Neural network model for designing automotive devices using SMD LED

The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.

Gait Pattern Adaptation for an Active Lower-Limb Orthosis Based on Neural Networks

This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011

Neural network-based H(infinity) control for fully actuated and underactuated cooperative manipulators

This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.

Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

Network of phase-locking oscillators and a possible model for neural synchronization

In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state. (C) 2011 Elsevier B.V. All rights reserved.

Adoption and use of precision agriculture technologies in the sugarcane industry of So Paulo state, Brazil

Precision agriculture (PA) technologies are being applied to crops in Brazil, which are important to ensure Brazil`s position in agricultural production. However, there are no studies available at present to indicate the extent to which PA technologies are being used in the country. Therefore, the main objective of this research was to investigate how the sugar-ethanol industry in So Paulo state, which produces 60% of the domestic sugarcane, is adopting and using these techniques. For this purpose, primary data were used, which were obtained from a questionnaire sent to all companies operating in the sugar-ethanol industry in the region. The aim was to determine to what extent these companies are adopting and using PA technologies, and also to promote a more in-depth discussion of the topic within the sugar-ethanol industry. Information was obtained on the features of the companies, on sources of information that they use for adopting these technologies, on their impacts on these companies and on obstacles hindering their adoption. The main conclusions of this research suggest that companies that adopt and use PA practices reap benefits, such as managerial improvements, higher yields, lower costs, minimization of environmental impacts and improvements in sugarcane quality.

Distance Education in Another Register: Uses and Appropriation of Technologies in Teacher Education

The article explores the relationships between distance education, information and communication technologies and teacher education. Its focus is on the interactive media and its uses in an in-service teacher education program, in Brazil, and on the ways the teachers used the technologies doing their own appropriateness. It departs from the presuppositions of the society of knowledge, that is, the close relationships between new technologies, continuing professional development and social inclusion, arguing that this paradigm is an ideological discourse. The article shows how the teachers have used the technologies in creative ways, calling the attention to the importance of this teachers` abilities as a basic skill to facing the challenges of the society of knowledge itself.

L-Allylglycine dissociates the neural substrates of fear in the periaqueductal gray of rats

The dorsal (dPAG) and ventral (vPAG) regions of the periaqueductal gray are well known to contain the neural substrates of fear and anxiety. Chemical or electrical stimulation of the dPAG induces freezing, followed by a robust behavioral reaction that has been considered an animal model of panic attack. In contrast, the vPAG is part of a neural system, in which immobility is the usual response to its stimulation. The defense reaction induced by the stimulation of either region is accompanied by anti nociception. Although GABAergic mechanisms are known to exert tonic inhibitory control on the neural substrates of fear in the dPAG, the role of these mechanisms in the vPAG is still unclear. The present study examined defensive behaviors and antinociception induced by microinjections of an inhibitor of gamma-aminobutyric acid synthesis, L-allylglycine (L-AG; 1, 3, and 5 mu g/0.2 mu l), into either the dPAG or vPAG of rats subjected to the open field and tail-flick tests. Passive or tense immobility was the predominant behavior after L-AG (1 or 3 mu g) microinjection into the vPAG and dPAG, respectively, which was replaced with intense hyperactivity, including jumps or rearings, after injections of a higher dose (5 mu g/0.2 mu l) into the dPAG or vPAG. Moreover, whereas intra-dPAG injection of 3 mu g L-AG produced intense antinociception, only weak antinociception was induced by intra-vPAG injections of 5 mu g L-AG. These findings suggest that GABA mechanisms are involved in the mediation of antinociception and behavioral inhibition to aversive stimulation of the vPAG and exert powerful control over the neural substrates of fear in the dPAG to prevent a full-blown defense reaction possibly associated with panic disorder. (C) 2009 Elsevier Inc. All rights reserved.

NEURAL CORRELATES OF SCENT MARKING BEHAVIOR IN C57BL/6J MICE: DETECTION AND RECOGNITION OF A SOCIAL STIMULUS

Mice show urinary scent marking behavior as a form of social communication. Marking to a conspecific stimulus mouse or odor varies with stimulus familiarity, indicating discrimination of novel and familiar animals. This study investigated Fos immunoreactivity in inbred C57BL/6J (C57) males following scent marking behavior in response to detection of a social stimulus, or discrimination between a familiar and an unfamiliar conspecific. In Experiment 1 C57 mice were exposed for four daily trials to an empty chamber; on a test day they were exposed to the same chamber or to a male CD-1 mouse in that chamber. Increased scent marking to the CD-1 mouse was associated with increased Fos-immunoreactive cells in the basolateral amygdala, medial amygdala, and dorsal and ventral premammillary nuclei. In Experiment 2 C57 mice were habituated to a CD-1 male for 4 consecutive days and, on the 5th day, exposed to the same CD-1 male, or to a novel CD-1 male. Mice exposed to a novel CD-1 displayed a significant increase in scent marking compared to their last exposure to the familiar stimulus, indicating discrimination of the novelty of this social stimulus. Marking to the novel stimulus was associated with enhanced activation of several telencephalic, as well as hypothalamic and midbrain, structures in which activation had not been seen in the detection paradigm (Experiment 1). These included medial prefrontal and piriform cortices, and lateral septum; the paraventricular nuclei, ventromedial nuclei, and lateral area of the hypothalamus, and the ventrolateral column of the periaqueductal gray. These data suggest that a circumscribed group of structures largely concerned with olfaction is involved in detection of a conspecific olfactory stimulus, whereas discrimination of a novel vs. a familiar conspecific stimulus engages a wider range of forebrain structures encompassing higher-order processes and potentially providing an interface between cognitions and emotions. (C) 2009 IBRO. Published by Elsevier Ltd. All rights reserved.

Neural activity changes to emotional stimuli in healthy individuals under chronic use of clomipramine

Previous functional magnetic resonance imaging (fMRI) studies examined neural activity responses to emotive stimuli in healthy individuals after acute/subacute administration of antidepressants. We now report the effects of repeated use of the antidepressant clomipramine on fMRI data acquired during presentation of emotion-provoking and neutral stimuli on healthy volunteers. A total of 12 volunteers were evaluated with fMRI after receiving low doses of clomipramine for 4 weeks and again after 4 weeks of washout. Fear-, happiness-, anger-provoking and neutral pictures from the International Affective Picture System (IAPS) were used. Data analysis was performed with statistical parametric mapping (P < 0.05). Paired t-test comparisons for each condition between medicated and unmedicated states showed, to negative valence paradigms, decrease in brain activity in the amygdala when participants were medicated. We also demonstrated, across both positive and negative valence paradigms, consistent decreases in brain activity in the medicated state in the anterior cingulate gyrus and insula. This is the first report of modulatory effects of repeated antidepressant use on the central representation of somatic states in response to emotions of both negative and positive valences in healthy individuals. Also, our results corroborate findings of antidepressant-induced temporolimbic activity changes to emotion-provoking stimuli obtained in studies of subjects treated acutely with such agents.

Hyperdopaminergia and NMDA Receptor Hypofunction Disrupt Neural Phase Signaling

Neural phase signaling has gained attention as a putative coding mechanism through which the brain binds the activity of neurons across distributed brain areas to generate thoughts, percepts, and behaviors. Neural phase signaling has been shown to play a role in various cognitive processes, and it has been suggested that altered phase signaling may play a role in mediating the cognitive deficits observed across neuropsychiatric illness. Here, we investigated neural phase signaling in two mouse models of cognitive dysfunction: mice with genetically induced hyperdopaminergia [dopamine transporter knock-out (DAT-KO) mice] and mice with genetically induced NMDA receptor hypofunction [NMDA receptor subunit-1 knockdown (NR1-KD) mice]. Cognitive function in these mice was assessed using a radial-arm maze task, and local field potentials were recorded from dorsal hippocampus and prefrontal cortex as DAT-KO mice, NR1-KD mice, and their littermate controls engaged in behavioral exploration. Our results demonstrate that both DAT-KO and NR1-KD mice display deficits in spatial cognitive performance. Moreover, we show that persistent hyperdopaminergia alters interstructural phase signaling, whereas NMDA receptor hypofunction alters interstructural and intrastructural phase signaling. These results demonstrate that dopamine and NMDA receptor dependent glutamate signaling play a critical role in coordinating neural phase signaling, and encourage further studies to investigate the role that deficits in phase signaling play in mediating cognitive dysfunction.

Neural response telemetry in patients with the double-array cochlear implant

This study aimed to evaluate the neural response in double-array cochlear implant as well as to describe the refractory recovery and the spread of excitation functions. In a prospective study 11 patients were implanted with the double-array cochlear implant. Neural response telemetry (NRT) was performed intra-operatively. NRT threshold could be registered in 6 of the 11 patients, at least in one electrode. The remaining five patients did not show measurable neural response intra-operatively. It was noted that although recovery and spread of excitation functions could be recorded in all the tested electrodes with measurable neural responses, the responses were shown to be different from the usual register in patients with other etiologies.