988 resultados para NEURAL-BASIS


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The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

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Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

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This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.

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In this study, an infrared thermography based sensor was studied with regard to usability and the accuracy of sensor data as a weld penetration signal in gas metal arc welding. The object of the study was to evaluate a specific sensor type which measures thermography from solidified weld surface. The purpose of the study was to provide expert data for developing a sensor system in adaptive metal active gas (MAG) welding. Welding experiments with considered process variables and recorded thermal profiles were saved to a database for further analysis. To perform the analysis within a reasonable amount of experiments, the process parameter variables were gradually altered by at least 10 %. Later, the effects of process variables on weld penetration and thermography itself were considered. SFS-EN ISO 5817 standard (2014) was applied for classifying the quality of the experiments. As a final step, a neural network was taught based on the experiments. The experiments show that the studied thermography sensor and the neural network can be used for controlling full penetration though they have minor limitations, which are presented in results and discussion. The results are consistent with previous studies and experiments found in the literature.

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The freshwater mollusc Lymnaea stagnalis was utilized in this study to further the understanding of how network properties change as a result of associative learning, and to determine whether or not this plasticity is dependent on previous experience during development. The respiratory and neural correlates of operant conditioning were first determined in normally reared Lymnaea. The same procedure was then applied to differentially reared Lymnaea, that is, animals that had never experienced aerial respiration during their development. The aim was to determine whether these animals would demonstrate the same responses to the training paradigm. In normally reared animals, a behavioural reduction in aerial respiration was accompanied by numerous changes within the neural network. Specifically, I provide evidence of changes at the level of the respiratory central pattern generator and the motor output. In the differentially reared animals, there was little behavioural data to suggest learning and memory. There were, however, significant differences in the network parameters, similar to those observed in normally reared animals. This demonstrated an effect of operant conditioning on differentially reared animals. In this thesis, I have identified additional correlates of operant conditioning in normally reared animals and provide evidence of associative learning in differentially reared animals. I conclude plasticity is not dependent on previous experience, but is rather ontogenetically programmed within the neural network.

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Atheory of educating is always derived from philosophical tenets. In Western society these tenets are concerned primarily with the provision, maintenance and evolution of knowledge for use by future generations. The provision of knowledge for future generations is for the purpose of ensuring cultural and biological survival. Essentially this provision involves two major criteria: first, that only that knowledge which has been judged to be exce11 ent shou1d be passed on and, second, in add it ion to providing knowledge claims, the evidence for knowledge claims must also be extended in order to fully enrich meaning for an individual involved in a learning experience. Embedded in such a theory of educating are a concept of educational excellence and a concept of the provision of evidence for knowledge claims. This thesis applied the contributions of metaphilosophy to the concepts of educational excellence and the provision of evidence. The metaphilosophy of Stephen C. Pepper was examined for its contributions to a theory of educating and a concept of educational excellence. Metaphilosophy is concerned with making knowledge meaningful. It is a subject matter which may be studied in and of itself and it is a method for acquiring meaning by interpreting knowledge. Historically people have interpreted the knowledge of the world from basically four adequate world views which Pepper termed formism, mechanism, contextual ism and organicism. He later proposed a fifth world view which he termed selectivism. In this thesis these world views were shown to contribute in a variety of ways to educational excellence, most particularly as they allow for interpretations and analysis of evidence about knowledge claims. Selecti vismwas examined in depth and was shown to contribute to educational excellence in two major ways; first, as a world hypothesis which offers an interpretation of the evidence for knowledge claims and, second, as a metahypothesis which provides knowledge about the nature of knowledge. Finally the importance of metaphilosophy in contributing to cultural survival was demonstrated in a discussion of the potential impact of selectivism on a theory of educating and educational excellence.

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Objectlve:--This study examined the intraclass reliability· of different measures of the excitability of the Hoffmann reflex, derived from stimulus-response curves. The slope of the regression line of the H-reflex stimulus-response curve advocated by Funase et al. (1994) was also compared to the peak of the first derivative of the H-reflex stimulus-response curve (dHIdVmax), a new measure introduced in this investigation. A secondary purpose was to explore the possibility of mood as a covariate when measuring excitability of the H-reflex arc. Methods: The H-reflex amplitude at a stimulus intensity corresponding to 5% of the maximum M-wave (Mmax) is an established measure that was used as an additional basis of comparison. The H-reflex was elicited in the soleus for 24 subjects (12 males and 12 females) on five separate days. Vibration was applied to the Achilles tendon prior to stimulation to test the sensitivity of the measures on test day four. The means of five evoked potentials at each gradually increasing intensity, from below H-reflex threshold to above Mmax, were used to create both the H-reflex and M-wave stimulus response curves for each subject across test days. The mood of the subjects was assessed using the Subjective Exercise Experience Scale (SEES) prior to the stimulation protocol each day. Results: There was a modest decrease in all H-reflex measures from the first to third test day, but it was non-significant (P's>0.05). All measures of the H-reflex exhibited a profound reduction following vibration on test day four, and then returned to baseline levels on test day five (P's<0.05). The intraclass correlation coefficient (ICC) for H-reflex amplitude at 5% of Mmax was 0.85. The ICC for the slope of the regression line was 0.79 while it was 0.89 for dH/dVmax. Maximum M-wave amplitude had an ICC of 0.96 attesting to careful methodological controls. The SEES subscales of fatigue and psychological well-being remained unchanged IV across the five days. The psychological distress subscale (PO.05). Conclusions: The peak of the first derivative of the H-reflex stimulus-response curve (dH/dVmax) was shown to have comparable reliability and sensitivity to other more established measures of excitability. Psychological distress and the amplitude of the H-reflex at 5% Mmax follow similar trends across days, however there was no significant correlation between the two measures. Significance: The proposed method appears to be a more robust measure ofH-reflex excitability than the other methods tested. As such it would be an advantageous method to apply in clinical and investigative settings. Additionally, the results suggest that the relationship between psychological distress and H-reflex amplitude should be investigated further.

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Psychopathy is associated with well-known characteristics such as a lack of empathy and impulsive behaviour, but it has also been associated with impaired recognition of emotional facial expressions. The use of event-related potentials (ERPs) to examine this phenomenon could shed light on the specific time course and neural activation associated with emotion recognition processes as they relate to psychopathic traits. In the current study we examined the PI , N170, and vertex positive potential (VPP) ERP components and behavioural performance with respect to scores on the Self-Report Psychopathy (SRP-III) questionnaire. Thirty undergraduates completed two tasks, the first of which required the recognition and categorization of affective face stimuli under varying presentation conditions. Happy, angry or fearful faces were presented under with attention directed to the mouth, nose or eye region and varied stimulus exposure duration (30, 75, or 150 ms). We found that behavioural performance to be unrelated to psychopathic personality traits in all conditions, but there was a trend for the Nl70 to peak later in response to fearful and happy facial expressions for individuals high in psychopathic traits. However, the amplitude of the VPP was significantly negatively associated with psychopathic traits, but only in response to stimuli presented under a nose-level fixation. Finally, psychopathic traits were found to be associated with longer N170 latencies in response to stimuli presented under the 30 ms exposure duration. In the second task, participants were required to inhibit processing of irrelevant affective and scrambled face distractors while categorizing unrelated word stimuli as living or nonliving. Psychopathic traits were hypothesized to be positively associated with behavioural performance, as it was proposed that individuals high in psychopathic traits would be less likely to automatically attend to task-irrelevant affective distractors, facilitating word categorization. Thus, decreased interference would be reflected in smaller N170 components, indicating less neural activity associated with processing of distractor faces. We found that overall performance decreased in the presence of angry and fearful distractor faces as psychopathic traits increased. In addition, the amplitude of the N170 decreased and the latency increased in response to affective distractor faces for individuals with higher levels of psychopathic traits. Although we failed to find the predicted behavioural deficit in emotion recognition in Task 1 and facilitation effect in Task 2, the findings of increased N170 and VPP latencies in response to emotional faces are consistent wi th the proposition that abnormal emotion recognition processes may in fact be inherent to psychopathy as a continuous personality trait.

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The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, K-nearest neighbor and 103 algorithms. In order to evaluate the similarity of these algorithms, we carried out three experiments using nine benchmark data sets from UCI machine learning repository. The first experiment compares HBL to other algorithms when sample size of dataset is changing. The second experiment compares HBL to other algorithms when dimensionality of data changes. The last experiment compares HBL to other algorithms according to the level of agreement to data target values. Our observations in general showed, considering classification accuracy as a measure, HBL is performing as good as most ANn variants. Additionally, we also deduced that HBL.:s classification accuracy outperforms 103's and K-nearest neighbour's for the selected data sets.

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Youth sport organizations depend on volunteers to coach the teams in the organization. The purpose of this quantitative study was to develop a further understanding of volunteer coach retention in youth sport. The data was collected through a quantitative questionnaire which used close-ended and Likert-scale questions. The questionnaire collected data on the modified Model of Volunteer Retention in Youth Sports, reasons to withdraw from coaching and human resource management. There were 126 surveys collected from members of the three largest youth sport associations in the town of Aylmer, Ontario. The study found that Person-Task fit was the best predictor of volunteer coach retention as it significantly correlated to one’s intention to continue coaching (p< 0.01). Furthermore, additional reasons were found to explain withdrawal from coaching - if one’s child stops playing the sport or if coaching is too time consuming. The retention of volunteer coaches in youth sport organizations requires a multi-dimensional approach in understanding how to best retain volunteer coaches.

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Four questions dominate normative contemporary constitutional theroy: What is the purpose of a constitution? What makes a constitution legitimate? What kinds of arguments are legitimate within the process of constitutional interpretation? What can make judicial review of legislation legitimate in principle? The main purpose of this text is to provide one general answer to the last question. The secondary purpose is to show how this answer may bear upon our understanding of the fundamental basis of constitutional law. These two purposes should suggest particular answers to the first three questions.

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Tesis (Doctor en Ciencias con Orientación en Procesos Sustentables) UANL, 2013.

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Les interneurones GABAergiques constituent une population mineure de cellules par rapport aux neurones glutamatergiques dans le néocortex. Cependant ils contrôlent fortement l'excitabilité neuronale, la dynamique des réseaux neuronaux et la plasticité synaptique. L'importance des circuits GABAergiques dans le processus fonctionnel et la plasticité des réseaux corticaux est soulignée par des résultats récents qui montrent que des modifications très précises et fiables des circuits GABAergiques sont associées à divers troubles du développement neurologique et à des défauts dans les fonctions cérébrales. De ce fait, la compréhension des mécanismes cellulaires et moléculaires impliquant le développement des circuits GABAergiques est la première étape vers une meilleure compréhension de la façon dont les anomalies de ces processus peuvent se produire. La molécule d’adhésion cellulaire neurale (NCAM) appartient à la super-famille des immunoglobulines de reconnaissance cellulaire et est impliquée dans des interactions homophiliques et hétérophiliques avec d’autres molécules. Même si plusieurs rôles de NCAM ont été démontrés dans la croissance neuronale, la fasciculation axonale, la formation et la maturation de synapses, de même que dans la plasticité cellulaire de plusieurs systèmes, le rôle de NCAM dans la formation des synapses GABAergiques reste inconnu. Ce projet visait donc à déterminer le rôle précis de NCAM dans le processus de maturation des synapses GABAergiques dans le néocortex, en modulant son expression à différentes étapes du développement. L’approche choisie a été de supprimer NCAM dans des cellules GABAergiques à paniers avant la maturation des synapses (EP12-18), pendant la maturation (EP16-24), ou durant le maintien de celles-ci (EP24-32). Les méthodes utilisées ont été le clonage moléculaire, l’imagerie confocale, la culture de coupes organotypiques et des techniques morphométriques de quantification de l’innervation GABAergique. Nos résultats montrent que l’inactivation de NCAM durant la phase de maturation des synapses périsomatiques (EP16-24) cause une réduction du nombre de synapses GABAergiques périsomatiques et du branchement de ces axones. En revanche, durant la phase de maintien (EP26-32), l’inactivation de NCAM n’a pas affecté ces paramètres des synapses GABAergiques. Or, il existe trois isoformes de NCAM (NCAM120, 140 et 180) qui pourraient jouer des rôles différents dans les divers types cellulaires ou à des stades développementaux différents. Nos données montrent que NCAM120 et 140 sont nécessaires à la maturation des synapses périsomatiques GABAergiques. Cependant, NCAM180, qui est l’isoforme la plus étudiée et caractérisée, ne semble pas être impliquée dans ce processus. De plus, l’inactivation de NCAM n’a pas affecté la densité des épines dendritiques ou leur longueur. Elle est donc spécifique aux synapses périsomatiques GABAeriques. Finalement, nos résultats suggèrent que le domaine conservé C-terminal KENESKA est essentiel à la maturation des synapses périsomatiques GABAergiques. Des expériences futures nous aiderons à mieux comprendre la mécanistique et les différentes voies de signalisation impliquées.