resulted in a 11% relative risk reduction of dementia in patients with no prior cerebrovascular disease but this effect was not statistically significant (p = 0.38) and there was considerable heterogeneity between the trials. The combined results from the two trials reporting change in Mini Mental State Examination (MMSE) did not indicate a benefit from treatment (Weighted Mean Difference (WMD) = 0.10, 95% CI -0.03, 0.23). Both systolic and diastolic blood pressure levels were reduced significantly in the two trials assessing this outcome (WMD = -7.53, 95% CI -8.28, -6.77 for systolic blood pressure, WMD = -3.87, 95% CI -4.25, -3.50 for diastolic blood pressure).Two trials reported adverse effects requiring discontinuation of treatment and the combined results indicated a significant benefit from placebo (OR = 1.18, 95% CI 1.06, 1.30). When analysed separately, however, more patients on placebo in SCOPE were likely to discontinue treatment due to side effects; the converse was true in SHEP 1991. Quality of life data could not be analysed in the three studies. There was difficulty with the control group in this review as many of the control subjects received antihypertensive treatment because their blood pressures exceeded pre-set values. In most cases the study became a comparison between the study drug against a usual antihypertensive regimen. AUTHORS' CONCLUSIONS: There was no convincing evidence from the trials identified that blood pressure lowering prevents the development of dementia or cognitive impairment in hypertensive patients with no apparent prior cerebrovascular disease. There were significant problems identified with analysing the data, however, due to the number of patients lost to follow-up and the number of placebo patients given active treatment. This introduced bias. More robust results may be obtained by analysing one year data to reduce differential drop-out or by conducting a meta-analysis using individual patient data.

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Patients with schizophrenia display numerous cognitive deficits, including problems in working memory, time estimation, and absolute identification of stimuli. Research in these fields has traditionally been conducted independently. We examined these cognitive processes using tasks that are structurally similar and that yield rich error data. Relative to healthy control participants (n = 20), patients with schizophrenia (n = 20) were impaired on a duration identification task and a probed-recall memory task but not on a line-length identification task. These findings do not support the notion of a global impairment in absolute identification in schizophrenia. However, the authors suggest that some aspect of temporal information processing is indeed disturbed in schizophrenia.

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The Convention on the Rights of the Child (CRC, 1989) is currently the most ratified international treaty. Several authors have highlighted its potential for both a moral education and citizenship. However, paradoxically, different studies report its limited or occasional incorporation into school practices. This article explores experiences of participation in schools,the third P of the CRC, from the plurality of voices and actors of the educational community,by means of 14 discussion groups in 11 autonomous communities in Spain. Discourse analysis evidence low levels of student participation in school life. But, at the same time, a favorable educational environment for the development of projects that contribute to child participation is found, as well as for the incorporation of the CRC as a mover and a referential integrator of the different schools projects. However, it is also an educational background conductive to projects for its development, such as the incorporation of the CRC as a referential integrator of the schools projects.

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In his provocative article, F. Mechsner (2004) advances the thesis that human voluntary movements are subject to "psychological" or "perceptual -cognitive" control and are thus organized "without regard to efferent patterns" (p. 355). Rather than considering in detail the experiments that he proffered by way of support, the present author discusses the degree to which that supposition has appeal on the grounds of simplicity and is defined in terms that are compatible with a unified science.

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The association fiber tracts integrity of the inter-hemispheric and within-hemispheric communication was poor understood in amnestic type mild cognitive impairment (aMCI) patients by diffusion tensor imaging (DTI). A region of interest-based DTI approach was applied to explore fiber tract differences between 22 aMCI patients and 22 well-matched normal aging. Correlations were also sought between fractional anisotropy (FA) values and the cognitive performance scores in the aMCI patients. Extensive impairment of association fiber tracts integrity was observed in aMCI patients, including bilateral inferior fronto-occipital fascicles, the genu of corpus callosum, bilateral cingulate bundles and bilateral superior longitudinal fascicles II (SLE II) subcomponent. In addition, the FA value of right SLE II was significantly negatively correlated to the performance of Trail Making Test A and B, whilst the values of right posterior cingulate bundle was significantly positive correlation with MMSE score. As aMCI is a putative prodromal syndrome to Alzheimer's disease (AD), this study suggested that investigation of association fiber tracts between remote cortexes may yield important new data to predict whether a patient will eventually develop AD.

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Hippocampus displayed progressively gender-associated damage in Alzheimer's disease. However, gender effects have been largely neglected in studies of amnestic type mild cognitive impairment (aMCI) patients who were believed to represent an early stage of this disease. The goal of this study was to use in vivo neuroimaging techniques to determine whether there were any evidences of gender differences in hippocampal atrophy in aMCI. A region of interest-based magnetic resonance imaging approach was used to compare hippocampal volume between aMCI patients (22 male, 17 female) and normal aging controls (12 male, 11 female). Independent of group, male hippocampal volumes were larger than female volumes and right hippocampal volumes were typically smaller than left volumes. Hippocampal volumes were significantly reduced in the clinical group but no gender differences were noted in terms of degree of atrophy present. However, female patients showed more impaired cognitive function than male patients despite this apparent equivalence in atrophy. The absence of a gender difference suggested that early neuropathological progression might be independent of gender. However, the data also suggested female aMCI patients had an increased vulnerability to cognitive impairment earlier in the illness course.