22,327 research outputs found

    A Wideband Direct Data Domain Genetic Algorithm Beamforming

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    In this paper, a wideband direct data-domain genetic algorithm beamforming is presented. Received wideband signals are decomposed to a set of narrow sub-bands using fast Fourier transform. Each sub-band is transformed to a reference frequency using the steering vector transformation. So, narrowband approaches could be used for any of these sub-bands. Hence, the direct data-domain genetic algorithm beamforming can be used to form a single ‘hybrid’ beam pattern with sufficiently deep nulls in order to separate and reconstruct frequency components of the signal of interest efficiently. The proposed approach avoids most of drawbacks of already-existing statistical and gradient-based approaches since formation of a covariance matrix is not needed, and a genetic algorithm is used to solve the beamforming problem

    Nongrey radiation effects on the boundary layer of an absorbing gas over a flat plate

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    Nongrey radiation effects on boundary layer of absorbing gas over flat plat

    Deep Loving - The Friend of Deep Learning

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    Artificial Intelligence and Deep Learning are good fields of research. Recently, the brother of Artificial Intelligence titled "Artificial Satisfaction" was introduced in literature [10]. In this article, we coin the term 201C;Deep Loving201D;. After the publication of this article, "Deep Loving" will be considered as the friend of Deep Learning. Proposing a new field is different from proposing a new algorithm. In this paper, we strongly focus on defining and introducing "Deep Loving Field" to Research Scientists across the globe. The future of the "Deep Loving" field is predicted by showing few future opportunities in this new field. The definition of Deep Learning is shown followed by a literature review of the "Deep Loving" field. The World's First Deep Loving Algorithm (WFDLA) is designed and implemented in this work by adding Deep Loving concepts to Particle Swarm Optimization Algorithm. Results obtained by WFDLA are compared with the PSO algorithm

    Evaluation of the BD GeneOhm MRSA and VanR Assays as a Rapid Screening Tool for Detection of Methicillin-Resistant Staphylococcus aureus and Vancomycin-Resistant Enterococci in a Tertiary Hospital in Saudi Arabia

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    Objectives. The aim of this study was to evaluate the diagnostic performance of BD GeneOhm VanR Assay, a rapid PCR test that detects the presence of vanA and/or vanB genes and the performance of BDGeneOhm MRSA Assay which detects the staphylococcal cassette chromosomemec (SCCmec cassette) carrying the mecA gene and Staphylococcus aureus specific sequence located within the orfX gene. Methods. 300 duplicate rectal swabs collected consecutively were analyzed for the presence of VRE by culture and BD PCR. 2267 duplicate swabs were collected (728 nasal and 1539 groin swabs) and analyzed for the presence of MRSA by culture method and BD PCR. Results. Compared to culture, the BD GeneOhm VanR Assay showed a sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 100%, 91.1%, 23.5%, and 100%, respectively. The BD GeneOhm MRSA Assay revealed sensitivity, specificity, PPV, and NPV of 97.2%, 99.4%, 89.7%, and 99.9%, respectively, for nasal swabs. For groin swabs, it was 100%, 98.7%, 61.5% and 100%, respectively. Conclusion. The BD GeneOhm vanR Assay is a good screening test for rapid exclusion of VRE carriers in hospitals. The BD GeneOhm MRSA Assay represents a reliable screening test. The true strength of the BD GeneOhm Assay for MRSA and VRE is its exceptionally high NPV making the test an ideal tool for rapid exclusion of MRSA and VRE carriers in hospitals. As a consequence, this would dramatically shorten the patient isolation time
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