10 resultados para Web-Assisted Error Detection

em Instituto Politécnico do Porto, Portugal


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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.

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An accurate and sensitive method for determination of 18 polycyclic aromatic hydrocarbons (PAHs) (16 PAHs considered by USEPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in fish samples was validated. Analysis was performed by microwave-assisted extraction and liquid chromatography with photodiode array and fluorescence detection. Response surface methodology was used to find the optimal extraction parameters. Validation of the overall methodology was performed by spiking assays at four levels and using SRM 2977. Quantification limits ranging from 0.15–27.16 ng/g wet weight were obtained. The established method was applied in edible tissues of three commonly consumed and commercially valuable fish species (sardine, chub mackerel and horse mackerel) originated from Atlantic Ocean. Variable levels of naphthalene (1.03–2.95 ng/g wet weight), fluorene (0.34–1.09 ng/g wet weight) and phenanthrene (0.34–3.54 ng/g wet weight) were detected in the analysed samples. None of the samples contained detectable amounts of benzo[a]pyrene, the marker used for evaluating the occurrence and carcinogenic effects of PAHs in food.

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A methodology for the determination of the pesticide chlorfenvinphos by microwave-assisted solvent extraction and square-wave cathodic stripping voltammetry at a mercury film ultramicroelectrode in soil samples is proposed. Optimization of microwave solvent extraction performed with two soils, selected for having significantly different properties, indicated that the optimum solvent for extracting chlorfenvinphos is hexane-acetone (1:1, v/v). The voltammetric procedure is based on controlled adsorptive accumulation of the insecticide at the potential of -0.60 V (vs. Ag/AgCl) in the presence of Britton-Robinson buffer (pH 6.2). The detection limit obtained for a 10 s collection time was 3.0 x 10-8 mol l-1. The validity of the developed methodology was assessed by recovery experiments at the 0.100 µg g-1 level. The average recoveries and standard deviations for the global procedure reached byMASE-square-wave voltammetry were 90.2±2.8% and 92.1±3.4% for type I (soil rich in organic matter) and type II (sandy soil) samples, respectively. These results are in accordance to the expected values which show that the method has a good accuracy.

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An analytical multiresidue method for the simultaneous determination of seven pesticides in fresh vegetable samples, namely, courgette (Cucurbita pepo), cucumber (Cucumis sativus), lettuce (Lactuca sativa, Romaine and Iceberg varieties) and peppers (Capsicum sp.) is described. The procedure, based on microwave-assisted extraction (MAE) and analysis by liquid chromatography– photodiode array (LC–PDA) detection was applied to four carbamates (carbofuran, carbaryl, chlorpropham and EPTC) and three urea pesticides (monolinuron, metobromuron and linuron). Extraction solvent and the addition of anhydrous sodium sulphate to fresh vegetable homogenate before MAE were the parameters optimised for each commodity. Recovery studies were performed using spiked samples in the range 250–403 µgkg- 1 in each pesticide. The pesticide residues were extracted using 20mL acetonitrile at 60 ºC, for 10 min. Acceptable recoveries and RSDs were attained (overall average recovery of 77.2% and RSDs are lower than 11%). Detection limits ranged between 5.8 µgkg- 1 for carbaryl to 12.3 µgkg- 1 for carbofuran. The analytical protocol was applied for quality control of 41 fresh vegetable samples bought in Oporto Metropolitan Area (North Portugal). None of the samples contained any detectable amounts of the studied compounds.

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A new procedure for determining eleven organochlorine pesticides in soils using microwave-assisted extraction (MAE) and headspace solid phase microextraction (HS-SPME) is described. The studied pesticides consisted of mirex, α- and γ-chlordane, p,p’-DDT, heptachlor, heptachlor epoxide isomer A, γ-hexachlorocyclohexane, dieldrin, endrin, aldrine and hexachlorobenzene. The HS-SPME was optimized for the most important parameters such as extraction time, sample volume and temperature. The present analytical procedure requires a reduced volume of organic solvents and avoids the need for extract clean-up steps. For optimized conditions the limits of detection for the method ranged from 0.02 to 3.6 ng/g, intermediate precision ranged from 14 to 36% (as CV%), and the recovery from 8 up to 51%. The proposed methodology can be used in the rapid screening of soil for the presence of the selected pesticides, and was applied to landfill soil samples.

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An extraction-anodic adsorptive stripping voltammetric procedure using microwave-assisted solvent extraction and a gold ultramicroelectrode was developed for determining the pesticide ametryn in soil samples. The method is based on the use of acetonitrile as extraction solvent and on controlled adsorptive accumulation of the herbicide at the potential of 0.50 V (vs. Ag/AgCl) in the presence of Britton-Robinson buffer (pH 3.3). Soil sample extracts were analysed directly after drying and redissolution with the supporting electrolyte but without other pre-treatment. The limit of detection obtained for a 10 s collection time was 0.021 µg g-1. Recovery experiments for the global procedure, at the 0.500 µg g-1 level, gave satisfactory mean and standard deviation results which were comparable to those obtained by HPLC with UV detection.

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A procedure for the determination of seven indicator PCBs in soils and sediments using microwave-assisted extraction (MAE) and headspace solid-phase microextraction (HS-SPME) prior to GC-MS/MS is described. Optimization of the HS-SPME was carried out for the most important parameters such as extraction time, sample volume and temperature. The adopted methodology has reduced consumption of organic solvents and analysis runtime. Under the optimized conditions, the method detection limit ranged from 0.6 to 1 ng/g when 5 g of sample was extracted, the precision on real samples ranged from 4 to 21% and the recovery from 69 to 104%. The proposed method, which included the analysis of a certified reference material in its validation procedure, can be extended to several other PCBs and used in the monitoring of soil or sediments for the presence of PCBs.

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An analytical method using microwave-assisted extraction (MAE) and liquid chromatography (LC) with fluorescence detection (FD) for the determination of ochratoxin A (OTA) in bread samples is described. A 24 orthogonal composite design coupled with response surface methodology was used to study the influence of MAE parameters (extraction time, temperature, solvent volume, and stirring speed) in order to maximize OTA recovery. The optimized MAE conditions were the following: 25 mL of acetonitrile, 10 min of extraction, at 80 °C, and maximum stirring speed. Validation of the overall methodology was performed by spiking assays at five levels (0.1–3.00 ng/g). The quantification limit was 0.005 ng/g. The established method was then applied to 64 bread samples (wheat, maize, and wheat/maize bread) collected in Oporto region (Northern Portugal). OTAwas detected in 84 % of the samples with a maximum value of 2.87 ng/g below the European maximum limit established for OTA in cereal products of 3 ng/g.

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In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

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A novel reusable molecularly imprinted polymer (MIP) assembled on a polymeric layer of carboxylated poly(vinyl chloride) (PVCsingle bondCOOH) for myoglobin (Myo) detection was developed. This polymer was casted on the gold working area of a screen printed electrode (Au-SPE), creating a novel disposable device relying on plastic antibodies. Electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and Fourier transform infrared spectroscopy (FTIR) studies confirmed the surface modification. The MIP/Au-SPE devices displayed a linear behaviour in EIS from 0.852 to 4.26 μg mL−1, of positive slope 6.50 ± 1.48 (kΩ mL μg−1). The limit of detection was 2.25 μg mL−1. Square wave voltammetric (SWV) assays were made in parallel and showed linear responses between 1.1 and 2.98 μg mL−1. A current decrease was observed against Myo concentration, producing average slopes of −0.28 ± 0.038 μA mL μg−1. MIP/Au-SPE also showed good results in terms of selectivity. The error% found for each interfering species were 7% for troponin T (TnT), 11% for bovine serum albumin (BSA) and 2% for creatine kinase MB (CKMB), respectively. Overall, the technical modification over the Au-SPE was found a suitable approach for screening Myo in biological fluids.