Two protocols without periodicity for the global and preemptive scheduling problem of multi-mode real-time systems upon multiprocessor Platforms

We consider the problem of scheduling a multi-mode real-time system upon identical multiprocessor platforms. Since it is a multi-mode system, the system can change from one mode to another such that the current task set is replaced with a new task set. Ensuring that deadlines are met requires not only that a schedulability test is performed on tasks in each mode but also that (i) a protocol for transitioning from one mode to another is specified and (ii) a schedulability test for each transition is performed. We propose two protocols which ensure that all the expected requirements are met during every transition between every pair of operating modes of the system. Moreover, we prove the correctness of our proposed algorithms by extending the theory about the makespan determination problem.

Comparative study about heating systems for pultrusion process

Different heating systems have been used in pultrusion, where the most widely used heaters are planar resistances. The primary objective of this study was to develop an improved heating system and compare its performance with that of a system with planar resistances. In this study, thermography was used to better understand the temperature profile along the die. Finite element analysis was performed to determine the amount of energy consumed by the heating systems. Improvements were made to the die to test the new heating system, and it was found that the new system reduced the setup time and energy consumption by approximately 57%.

Approximate entropy normalized measures for analyzing social neurobiological systems

When considering time series data of variables describing agent interactions in social neurobiological systems, measures of regularity can provide a global understanding of such system behaviors. Approximate entropy (ApEn) was introduced as a nonlinear measure to assess the complexity of a system behavior by quantifying the regularity of the generated time series. However, ApEn is not reliable when assessing and comparing the regularity of data series with short or inconsistent lengths, which often occur in studies of social neurobiological systems, particularly in dyadic human movement systems. Here, the authors present two normalized, nonmodified measures of regularity derived from the original ApEn, which are less dependent on time series length. The validity of the suggested measures was tested in well-established series (random and sine) prior to their empirical application, describing the dyadic behavior of athletes in team games. The authors consider one of the ApEn normalized measures to generate the 95th percentile envelopes that can be used to test whether a particular social neurobiological system is highly complex (i.e., generates highly unpredictable time series). Results demonstrated that suggested measures may be considered as valid instruments for measuring and comparing complexity in systems that produce time series with inconsistent lengths.

Efficient schedulability tests for real-time embedded systems with urgent routines

Task scheduling is one of the key mechanisms to ensure timeliness in embedded real-time systems. Such systems have often the need to execute not only application tasks but also some urgent routines (e.g. error-detection actions, consistency checkers, interrupt handlers) with minimum latency. Although fixed-priority schedulers such as Rate-Monotonic (RM) are in line with this need, they usually make a low processor utilization available to the system. Moreover, this availability usually decreases with the number of considered tasks. If dynamic-priority schedulers such as Earliest Deadline First (EDF) are applied instead, high system utilization can be guaranteed but the minimum latency for executing urgent routines may not be ensured. In this paper we describe a scheduling model according to which urgent routines are executed at the highest priority level and all other system tasks are scheduled by EDF. We show that the guaranteed processor utilization for the assumed scheduling model is at least as high as the one provided by RM for two tasks, namely 2(2√−1). Seven polynomial time tests for checking the system timeliness are derived and proved correct. The proposed tests are compared against each other and to an exact but exponential running time test.

Maintenance of fire sprinkler systems based on the dynamic assessment of its condition

Safety is one of the major concerns of process safety engineers in most industrial facilities all over the world. To this scope, some events play an important role once the effect of their consequences can be assumed as totally undesirable. One of these events refers to the occurrence of a fire. Such event can result in catastrophic consequences for life, equipment, and continuity of activities or even leading to environmental damage. A fire protection equipment with low reliability means that this equipment are often unavailable and thus the risk of a fire increases. Maintenance of fire protection equipment is very important because this kind of systems is mostly in a dormant mode, which gives uncertainty about their operability when demanded in a real situation of fire. This article outlines the importance of tests, inspection, and maintenance operations in the context of a fire sprinkler system and proposes a methodology based on international standards and supported by test/inspection reports to correct the frequency of these actions according to the level of degradation of the components and regarding safety purposes. © 2015 American Institute of Chemical Engineers.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Intelligent decision support systems for collaboration in industrial plants

Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Study of forbidden transitions in atomic systems

A Thesis submitted for the co-tutelle degree of Doctor in Physics at Universidade Nova de Lisboa and Université Pierre et Marie Curie

A low-cost method to test cytotoxic effects of Crotalus vegrandis (Serpentes: Viperidae) venom on kidney cell cultures

The pathogenesis of the renal lesion upon envenomation by snakebite has been related to myolysis, hemolysis, hypotension and/or direct venom nephrotoxicity caused by the venom. Both primary and continuous cell culture systems provide an in vitro alternative for quantitative evaluation of the toxicity of snake venoms. Crude Crotalus vegrandis venom was fractionated by molecular exclusion chromatography. The toxicity of C. vegrandis crude venom, hemorrhagic, and neurotoxic fractions were evaluated on mouse primary renal cells and a continuous cell line of Vero cells maintained in vitro. Cells were isolated from murine renal cortex and were grown in 96 well plates with Dulbecco's Modified Essential Medium (DMEM) and challenged with crude and venom fractions. The murine renal cortex cells exhibited epithelial morphology and the majority showed smooth muscle actin determined by immune-staining. The cytotoxicity was evaluated by the tetrazolium colorimetric method. Cell viability was less for crude venom, followed by the hemorrhagic and neurotoxic fractions with a CT50 of 4.93, 18.41 and 50.22 µg/mL, respectively. The Vero cell cultures seemed to be more sensitive with a CT50 of 2.9 and 1.4 µg/mL for crude venom and the hemorrhagic peak, respectively. The results of this study show the potential of using cell culture system to evaluate venom toxicity.

An Exact Schedulability Test for Global FP Using State Space Pruning

Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

SUSCEPTIBILITY TEST FOR FUNGI: CLINICAL AND LABORATORIAL CORRELATIONS IN MEDICAL MYCOLOGY

SUMMARYDuring recent decades, antifungal susceptibility testing has become standardized and nowadays has the same role of the antibacterial susceptibility testing in microbiology laboratories. American and European standards have been developed, as well as equivalent commercial systems which are more appropriate for clinical laboratories. The detection of resistant strains by means of these systems has allowed the study and understanding of the molecular basis and the mechanisms of resistance of fungal species to antifungal agents. In addition, many studies on the correlation of in vitro results with the outcome of patients have been performed, reaching the conclusion that infections caused by resistant strains have worse outcome than those caused by susceptible fungal isolates. These studies have allowed the development of interpretative breakpoints for Candida spp. and Aspergillus spp., the most frequent agents of fungal infections in the world. In summary, antifungal susceptibility tests have become essential tools to guide the treatment of fungal diseases, to know the local and global disease epidemiology, and to identify resistance to antifungals.

Information Systems Outsourcing Adoption

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Assessing the feasibility of impregnating phase change materials in lightweight aggregate for development of thermal energy storage systems

This paper assesses the feasibility of impregnation/encasement of phase change materials (PCMs) in lightweight aggregates (LWAs). An impregnation process was adopted to carry out the encasement study of two different PCMs in four different LWAs. The leakage of the impregnated/encased PCMs was studied when they were submitted to freeze/thawing and oven drying tests, separately. The results confirmed that, the impregnation/encasement method is effective with respect to the large thermal energy storage density, and can be suitable for applications were PCMs cannot be incorporated directly such as asphalt road pavements.