Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

Contextual visual localization: cascaded submap classification, optimized saliency detection, and fast view matching

In this paper, we present a novel coarse-to-fine visual localization approach: contextual visual localization. This approach relies on three elements: (i) a minimal-complexity classifier for performing fast coarse localization (submap classification); (ii) an optimized saliency detector which exploits the visual statistics of the submap; and (iii) a fast view-matching algorithm which filters initial matchings with a structural criterion. The latter algorithm yields fine localization. Our experiments show that these elements have been successfully integrated for solving the global localization problem. Context, that is, the awareness of being in a particular submap, is defined by a supervised classifier tuned for a minimal set of features. Visual context is exploited both for tuning (optimizing) the saliency detection process, and to select potential matching views in the visual database, close enough to the query view.

Classification and contextual enhancement of remotely sensed data

The aims of the project were twofold: 1) To investigate classification procedures for remotely sensed digital data, in order to develop modifications to existing algorithms and propose novel classification procedures; and 2) To investigate and develop algorithms for contextual enhancement of classified imagery in order to increase classification accuracy. The following classifiers were examined: box, decision tree, minimum distance, maximum likelihood. In addition to these the following algorithms were developed during the course of the research: deviant distance, look up table and an automated decision tree classifier using expert systems technology. Clustering techniques for unsupervised classification were also investigated. Contextual enhancements investigated were: mode filters, small area replacement and Wharton's CONAN algorithm. Additionally methods for noise and edge based declassification and contextual reclassification, non-probabilitic relaxation and relaxation based on Markov chain theory were developed. The advantages of per-field classifiers and Geographical Information Systems were investigated. The conclusions presented suggest suitable combinations of classifier and contextual enhancement, given user accuracy requirements and time constraints. These were then tested for validity using a different data set. A brief examination of the utility of the recommended contextual algorithms for reducing the effects of data noise was also carried out.

Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

Padrão fundamental de movimento : uma analise universal ou contextual?

Universidade Estadual de Campinas . Faculdade de Educação Física

On the functional integration between postural and supra-postural tasks on the basis of contextual cues and task constraint

In order to evaluate the effects of uncertainty about direction of mechanical perturbation and supra-postural task constraint on postural control young adults had their upright stance perturbed while holding a tray in a horizontal position Stance was perturbed by moving forward or backward a supporting platform contrasting situations of certainty versus uncertainty of direction of displacement Increased constraint on postural stability was Imposed by a supra-postural task of equilibrating a cylinder on the tray Performance was assessed through EMG of anterior leg muscles angular displacement of the main Joints involved in the postural reactions and displacement of the tray Results showed that both certainty on the direction of perturbation and Increased supra-postural task constraint led to decreased angular displacement of the knee and the hip Furthermore combination of certainty and high supra-postural task constraint produced shorter latency of muscular activation Such postural responses were paralleled by decreased displacement of the tray Thesi results suggest a functional integration between the tasks with central set priming reactive postural responses from contextual cues and Increased stability demand (C) 2010 Elsevier B V All rights reserved

Contextual Deliberation of Cognitive Agents in Defeasible Logic

This article extends Defeasible Logic to deal with the contextual deliberation process of cognitive agents. First, we introduce meta-rules to reason with rules. Meta-rules are rules that have as a consequent rules for motivational components, such as obligations, intentions and desires. In other words, they include nested rules. Second, we introduce explicit preferences among rules. They deal with complex structures where nested rules can be involved.

Effect of estradiol benzoate microinjection into the median raphe nucleus on contextual conditioning

Estrogen deficiency has been associated with stress, anxiety and depression. Estrogen receptors have been identified in the median raphe nucleus (MRN). This structure is the main source of serotonergic projections to the hippocampus, a forebrain area implicated in the regulation of defensive responses and in the resistance to chronic stress. There is reported evidence indicating that estrogen modulates 5-HT(1A) receptor function. In the MRN, somatodendritic 5-HT(1A) receptors control the activity of serotonergic neurones by negative feedback. The present study has evaluated the effect of intra-MRN injection of estradiol benzoate (EB, 600 or 1200 ng/0.2 mu l) on the performance of ovariectormized rats submitted to contextual conditioning. Additionally, the same treatment was given after intra-MRN injection of Way 100635 (100 ng/0.2 mu l). a 5-HT(1A) receptor antagonist. Both doses of EB decreased freezing and increased rearing, indicating an anxiolytic effect. Pretreatment with Way 100635 antagonized the anxiolytic effect of estradiol. On the basis of these results, it may be suggested that estrogens modulate anxiety by acting on 5-HT(1A) receptors localized in the MRN. (C) 2009 Elsevier B.V. All rights reserved.

Selective involvement of GABAergic mechanisms of the dorsal periaqueductal gray and inferior colliculus on the memory of the contextual fear as assessed by the fear potentiated startle test

The inferior colliculus (IC) together with the dorsal periaqueductal gray (dPAG), the amygdala and the medial hypothalamus make part of the brain aversion system, which has mainly been related to the organization of unconditioned fear. However, the involvement of the IC and dPAG in the conditioned fear is still unclear. It is certain that GABA has a regulatory role on the aversive states generated and elaborated in these midbrain structures. In this study, we evaluated the effects of injections of the GABA-A receptor agonist muscimol (1.0 and 2.0 nmol/0.2 mu L) into the IC or dPAG on the freezing and fear-potentiated startle (FPS) responses of rats submitted to a context fear conditioning. Intra-IC injections of muscimol did not cause any significant effect on the FPS or conditioned freezing but enhanced the startle reflex in non-conditioned animals. In contrast, intra-dPAG injections of muscimol caused significant reduction in FPS and conditioned freezing without changing the startle reflex in non-conditioned animals. Thus, intra-dPAG injections of muscimol produced the expected inhibitory effects on the anxiety-related responses, the FPS and the freezing whereas these injections into the IC produced quite opposite effects suggesting that descending inhibitory pathways from the IC, probably mediated by GABA-A mechanisms, exert a regulatory role on the lower brainstem circuits responsible for the startle reflex. (C) 2008 Elsevier Inc. All rights reserved.

Midazolam reduces the selective activation of the rhinal cortex by contextual fear stimuli

Independent brain circuits appear to underlie different forms of conditioned fear, depending on the type of conditioning used, such as a context or explicit cue paired with footshocks. Several clinical reports have associated damage to the medial temporal lobe (MTL) with retrograde amnesia. Although a number of studies have elucidated the neural circuits underlying conditioned fear, the involvement of MTL components in the aversive conditioning paradigm is still unclear. To address this issue, we assessed freezing responses and Fos protein expression in subregions of the rhinal cortex and ventral hippocampus of rats following exposure to a context, light or tone previously paired with footshock (Experiment 1). A comparable degree of freezing was observed in the three types of conditioned fear, but with distinct patterns of Fos distribution. The groups exposed to cued fear conditioning did not show changes in Fos expression, whereas the group subjected to contextual fear conditioning showed selective activation of the ectorhinal (Ect), perirhinal (Per), and entorhinal (Ent) cortices, with no changes in the ventral hippocampus. We then examined the effects of the benzodiazepine midazolam injected bilaterally into these three rhinal subregions in the expression of contextual fear conditioning (Experiment 2). Midazolam administration into the Ect, Per, and Ent reduced freezing responses. These findings suggest that contextual and explicit stimuli endowed with aversive properties through conditioning recruit distinct brain areas, and the rhinal cortex appears to be critical for storing context-, but not explicit cue-footshock, associations. (C) 2010 Elsevier B.V. All rights reserved.

Contextual politics of service delivery reforms: Lessons from Delhi, Mexico city and Sao Paulo comparison

Little attention has been given to the contextual politics of service delivery reforms. By focusing on cases of reform in the healthcare sector and, to a lesser extent, in the main policies in the social service sector in India, Mexico and Brazil, this article explores two dimensions of analysis which have enormous relevance in understanding the reach and effectiveness of service delivery reforms: (1) the historical timing of reforms and sectorial baselines, and (2) the degree and institutional locus of local discretion in policy. Findings show that depending on both dimensions, there is an extraordinary variation as to the degree, interests involved and meaning of changes which, in theory, correspond to these countries` commitment to the service delivery reforms, However, consideration of the contextual politics is relevant not for the sake of diversity but for the similarities that this diversity reveals, pointing to underlying analytic dimensions that receive attention in this article.

Incidental Encoding Strategies Did Not Improve Contextual Memory in Parkinson`s Disease Patients

Background. This study investigated the performance of patients with idiopathic Parkinson`s disease (PD) without dementia for incidental recognition memory and the effect of encoding strategies on contextual memory. Methods. The authors studied 21 patients with PD (ages 60-85, 12 women; Hoehn and Yahr I-III, Activities of Daily Living 70%-100%) and 22 healthy controls (ages 60-84, 18 women). Participants completed the vocabulary subtest of the Wechsler Adult Intelligence Scale and the Wisconsin Card Sorting Test (WCST). To assess the incidental recognition memory for item (object) and context (location of the object), participants of each group were assigned to 1 of 2 encoding conditions: (a) an incidental associative instruction to bind the object to its location or (b) a nonassociative, nonspecific instruction. Results. PD patients showed performance comparable to the control group`s on the vocabulary subtest and WCST. In contrast to controls, PD patients were unable to take advantage of the associative encoding instruction, which also had a deleterious effect on item recognition. Conclusion. This sample of participants with PD showed diminished item and context recognition memory and an impaired ability to use incidental memory encoding strategy, suggesting a compromised cognitive reserve. The fact that these alterations occurred in early stages of PD, and prior to more general cognitive alterations such as executive dysfunction, should be considered in the management of patients by using specific cognitive rehabilitation interventions.

The expression of contextual fear conditioning involves activation of an NMDA receptor-nitric oxide pathway in the medial prefrontal cortex

The ventral portion of medial prefrontal cortex (vMPFC) is involved in contextual fear-conditioning expression in rats. In the present study, we investigated the role of local N-methyl-D-aspartic acid (NMDA) glutamate receptors and nitric oxide (NO) in vMPFC on the behavioral (freezing) and cardiovascular (increase of arterial pressure and heart rate) responses of rats exposed to a context fear conditioning. The results showed that both freezing and cardiovascular responses to contextual fear conditioning were reduced by bilateral administration of NMDA receptor antagonist LY235959 (4 nmol/200 nL) into the vMPFC before reexposition to conditioned chamber. Bilateral inhibition of neuronal NO synthase (nNOS) by local vMPFC administration of the N omega-propyl-L-arginine (N-propyl, 0.04 nmol/200 nL) or the NO scavenger carboxy-PTI0 (1 nmol/200 A) caused similar results, inhibiting the fear responses. We also investigated the effects of inhibiting glutamate- and NO-mediated neurotransmission in the vMPFC at the time of aversive context exposure on reexposure to the same context. It was observed that the 1st exposure results in a significant attenuation of the fear responses on reexposure in vehicle-treated animals, which was not modified by the drugs. The present results suggest that a vMPFC NMDA-NO pathway may play an important role on expression of contextual fear conditioning.