216 research outputs found

    Towards wide-bandwidth ultra-flat FOPAs

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    Fibre optical parametric amplifiers (FOPAs) offer the potential for high gain and >100 nm bandwidth at arbitrary wavelengths for increased transmission capacity. We will cover the main principles of the FOPA and discuss our approach to obtaining broad flat gain and performance improvement via simultaneous Raman amplification

    Badger: Complexity Analysis with Fuzzing and Symbolic Execution

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    Hybrid testing approaches that involve fuzz testing and symbolic execution have shown promising results in achieving high code coverage, uncovering subtle errors and vulnerabilities in a variety of software applications. In this paper we describe Badger - a new hybrid approach for complexity analysis, with the goal of discovering vulnerabilities which occur when the worst-case time or space complexity of an application is significantly higher than the average case. Badger uses fuzz testing to generate a diverse set of inputs that aim to increase not only coverage but also a resource-related cost associated with each path. Since fuzzing may fail to execute deep program paths due to its limited knowledge about the conditions that influence these paths, we complement the analysis with a symbolic execution, which is also customized to search for paths that increase the resource-related cost. Symbolic execution is particularly good at generating inputs that satisfy various program conditions but by itself suffers from path explosion. Therefore, Badger uses fuzzing and symbolic execution in tandem, to leverage their benefits and overcome their weaknesses. We implemented our approach for the analysis of Java programs, based on Kelinci and Symbolic PathFinder. We evaluated Badger on Java applications, showing that our approach is significantly faster in generating worst-case executions compared to fuzzing or symbolic execution on their own

    Soft Robot Locomotion via Mechanical Metamaterials: Application in Pipe Inspection

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    Pipe inspections are performed using large robots that utilize wheels or tracks for locomotion. Due to their large size, weight and hard exterior, these robots can occasionally cause damage to the pipe interiors during inspection. In addition, these pipe inspection robots struggle with the ability to move in a congested environment and adapt to obstacles or geometry changes within the pipe. This project investigates the capabilities of auxetic and conventional metamaterials to achieve locomotion in an enclosed channel through the different metamaterials reactions to an axial force. The resulting robot is capable of both horizontal and vertical locomotion. Computer simulation is used to confirm the metamaterials effective Poissons ratio through testing deformation under applied loads at small displacements. Physical testing of the soft-bodied robot is employed to demonstrate the force needed for movement and validate the auxetic and conventional metamaterial behavior. The extensive work serves as a proof of concept of auxetic metamaterials as a viable solution for less invasive movement through enclosed channels. Further work and alterations to the soft-bodied robot body may allow for future applications in realms such as medical device development

    Adaptive Grey-Box Fuzz-Testing with Thompson Sampling

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    Fuzz testing, or "fuzzing," refers to a widely deployed class of techniques for testing programs by generating a set of inputs for the express purpose of finding bugs and identifying security flaws. Grey-box fuzzing, the most popular fuzzing strategy, combines light program instrumentation with a data driven process to generate new program inputs. In this work, we present a machine learning approach that builds on AFL, the preeminent grey-box fuzzer, by adaptively learning a probability distribution over its mutation operators on a program-specific basis. These operators, which are selected uniformly at random in AFL and mutational fuzzers in general, dictate how new inputs are generated, a core part of the fuzzer's efficacy. Our main contributions are two-fold: First, we show that a sampling distribution over mutation operators estimated from training programs can significantly improve performance of AFL. Second, we introduce a Thompson Sampling, bandit-based optimization approach that fine-tunes the mutator distribution adaptively, during the course of fuzzing an individual program. A set of experiments across complex programs demonstrates that tuning the mutational operator distribution generates sets of inputs that yield significantly higher code coverage and finds more crashes faster and more reliably than both baseline versions of AFL as well as other AFL-based learning approaches.Comment: Published as a workshop paper in the 11th ACM Workshop on Artificial Intelligence and Security (AISec '18) with the 25th ACM Conference on Computer and Communications Security (CCS '18

    1THz-bandwidth polarization-diverse optical phase conjugation of 10x114Gb/s DP-QPSK WDM signals

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    Polarization diverse optical phase conjugation of a 1THz spectral-band 1.14Tb/s DP-QPSK WDM multiplex is demonstrated for the first time, showing a worst case Q2 penalty of 0.9dB over all conjugate wavelengths, polarizations and OSNR

    Loneliness in men 60 years and over : the association with purpose in life

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    Loneliness as a consequence of getting older negatively impacts on the health and well-being of men as they age. Having a purpose in life may mitigate loneliness and therefore positively impact on health and well-being. Limited research into loneliness and purpose in life has been undertaken in older men. This study seeks to understand the relationship between loneliness and purpose in life in a group of older men. Using data from a cross-sectional survey of 614 men aged 60 years and over living in New Zealand, bivariate and multivariate analyses were undertaken to examine the relationship between loneliness and purpose in life using a range of demographic, health, and social connection variables. Bivariate analysis revealed that being unpartnered and having low socioeconomic status, limited social networks, low levels of participation, and mental health issues were associated with loneliness. Multivariate analysis showed that having poor mental health and lower purpose in life were indicators of loneliness. Consequently, improving mental health and purpose in life are likely to reduce loneliness in at-risk older men. As older men are a heterogeneous group from a variety of sociocultural and ethnic backgrounds, a multidimensional approach to any intervention initiatives needs to occur

    Reduction of Nonlinear Intersubcarrier Intermixing in Coherent Optical OFDM by a Fast Newton-Based Support Vector Machine Nonlinear Equalizer

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    A fast Newton-based support vector machine (N-SVM) nonlinear equalizer (NLE) is experimentally demonstrated, for the first time, in 40 Gb/s 16-quadrature amplitude modulated coherent optical orthogonal frequency division multiplexing at 2000 km of transmission. It is shown that N-SVM-NLE extends the optimum launched optical power by 2 dB compared to the benchmark Volterra-based NLE. The performance improvement by N-SVM is due to its ability of tackling both deterministic fiber-induced nonlinear effects and the interaction between nonlinearities and stochastic noises (e.g., polarization-mode dispersion). An N-SVM is more tolerant to intersubcarrier nonlinear crosstalk effects than Volterra-based NLE, especially when applied across all subcarriers simultaneously. In contrast to the conventional SVM, the proposed algorithm is of reduced classifier complexity offering lower computational load and execution time. For a low C-parameter of 4 (a penalty parameter related to complexity), an execution time of 1.6 s is required for N-SVM to effectively mitigate nonlinearities. Compared to conventional SVM, the computational load of N-SVM is ∼6 times lower

    The impact of equilibrating hemispheric albedos on tropical performance in the HadGEM2-ES coupled climate model

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    AcceptedArticle in Press©2015. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.©2015. The Authors. The Earth's hemispheric reflectances are equivalent to within±0.2Wm-2, even though the Northern Hemisphere contains a greater proportion of higher reflectance land areas, because of greater cloud cover in the Southern Hemisphere. This equivalence is unlikely to be by chance, but the reasons are open to debate. Here we show that equilibrating hemispheric albedos in the Hadley Centre Global Environment Model version 2-Earth System coupled climate model significantly improves what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases over all continental land areas, the penetration of monsoon rainfall across the Sahel, the West African monsoon "jump", and indicators of hurricane frequency are all significantly improved. Mechanistically, equilibrating hemispheric albedos improves the atmospheric cross-equatorial energy transport and increases the supply of tropical atmospheric moisture to the Hadley cell. We conclude that an accurate representation of the cross-equatorial energy transport appears to be critical if tropical performance is to be improved

    Experimental demonstration of data-dependent pilot-aided phase noise estimation for CO-OFDM

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    We demonstrate a novel phase noise estimation scheme for CO-OFDM, in which pilot subcarriers are deliberately correlated to the data subcarriers. This technique reduces the overhead by a factor of 2

    Typestate-Guided Fuzzer for Discovering Use-after-Free Vulnerabilities

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    © 2020 Association for Computing Machinery. Existing coverage-based fuzzers usually use the individual control flow graph (CFG) edge coverage to guide the fuzzing process, which has shown great potential in finding vulnerabilities. However, CFG edge coverage is not effective in discovering vulnerabilities such as use-after-free (UaF). This is because, to trigger UaF vulnerabilities, one needs not only to cover individual edges, but also to traverse some (long) sequence of edges in a particular order, which is challenging for existing fuzzers. To this end, we propose to model UaF vulnerabilities as typestate properties, and develop a typestateguided fuzzer, named UAFL, for discovering vulnerabilities violating typestate properties. Given a typestate property, we first perform a static typestate analysis to find operation sequences potentially violating the property. Our fuzzing process is then guided by the operation sequences in order to progressively generate test cases triggering property violations. In addition, we also employ an information flow analysis to improve the efficiency of the fuzzing process. We have performed a thorough evaluation of UAFL on 14 widely-used real-world programs. The experiment results show that UAFL substantially outperforms the state-of-the-art fuzzers, including AFL, AFLFast, FairFuzz, MOpt, Angora and QSYM, in terms of the time taken to discover vulnerabilities. We have discovered 10 previously unknown vulnerabilities, and received 5 new CVEs
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