962 resultados para predicting and alert system
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In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.
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A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and surveillance programs for antimicrobial resistance.
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NA61/SHINE (SPS Heavy Ion and Neutrino Experiment) is a multi-purpose experimental facility to study hadron production in hadron-proton, hadron-nucleus and nucleus-nucleus collisions at the CERN Super Proton Synchrotron. It recorded the first physics data with hadron beams in 2009 and with ion beams (secondary 7Be beams) in 2011. NA61/SHINE has greatly profited from the long development of the CERN proton and ion sources and the accelerator chain as well as the H2 beamline of the CERN North Area. The latter has recently been modified to also serve as a fragment separator as needed to produce the Be beams for NA61/SHINE. Numerous components of the NA61/SHINE set-up were inherited from its predecessors, in particular, the last one, the NA49 experiment. Important new detectors and upgrades of the legacy equipment were introduced by the NA61/SHINE Collaboration. This paper describes the state of the NA61/SHINE facility — the beams and the detector system — before the CERN Long Shutdown I, which started in March 2013.
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East Africa’s Lake Victoria provides resources and services to millions of people on the lake’s shores and abroad. In particular, the lake’s fisheries are an important source of protein, employment, and international economic connections for the whole region. Nonetheless, stock dynamics are poorly understood and currently unpredictable. Furthermore, fishery dynamics are intricately connected to other supporting services of the lake as well as to lakeshore societies and economies. Much research has been carried out piecemeal on different aspects of Lake Victoria’s system; e.g., societies, biodiversity, fisheries, and eutrophication. However, to disentangle drivers and dynamics of change in this complex system, we need to put these pieces together and analyze the system as a whole. We did so by first building a qualitative model of the lake’s social-ecological system. We then investigated the model system through a qualitative loop analysis, and finally examined effects of changes on the system state and structure. The model and its contextual analysis allowed us to investigate system-wide chain reactions resulting from disturbances. Importantly, we built a tool that can be used to analyze the cascading effects of management options and establish the requirements for their success. We found that high connectedness of the system at the exploitation level, through fisheries having multiple target stocks, can increase the stocks’ vulnerability to exploitation but reduce society’s vulnerability to variability in individual stocks. We describe how there are multiple pathways to any change in the system, which makes it difficult to identify the root cause of changes but also broadens the management toolkit. Also, we illustrate how nutrient enrichment is not a self-regulating process, and that explicit management is necessary to halt or reverse eutrophication. This model is simple and usable to assess system-wide effects of management policies, and can serve as a paving stone for future quantitative analyses of system dynamics at local scales.
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Referred to as orthographic depth, the degree of consistency of grapheme/phoneme correspondences varies across languages from high in shallow orthographies to low in deep orthographies. The present study investigates the impact of orthographic depth on reading route by analyzing evoked potentials to words in a deep (French) and shallow (German) language presented to highly proficient bilinguals. ERP analyses to German and French words revealed significant topographic modulations 240-280ms post-stimulus onset, indicative of distinct brain networks engaged in reading over this time window. Source estimations revealed that these effects stemmed from modulations of left insular, inferior frontal and dorsolateral regions (German>French) previously associated to phonological processing. Our results show that reading in a shallow language was associated to a stronger engagement of phonological pathways than reading in a deep language. Thus, the lexical pathways favored in word reading are reinforced by phonological networks more strongly in the shallow than deep orthography.
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We describe radial-velocity time series obtained by HARPS on the 3.60 m telescope in La Silla (ESO, Chile) over ten years and report the discovery of five new giant exoplanets in distant orbits; these new planets orbit the stars HD 564, HD 30669, HD 108341, and BD -114672. Their periods range from 492 to 1684 days, semi-major axes range from 1.2 to 2.69 AU, and eccentricities range from 0 to 0.85. Their minimum mass ranges from 0.33 to 3.5 MJup. We also refine the parameters of two planets announced previously around HD 113538, based on a longer series of measurements. The planets have a period of 663 ± 8 and 1818 ± 25 days, orbital eccentricities of 0.14 ± 0.08 and 0.20 ± 0.04, and minimum masses of 0.36 ± 0.04 and 0.93 ± 0.06 MJup. Finally, we report the discovery of a new hot-Jupiter planet around an active star, HD 103720; the planet has a period of 4.5557 ± 0.0001 days and a minimum mass of 0.62 ± 0.025 MJup. We discuss the fundamental parameters of these systems and limitations due to stellar activity in quiet stars with typical 2 m s-1 radial velocity precision.
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by B. Martin
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Objective. In 2003, the State of Texas instituted the Driver Responsibility Program (TDRP), a program consisting of a driving infraction point system coupled with a series of graded fines and annual surcharges for specific traffic violations such as driving while intoxicated (DWI). Approximately half of the revenues generated are earmarked to be disbursed to the state's trauma system to cover uncompensated trauma care costs. This study examined initial program implementation, the impact of trauma system funding, and initial impact on impaired driving knowledge, attitudes and behaviors. A model for targeted media campaigns to improve the program's deterrence effects was developed. ^ Methods. Data from two independent driver survey samples (conducted in 1999 and 2005), department of public safety records, state health department data and a state auditor's report were used to evaluate the program's initial implementation, impact and outcome with respect to drivers' impaired driving knowledge, attitudes and behavior (based on constructs of social cognitive theory) and hospital uncompensated trauma care funding. Survey results were used to develop a regression model of high risk drivers who should be targeted to improve program outcome with respect to deterring impaired driving. ^ Results. Low driver compliance with fee payment (28%) and program implementation problems were associated with lower surcharge revenues in the first two years ($59.5 million versus $525 million predicted). Program revenue distribution to trauma hospitals was associated with a 16% increase in designated trauma centers. Survey data demonstrated that only 28% of drivers are aware of the TDRP and that there has been no initial impact on impaired driving behavior. Logistical regression modeling suggested that target media campaigns highlighting the likelihood of DWI detection by law enforcement and the increased surcharges associated with the TDRP are required to deter impaired driving. ^ Conclusions. Although the TDRP raised nearly $60 million in surcharge revenue for the Texas trauma system over the first two years, this study did not find evidence of a change in impaired driving knowledge, attitudes or behaviors from 1999 to 2005. Further research is required to measure whether the program is associated with decreased alcohol-related traffic fatalities. ^
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Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.