45 research outputs found

    Hybrid multicriteria fuzzy classification of network traffic patterns, anomalies, and protocols

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    © 2017, Springer-Verlag London Ltd., part of Springer Nature. Traffic classification in computer networks has very significant roles in network operation, management, and security. Examples include controlling the flow of information, allocating resources effectively, provisioning quality of service, detecting intrusions, and blocking malicious and unauthorized access. This problem has attracted a growing attention over years and a number of techniques have been proposed ranging from traditional port-based and payload inspection of TCP/IP packets to supervised, unsupervised, and semi-supervised machine learning paradigms. With the increasing complexity of network environments and support for emerging mobility services and applications, more robust and accurate techniques need to be investigated. In this paper, we propose a new supervised hybrid machine-learning approach for ubiquitous traffic classification based on multicriteria fuzzy decision trees with attribute selection. Moreover, our approach can handle well the imbalanced datasets and zero-day applications (i.e., those without previously known traffic patterns). Evaluating the proposed methodology on several benchmark real-world traffic datasets of different nature demonstrated its capability to effectively discriminate a variety of traffic patterns, anomalies, and protocols for unencrypted and encrypted traffic flows. Comparing with other methods, the performance of the proposed methodology showed remarkably better classification accuracy

    Thermal Properties of Graphene, Carbon Nanotubes and Nanostructured Carbon Materials

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    Recent years witnessed a rapid growth of interest of scientific and engineering communities to thermal properties of materials. Carbon allotropes and derivatives occupy a unique place in terms of their ability to conduct heat. The room-temperature thermal conductivity of carbon materials span an extraordinary large range - of over five orders of magnitude - from the lowest in amorphous carbons to the highest in graphene and carbon nanotubes. I review thermal and thermoelectric properties of carbon materials focusing on recent results for graphene, carbon nanotubes and nanostructured carbon materials with different degrees of disorder. A special attention is given to the unusual size dependence of heat conduction in two-dimensional crystals and, specifically, in graphene. I also describe prospects of applications of graphene and carbon materials for thermal management of electronics.Comment: Review Paper; 37 manuscript pages; 4 figures and 2 boxe

    Tuning the Seebeck coefficient of naphthalenediimide by electrochemical gating and doping

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    We investigate the sign and magnitude of the single-molecule Seebeck coefficient of naphthalenediimide (NDI) under the influence of electrochemical gating and doping. The molecule consists of a NDI core with two alkyl chains in the bay-area position, connected to gold electrodes via benzothiophene (DBT) anchor groups. By switching between the neutral, radical and di-anion charge states, we are able to tune the molecular energy levels relative to the Fermi energy of the electrodes. The resulting single-molecule room-temperature Seebeck coefficents of the three charge states are -294.5 μV K(-1), 122 μV K(-1) and 144 μV K(-1) respectively and the room-temperature power factors are 4.4 × 10(-5) W m(-1) K(-2), 3 × 10(-5) W m(-1) K(-2) and 8.2 × 10(-4) W m(-1) K(-2). As a further strategy for optimising thermoelectric properties, we also investigate the effect on both phonon and electron transport of doping the NDI with either an electron donor (TTF) or an electron acceptor (TCNE). We find that doping by TTF increases the room-temperature Seebeck coefficient and power factor from -73.7 μV K(-1) and 2.6 × 10(-7) W m(-1) K(-2) for bare NDI to -105 μV K(-1) and 3.6 × 10(-4) W m(-1) K(-2) in presence of TTF. The low thermal conductance of NDI-TTF, combined with the higher Seebeck coefficient and higher electrical conductance lead to a maximum thermoelectric figure of merit of ZT = 1.2, which is higher than that of bare NDI in several orders of magnitude. This demonstrates that both the sign and magnitude of NDI Seebeck coefficient can be tuned reversibly by electrochemical gating and doping, suggesting that such redox active molecules are attractive materials for ultra-thin-film thermoelectric devices

    Network Geometry and Complexity

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    (28 pages, 11 figures)Higher order networks are able to characterize data as different as functional brain networks, protein interaction networks and social networks beyond the framework of pairwise interactions. Most notably higher order networks include simplicial complexes formed not only by nodes and links but also by triangles, tetrahedra, etc. More in general, higher-order networks can be cell-complexes formed by gluing convex polytopes along their faces. Interestingly, higher order networks have a natural geometric interpretation and therefore constitute a natural way to explore the discrete network geometry of complex networks. Here we investigate the rich interplay between emergent network geometry of higher order networks and their complexity in the framework of a non-equilibrium model called Network Geometry with Flavor. This model, originally proposed for capturing the evolution of simplicial complexes, is here extended to cell-complexes formed by subsequently gluing different copies of an arbitrary regular polytope. We reveal the interplay between complexity and geometry of the higher order networks generated by the model by studying the emergent community structure and the degree distribution as a function of the regular polytope forming its building blocks. Additionally, we discuss the underlying hyperbolic nature of the emergent geometry and we relate the spectral dimension of the higher-order network to the dimension and nature of its building blocks

    A review of communication-oriented optical wireless systems

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    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat
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