The conversion matrix between Beta-spline basis functions and Bézier representation is analyzed in this paper. Based on it, calculation of arbitrary degree Beta-spline basis functions can be translated into a sol...
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The conversion matrix between Beta-spline basis functions and Bézier representation is analyzed in this paper. Based on it, calculation of arbitrary degree Beta-spline basis functions can be translated into a solution of linear system of equations. The construction of Beta-spline is simplified greatly, which made it more suitable for implement in pervasive computing.
In earlier works, we presented a computational infrastructure that allows an analyst to estimate the security of a system in terms of the loss that each stakeholder. We also demonstrated this infrastructure through th...
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In an earlier series of works, Boehm et al. discuss the nature of information system dependability and highlight the variability of system dependability according to stakeholders. In a recent paper, the dependency pat...
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Human sleep is divided into two segments, Rapid Eye Movement (REM) sleep and Non-REM (NREM) sleep. NREM sleep is further divided into 4 stages. Sleep staging attempts to identify these stages based on the signals coll...
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It is well known that the combination between Neural networks and fuzzy controllers are considered as the most efficient approximators of different functions and also proves their capability of controlling nonlinear d...
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ISBN:
(纸本)9781849192316
It is well known that the combination between Neural networks and fuzzy controllers are considered as the most efficient approximators of different functions and also proves their capability of controlling nonlinear dynamical systems So, in this paper, the authors introduce a novel technique of control called" hybrid control" which is Based on Feedback Linearization and Field Oriented Control of an Induction Motor, in order to replace the sliding mode controllers (speed and flux ones). In fact, the objectives required by the introduction of neural networks (RANNCs) is to perform the control which is shown by simulation results.
Probabilistic atlases have been established in the literature as a standard tool for enhancing the intensity-based classification of brain MRI. The rapidly growing neonatal brain requires an age-specific spatial proba...
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ISBN:
(纸本)9781424441259
Probabilistic atlases have been established in the literature as a standard tool for enhancing the intensity-based classification of brain MRI. The rapidly growing neonatal brain requires an age-specific spatial probabilistic atlas to guide the segmentation process. In this paper we describe a method for dynamically creating a probabilistic atlas for any chosen stage of neonatal brain development. The atlas is created from the segmentations of 153 subjects of different ages using a kernel regression method. For any given age, an intensity template as well as the corresponding tissue probability maps with the correct sizes and shapes of the structures can be dynamically generated. The resulting atlas provides prior tissue probability maps for six structures - cortex, white matter, subcortical gray matter, brainstem and cerebellum, for ages of 29 to 44 weeks of gestation.
Modern machine learning techniques have encouraged interest in the development of vehicle health monitoring systems that ensure secure and reliable operations of rail vehicles. In an earlier study, an energy-efficient...
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This paper outlines the initial ideas and results surrounding the development of an accurate hand movement measurement tool. This tool will assist medical clinicians, specifically rheumatologists and orthopeadic hand ...
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Emotional learning involves two stages. The first is to acquire reinforcers from stimuli and the second is to associate such reinforcers with emotional responses. Both stages can be found occurring in the amygdala. Le...
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Emotional learning involves two stages. The first is to acquire reinforcers from stimuli and the second is to associate such reinforcers with emotional responses. Both stages can be found occurring in the amygdala. LeDoux's fear circuit model suggests two routes, a subcortical route and a cortical route, for emotional information entering the amygdala for associative learning. It can be used to explain how the actual recognition of emotions from facial expressions can be processed in the brain. Based on the model, a neural architecture is proposed using the stochastic Helmholtz machine (SHM) with the wake-sleep algorithm. In this paper, the results of three experiments about the subcortical emotional learning are reported, where different configurations of SHMs are involved. The first two experiments are to identify a suitable way to allow behavioural responses entering the central nucleus of the amygdala for association. However, both experiments show symptoms of overfitting, where some weights and biases of neurons are observed that will unusually increase during training. Therefore, the final experiment is designed to maintain the range of weights between -1 and +1 in order to solve the overfitting problem. The last experiment shows that the neural architecture with the new weight policy holds a lot of potential for modelling subcortical learning.
Data mining (DM) is the extraction of hidden predictive information from large databases that has becoming a powerful new technology with great potential to help companies to focus on the most important information in...
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