Inferring Temporal Behaviours Through Kernel Tracing

In order to provide reliable system support for real-time applications, it is often important to be able to collect statistics about the tasks temporal behaviours (in terms of execution times and inter-arrival times). Such statistics can, for example, be used to provide a-priori schedulability guarantees, or to perform some kind of on-line adaptation of the scheduling parameters (adaptive scheduling, or feedback scheduling). This work shows how the Linux kernel allows to collect such statistics by using an internal function tracer called Ftrace. Based on this feature, tools can be developed to evaluate the real-time performance of a system or an application, to debug real-time applications, and/or to infer the temporal properties (for example, periodicity) of tasks running in the system

An Improved Excitation Matching Method based on an Ant Colony Optimization for Suboptimal-Free Clustering in Sum-Difference Compromise Synthesis

Dealing with an excitation matching method, this paper presents a global optimization strategy for the optimal clustering in sum-difference compromise linear arrays. Starting from a combinatorial formulation of the problem at hand, the proposed technique is aimed at determining the sub-array configuration expressed as the optimal path inside a directed acyclic graph structure modelling the solution space. Towards this end, an ant colony metaheuristic is used to benefit of its hill-climbing properties in dealing with the non-convexity of the sub-arraying as well as in managing graph searches. A selected set of numerical experiments are reported to assess the efficiency and current limitations of the ant-based strategy also in comparison with previous local combinatorial search methods. (c) 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Ant Colony Based Hybrid Approach for Optimal Compromise Sum-Difference Patterns Synthesis

Dealing with the synthesis of monopulse array antennas, many stochastic optimization algorithms have been used for the solution of the so-called optimal compromise problem between sum and difference patterns when sub-arrayed feed networks are considered. More recently, hybrid approaches, exploiting the convexity of the functional with respect to a sub-set of the unknowns (i.e., the sub-array excitation coefficients) have demonstrated their effectiveness. In this letter, an hybrid approach based on the Ant Colony Optimization (ACO) is proposed. At the first step, the ACO is used to define the sub-array membership of the array elements, while, at the second step, the sub-array weights are computed by solving a convex programming problem. The definitive version is available at www3.interscience.wiley.co

Computationally-Effective Optimal Excitation Matching for the Synthesis of Large Monopulse Arrays

Antenna arrays able to generate two different patterns are widely used in tracking radar systems [1]. Optimal (in the Dolph�]Chebyshev sense) sum [2] and difference patterns [3] can be generated by using two independent feed networks. Unfortunately, such a situation generally turns out to be impracticable because of its costs, the occupied physical space, the circuit complexity, and electromagnetic interferences. Thus, starting from the optimal sum pattern a sub�]optimal solution for the difference pattern is usually synthesized by means of the sub�]array technique. The array elements are grouped in sub�]arrays properly weighted for matching the constrains of the difference beam. Finding the best elements grouping and the sub�]array weights is a complex and challenging research topic, especially when dealing with large arrays. As far as linear arrays are concerned, McNamara proposed in [4] an analytical method for determining the �gbest compromise�h difference pattern. Unfortunately, when the ratio between the elements of the array and sub�]arrays increases, such a technique exhibits several limitations mainly due to the ill�]conditioning of the problem and the computational costs due to exhaustive evaluations. A non�]negligible saving might be achieved by applying optimization algorithms (see for instance [5] and [6]) aimed at minimizing a suitable cost function. Notwithstanding, optimization�]based approaches still appear computationally expensive when dealing with large arrays because of wide dimension of solution space to be sampled. In order to properly deal with these computational issues, this contribution presents an innovative approach based on an optimal excitation matching procedure. By exploiting the relationship between independently�]optimal sum and difference patterns, the dimension of the solution space is considerably reduced and efficiently sampled by taking into account the presence of array elements more suitable to change sub�]array membership. In the following, the proposed technique is described pointing out, through a representative case, its potentialities and effectiveness in dealing with large arrays. This is the author's version of the final version available at IEEE

An innovative approach based on a tree-searching algorithm for the optimal matching of independently optimum sum and difference excitations

An innovative approach for the optimal matching of independently optimum sum and difference patterns through sub-arrayed monopulse linear arrays is presented. By exploiting the relationship between the independently optimal sum and difference excitations, the set of possible solutions is considerably reduced and the synthesis problem is recast as the search of the best solution in a non-complete binary tree. Towards this end, a fast resolution algorithm that exploits the presence of elements more suitable to charge sub-array membership is presented. The results of a set of numerical experiments are reported in order to validate the proposed approach pointing out its effectiveness also in comparison with state-of-the-art optimal matching techniques. (c) 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Hybrid Approach for Sub-arrayed Monopulse Antenna Synthesis

A computationally effective hybrid approach to define the “optimal” compromise between sum and difference patterns in monopulse arrays is presented. Firstly, the partitioning into sub-arrays is performed by exploiting the knowledge of independently optimal sum and difference excitations. Then, the sub-array gains are computed by means of a gradient-based procedure, which takes advantage from the convexity of the problem at hand. Selected results are shown and compared with those from state-of-the-art methods in dealing with representative test cases. This paper is a postprint of a paper submitted to and accepted for publication in Electronics Letters and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library

Mapping of Aedes albopictus abundance at a local scale in Italy

Given the growing risk of arbovirus outbreaks in Europe, there is a clear need to better describe the distribution of invasive mosquito species such as Aedes albopictus. Current challenges consist in simulating Ae. albopictus abundance, rather than its presence, and mapping its simulated abundance at a local scale to better assess the transmission risk of mosquito-borne pathogens and optimize mosquito control strategy. During 2014–2015, we sampled adult mosquitoes using 72 BG-Sentinel traps per year in the provinces of Belluno and Trento, Italy. We found that the sum of Ae. albopictus females collected during eight trap nights from June to September was positively related to the mean temperature of the warmest quarter and the percentage of artificial areas in a 250 m buffer around the sampling locations. Maps of Ae. albopictus abundance simulated from the most parsimonious model in the study area showed the largest populations in highly artificial areas with the highest summer temperatures, but with a high uncertainty due to the variability of the trapping collections. Vector abundance maps at a local scale should be promoted to support stakeholders and policy-makers in optimizing vector surveillance and control

QoS Support in the X11 Window Systems

Abstract In this paper, we consider the problem of providing QoS guarantees to the execution of applications using the X11 window system. In particular, we offer a system level analysis of the issues encountered when using X11 to serve realtime applications. By using a tracer developed for the purpose we analyse in depth the internal behaviour of the system

A Selective Sweep on a Deleterious Mutation in CPT1A in Arctic Populations.

Arctic populations live in an environment characterized by extreme cold and the absence of plant foods for much of the year and are likely to have undergone genetic adaptations to these environmental conditions in the time they have been living there. Genome-wide selection scans based on genotype data from native Siberians have previously highlighted a 3 Mb chromosome 11 region containing 79 protein-coding genes as the strongest candidates for positive selection in Northeast Siberians. However, it was not possible to determine which of the genes might be driving the selection signal. Here, using whole-genome high-coverage sequence data, we identified the most likely causative variant as a nonsynonymous G>A transition (rs80356779; c.1436C>T [p.Pro479Leu] on the reverse strand) in CPT1A, a key regulator of mitochondrial long-chain fatty-acid oxidation. Remarkably, the derived allele is associated with hypoketotic hypoglycemia and high infant mortality yet occurs at high frequency in Canadian and Greenland Inuits and was also found at 68% frequency in our Northeast Siberian sample. We provide evidence of one of the strongest selective sweeps reported in humans; this sweep has driven this variant to high frequency in circum-Arctic populations within the last 6-23 ka despite associated deleterious consequences, possibly as a result of the selective advantage it originally provided to either a high-fat diet or a cold environment.This research was supported by ERC Starting Investigator grant (FP7 - 261213) to T.K. http://erc.europa.eu/. CTS, YX, QA and MS were supported by the Wellcome Trust (098051). TA was supported by The Wellcome Trust (WT100066MA). M.M and R.V. were supported by EU ERDF Centre of Excellence in Genomics to EBC; T.K, M.M and R.V. by Estonian Institutional Research grant (IUT24-1), and M.M by Estonian Science Foundation (grant 8973).This is the accepted manuscript. The final version is available from Cell/Elsevier at http://www.cell.com/ajhg/abstract/S0002-9297%2814%2900422-4