950 resultados para Alarm message


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The main concern in Wireless Sensor Networks (WSN) algorithms and protocols are the energy consumption. Thus, the WSN lifetime is one of the most important metric used to measure the performance of the WSN approaches. Another important metric is the WSN spatial coverage, where the main goal is to obtain sensed data in a uniform way. This paper has proposed an approach called (m,k)-Gur Game that aims a trade-off between quality of service and the increasement of spatial coverage diversity. Simulation results have shown the effectiveness of this approach. © 2012 IEEE.

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A recent trend in networked control systems (NCSs) is the use of wireless networks enabling interoperability between existing wired and wireless systems. One of the major challenges in these wireless NCSs (WNCSs) is to overcome the impact of the message loss that degrades the performance and stability of these systems. Moreover, this impact is greater when dealing with burst or successive message losses. This paper discusses and presents the experimental results of a compensation strategy to deal with this burst message loss problem in which a NCS mathematical model runs in parallel with the physical process, providing sensor virtual data in case of packet losses. Running in real-time inside the controller, the mathematical model is updated online with real control signals sent to the actuator, which provides better reliability for the estimated sensor feedback (virtual data) transmitted to the controller each time a message loss occurs. In order to verify the advantages of applying this model-based compensation strategy for burst message losses in WNCSs, the control performance of a motor control system using CAN and ZigBee networks is analyzed. Experimental results led to the conclusion that the developed compensation strategy provided robustness and could maintain the control performance of the WNCS against different message loss scenarios.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In Ostariophysan fish, the detection of the alarm substance liberated into the water as a consequence of an attack by a predator elicits an alarm reaction or anti-predatory behavior. In this study, experiments were performed to: (i) describe and quantitatively characterize the behavioral and ventilatory responses in piaucu fish (Leporinus macrocephalus), individually and as part of a school, to conspecific alarm substance (CAS) and; (ii) test the effect of acute fluoxetine treatment on alarm reaction. Histological analysis revealed the presence of club cells in the intermediate and superficial layers of the epidermis. The predominant behavioral response to CAS was freezing for fish held individually, characterized by the cessation of the swimming activity as the animal settles to a bottom corner of the aquarium. Fish exposed to CAS showed decrease in the mean ventilatory frequency (approximately 13%) relative to control. In schools, CAS elicited a biphasic response that was characterized by erratic movements followed by increased school cohesion and immobility, reflected as an increased school cohesion (65.5% vs. -5.8% for controls) and in the number of animals near the bottom of the aquarium (42.0% vs. 6.5% for controls). Animals treated with single i.p. injections of fluoxetine (10 mu g/g b.w.) did not exhibit alarm behavior following CAS stimulation. These results show that an alarm pheromone system is present in piaucu fish, evidenced by the presence of epidermal club cells and an alarm reaction induced by CAS and consequently of a chemosensory system to transmit the appropriate information to neural structures responsible for initiating anti-predator behavioral responses. In addition, fluoxetine treatment caused an anxiolytic-like effect following CAS exposure. Thus, the alarm reaction in piaucu can be a useful model for neuroethological and pharmacological studies of anxiety-related states. (C) 2011 Elsevier Inc. All rights reserved.

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Every day, a substantial proportion of the general population experiences the distressing and frightening signs of an upcoming psychiatric illness. The consequences can be enormous because severe psychiatric disorders typically cause the loss of the ability to work and often mean a long-term burden for both the patients and their families. Even though most developed countries have an exceptionally high density of general practitioners and psychiatrists in private practice, getting a mental health appointment and seeing a doctor is often very difficult for patients with acute psychiatric symptoms. This study aimed at quantifying the time delay involved in seeking medical attendance when psychiatric disorders begin to develop.

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Using a chain of urns, we build a Bayesian nonparametric alarm system to predict catastrophic events, such as epidemics, black outs, etc. Differently from other alarm systems in the literature, our model is constantly updated on the basis of the available information, according to the Bayesian paradigm. The papers contains both theoretical and empirical results. In particular, we test our alarm system on a well-known time series of sunspots.

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To improve health and reduce costs, we need to encourage patients to make better healthcare decisions. Many informatics interventions are aimed at improving health outcomes by influencing patient behavior. However, we know little about how the content of a message in these interventions can influence a health-related decision. In this research we formulate a conceptual model to help explain and guide the design of “persuasive messages”, those which can change and influence patient behavior. We apply the conceptual model to design persuasive appointment reminder messages using humancentered design principles. Finally, we empirically test our hypotheses in a randomized controlled trial in order to determine the effectiveness of persuasive appointment reminders to reduce the number of missed appointments in a sample of 1016 subjects in a community health center. The results of the study confirm that reminder messages are effective in reducing missed appointment compared with no reminders (p=0.028). Further, reminder messages that incorporate heuristic cues such as authority, commitment, liking, and scarcity are more effective than reminder messages without such cues (p=0.006). However, the addition of systematic arguments or reasons for attending appointments have no effect on appointment adherence (p=0.646). The results of this research suggest that the content of reminder messages may be an important factor in helping to reduce missed appointments.