124 resultados para time analysis


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11th IEEE World Conference on Factory Communication Systems (WFCS 2015). 27 to 29, May, 2015, TII-SS-2: Scheduling and Performance Analysis. Palma de Mallorca, Spain.

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Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

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23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2015). 4 to 6, Mar, 2015. Turku, Finland.

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In this paper, we propose the Distributed using Optimal Priority Assignment (DOPA) heuristic that finds a feasible partitioning and priority assignment for distributed applications based on the linear transactional model. DOPA partitions the tasks and messages in the distributed system, and makes use of the Optimal Priority Assignment (OPA) algorithm known as Audsley’s algorithm, to find the priorities for that partition. The experimental results show how the use of the OPA algorithm increases in average the number of schedulable tasks and messages in a distributed system when compared to the use of Deadline Monotonic (DM) usually favoured in other works. Afterwards, we extend these results to the assignment of Parallel/Distributed applications and present a second heuristic named Parallel-DOPA (P-DOPA). In that case, we show how the partitioning process can be simplified by using the Distributed Stretch Transformation (DST), a parallel transaction transformation algorithm introduced in [1].

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Article in Press, Corrected Proof

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This paper applies multidimensional scaling techniques and Fourier transform for visualizing possible time-varying correlations between 25 stock market values. The method is useful for observing clusters of stock markets with similar behavior.

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This paper studies periodic gaits of multi-legged locomotion systems based on dynamic models. The purpose is to determine the system performance during walking and the best set of locomotion variables. For that objective the prescribed motion of the robot is completely characterized in terms of several locomotion variables such as gait, duty factor, body height, step length, stroke pitch, foot clearance, legs link lengths, foot-hip offset, body and legs mass and cycle time. In this perspective, we formulate three performance measures of the walking robot namely, the mean absolute energy, the mean power dispersion and the mean power lost in the joint actuators per walking distance. A set of model-based experiments reveals the influence of the locomotion variables in the proposed indices.

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4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications

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Presented at 21st IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2015). 19 to 21, Aug, 2015, pp 122-131. Hong Kong, China.

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The robotics community is concerned with the ability to infer and compare the results from researchers in areas such as vision perception and multi-robot cooperative behavior. To accomplish that task, this paper proposes a real-time indoor visual ground truth system capable of providing accuracy with at least more magnitude than the precision of the algorithm to be evaluated. A multi-camera architecture is proposed under the ROS (Robot Operating System) framework to estimate the 3D position of objects and the implementation and results were contextualized to the Robocup Middle Size League scenario.

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Presented at IEEE 21st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2015). 19 to 21, Aug, 2015.

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Presented at IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

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Presented at IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

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In this study a citrate-buffered version of QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method for determination of 14 organochlorine pesticides (OCPs) residues in tamarind peel, fruit and commercial pulp was optimized using gas chromatography (GC) coupled with electron-capture detector (ECD) and confirmation by GC tandem mass spectrometry (GC–MS/MS). Five procedures were tested based on the original QuEChERS method. The best one was achieved with increased time in ultrasonic bath. For the extract clean-up, primary secondary amine (PSA), octadecyl-bonded silica (C18) and magnesium sulphate (MgSO4) were used as sorbents for tamarind fruit and commercial pulp and for peel was also added graphitized carbon black (GCB). The samples mass was optimized according to the best recoveries (1.0 g for peel and fruit; 0.5 g for pulp). The method results showed the matrix-matched calibration curve linearity was r2 > 0.99 for all target analytes in all samples. The overall average recoveries (spiked at 20, 40 and 60 μg kg−1) have been considered satisfactory presenting values between 70 and 115% with RSD of 2–15 % (n = 3) for all analytes, with the exception of HCB (in peel sample). The ranges of limits of detection (LOD) and quantification (LOQ) for OCPs were for peel (LOD: 8.0–21 μg kg−1; LOQ: 27–98 μg kg−1); for fruit (LOD: 4–10 μg kg−1; LOQ: 15–49 μg kg−1) and for commercial pulp (LOD: 2–5 μg kg−1; LOQ: 7–27 μg kg−1). The method was successfully applied in tamarind samples being considered a rapid, sensitive and reliable procedure.

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The recent technological advancements and market trends are causing an interesting phenomenon towards the convergence of High-Performance Computing (HPC) and Embedded Computing (EC) domains. On one side, new kinds of HPC applications are being required by markets needing huge amounts of information to be processed within a bounded amount of time. On the other side, EC systems are increasingly concerned with providing higher performance in real-time, challenging the performance capabilities of current architectures. The advent of next-generation many-core embedded platforms has the chance of intercepting this converging need for predictable high-performance, allowing HPC and EC applications to be executed on efficient and powerful heterogeneous architectures integrating general-purpose processors with many-core computing fabrics. To this end, it is of paramount importance to develop new techniques for exploiting the massively parallel computation capabilities of such platforms in a predictable way. P-SOCRATES will tackle this important challenge by merging leading research groups from the HPC and EC communities. The time-criticality and parallelisation challenges common to both areas will be addressed by proposing an integrated framework for executing workload-intensive applications with real-time requirements on top of next-generation commercial-off-the-shelf (COTS) platforms based on many-core accelerated architectures. The project will investigate new HPC techniques that fulfil real-time requirements. The main sources of indeterminism will be identified, proposing efficient mapping and scheduling algorithms, along with the associated timing and schedulability analysis, to guarantee the real-time and performance requirements of the applications.