Efficient memory management in VOD disk array servers usingPer-Storage-Device buffering

We present a buffering technique that reduces video-on-demand server memory requirements in more than one order of magnitude. This technique, Per-Storage-Device Buffering (PSDB), is based on the allocation of a fixed number of buffers per storage device, as opposed to existing solutions based on per-stream buffering allocation. The combination of this technique with disk array servers is studied in detail, as well as the influence of Variable Bit Streams. We also present an interleaved data placement strategy, Constant Time Length Declustering, that results in optimal performance in the service of VBR streams. PSDB is evaluated by extensive simulation of a disk array server model that incorporates a simulation based admission test.This research was supported in part by the National R&D Program of Spain, Project Number TIC97-0438.Publicad

Implementation of a Hardware/Software Platform for Real-Timedata-Intensive Applications in Hazardous Environments

Real-Time Technology and Applications Symposium. Brookline, MA, USA, 10-12 Oct. 1996In real-time data-intensive applications, the simultaneous achievement of the required performance and determinism is a difficult issue to address, mainly due to the time needed to perform I/O operations, which is more significant than the CPU processing time. Additional features need to be considered if these applications are intended to perform in hostile environments. In this paper, we address the implementation of a hardware/software platform designed to acquire, transfer, process and store massive amounts of information at sustained rates of several MBytes/sec, capable of supporting real-time applications with stringent throughput requirements under hazardous environmental conditions. A real-world system devoted to the inspection of nuclear power plants is presented as an illustrative examplePublicad

A comprehensive approach in performance evaluation for modernreal-time operating systems

In real-time computing the accurate characterization of the performance and determinism that a particular real-time operating system/hardware combination can provide for real-time applications is essential. This issue is not properly addressed by existing performance metrics mainly due to the lack of completeness and generalization. In this paper we present a set of comprehensive, easy-to-implement and useful metrics covering three basic real-time operating system features: response to external events, intertask synchronization and resource sharing, and intertask data transferring. The evaluation of real-time operating systems using a set of fine-grained metrics is fundamental to guarantee that we can reach the required determinism in real-world applications.Publicad

Environmental Sensor Anomaly Detection Using Learning Machines

The problem of quality assurance/quality control (QA/QC) for real-time measurements of environmental and water quality variables has been a field explored by many in recent years. The use of in situ sensors has become a common practice for acquiring real-time measurements that provide the basis for important natural resources management decisions. However, these sensors are susceptible to failure due to such things as human factors, lack of necessary maintenance, flaws on the transmission line or any part of the sensor, and unexpected changes in the sensors\u27 surrounding conditions. Two types of machine learning techniques were used in this study to assess the detection of anomalous data points on turbidity readings from the Paradise site on the Little Bear River, in northern Utah: Artificial Neural Networks (ANNs) and Relevance Vector Machines (RVMs). ANN and RVM techniques were used to develop regression models capable of predicting upcoming Paradise site turbidity measurements and estimating confidence intervals associated with those predictions, to be later used to determine if a real measurement is an anomaly. Three cases were identified as important to evaluate as possible inputs for the regression models created: (1) only the reported values from the sensor from previous time steps, (2) reported values from the sensor from previous time steps and values of other water types of sensors from the same site as the target sensor, and (3) adding as inputs the previous readings from sensors from upstream sites. The decision of which of the models performed the best was made based on each model\u27s ability to detect anomalous data points that were identified in a QA/QC analysis that was manually performed by a human technician. False positive and false negative rates for a range of confidence intervals were used as the measure of performance of the models. The RVM models were able to detect more anomalous points within narrower confidence intervals than the ANN models. At the same time, it was shown that incorporating as inputs measurements from other sensors at the same site as well as measurements from upstream sites can improve the performance of the models

Enhanced magnetocaloric response in Cr/Mo containing Nanoperm-type amorphous alloys

The magnetocaloric effect of Fe76Cr8−xMoxCu1B15 (x =0,4) alloys is studied. Although the combined addition of Cr and Mo is more efficient in tuning the Curie temperature of the alloy, the Mo-free alloy presents a higher magnetocaloric response. The refrigerant capacity (RC) for the Mo-containing alloy is comparable to that of Gd5Ge1.9Si2Fe0.1 (for a field of 50 kOe, RC = 273 J kg−1 for the Mo alloy vs 240 J kg−1 for the Gd-based one), with a larger temperature span of the optimal refrigeration cycle (250 K vs 90 K, respectively). The restriction of the temperature span to 90 K gives RC = 187 J kg−1 for the Mo alloy. A master curve behavior for the magnetic entropy change is also evidenced

On the use of JMAK theory to describe mechanical amorphization: a comparison between experiments, numerical solutions and simulations

The kinetics of amorphization during ball milling is generally analyzed using two different approaches: the classical Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory and Delogu and Cocco’s model for which a region deterministically transforms after it reaches a certain number of collisions. The application of JMAK analysis to the latter model predicts Avrami exponents to be higher than the experimental ones (typically close to one). We develop simulations based on the probabilistic character of the nucleation phenomenon and concave growth of the amorphous phase in the core of a nanocrystal. The predictions of our simulations are in good agreement with the low Avrami exponents and with the size evolution of the remaining crystallites found experimentally. From these values, the parameters involved in the simulated model (growth rate and probability of nucleation) can be estimated.AEI/FEDER-UE (Project MAT-2016-77265-R)Junta de Andalucía (Grupo PAI

Exploring the S-Matrix of Massless Particles

We use the recently proposed generalised on-shell representation for scattering amplitudes and a consistency test to explore the space of tree-level consistent couplings in four-dimensional Minkowski spacetime. The extension of the constructible notion implied by the generalised on-shell representation, i.e. the possibility to reconstruct at tree level all the scattering amplitudes from the three-particle ones, together with the imposition of the consistency conditions at four-particle level, allow to rediscover all the known theories and their algebra structure, if any. Interestingly, this analysis seems to leave room for high-spin couplings, provided that at least the requirement of locality is weakened. We do not claim to have found tree-level consistent high-spin theories, but rather that our methods show signatures of them and very likely, with a suitable modification, they can be a good framework to perform a systematic search.Comment: 44 pages, 1 figur

Influence of Milling Time on the Homogeneity and Magnetism of a Fe70Zr30 Partially Amorphous Alloy: Distribution of Curie Temperatures

In this work, the mechanically alloyed Fe70Zr30 (at. %) composition has been used to study the influence of milling time on its homogeneity and magnetic properties. The microstructure and Fe environment results show the formation of an almost fully amorphous alloy after 50 h of milling in a mixture of pure 70 at. % Fe and 30 at. % Zr. The soft magnetic behavior of the samples enhances with the increase of the milling time, which is ascribed to the averaging out of the magnetocrystalline anisotropy as the crystal size decreases and the amorphous fraction increases. The formation of a non-perfectly homogenous system leads to a certain compositional heterogeneity, motivating the existence of a distribution of Curie temperatures. The parameters of the distribution (the average Curie temperature, T C ¯ , and the broadening of the distribution, ∆ T C ) have been obtained using a recently reported procedure, based on the analysis of the approach towards the saturation curves and the magnetocaloric effect. The decrease of ∆ T C and the increase of T C ¯ with the milling time are in agreement with the microstructural results. As the remaining α-Fe phase decreases, the amorphous matrix is enriched in Fe atoms, enhancing its magnetic response.AEI/FEDER-UE Project MAT 2016-77265-

Magnetic permeability of ( Fe Co Ge ) 88 Zr 6 B 5 Cu 1 alloys: Thermal stability in a wide temperature range.

Temperature dependence, from room temperature up to 1000 K, of the initial permeability of Fe83−xCoxGe5Zr6B5Cu1 x=5 and 20 alloys at different stages of devitrification is reported. As nanocrystallization progresses, room temperature decreases but high temperature one increases, leading to an improvement of its thermal stability extended from room temperature up to 915 K, characterized by a temperature coefficient of permeability 0.1%/K 4000 and 0.04%/K 800 for 5 and 20 at. % Co containing alloys, respectively