660 research outputs found

    Constrained Optimization Based Adversarial Example Generation for Transfer Attacks in Network Intrusion Detection Systems

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    Deep learning has enabled network intrusion detection rates as high as 99.9% for malicious network packets without requiring feature engineering. Adversarial machine learning methods have been used to evade classifiers in the computer vision domain; however, existing methods do not translate well into the constrained cyber domain as they tend to produce non-functional network packets. This research views the payload of network packets as code with many functional units. A meta-heuristic based generative model is developed to maximize classification loss of packet payloads with respect to a surrogate model by repeatedly substituting units of code with functionally equivalent counterparts. The perturbed packets are then transferred and tested against three test network intrusion detection system classifiers with various evasion rates that depend on the classifier and malicious packet type. If the test classifier is of the same architecture as the surrogate model, near-optimal adversarial examples penetrate the test model for 69% of packets whereas the raw examples succeeds for only 5% of packets. This confirms hypotheses that NIDS classifiers are vulnerable to adversarial attacks, motivating research in robust learning for cyber

    CHANGES IN SUPPORT MOMENT AND MUSCLE ACTIVATION FOLLOWING HIP AND TRUNK NEUROMUSCULAR TRAINING: THE HIP AND ACL INJURY RISK

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    This study investigated lower limb muscular activation strategies following an 8-week body-weight based training intervention focused on the dynamic control of the hip/trunk. Muscle activation, support moment and frontal plane knee moments of elite female hockey players (n=13) were measured during unplanned sidestepping pre/post training. Post-training, gluteal muscle activation increased (+10%;p=0.006). There was no change in support moment or frontal plane knee moments however, the contribution of hip extension to total support moment increased (+10%;d=0.56) following training. Hip/trunk neuromuscular training is effective in improving hip neuromuscular activation, allowing athletes to more effectively utilise their hip to generate their support moment, which may prevent dangerous ā€˜dynamic valgusā€™ knee postures during sidestepping sporting tasks

    HOW MUCH IS ENOUGH? MAINTAINING THE BIOMECHANICAL BENEFITS OF AN ACL INJURY PREVENTION TRAINING PROGRAM

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    This study investigated the effect of a 16-week maintenance training program which directly followed a high-dose 9 week initial training intervention, as part of a biomechanically informed ACL injury prevention program. Three-dimensional kinematic and kinetic data of elite female hockey players (n=16) were collected at baseline, post initial training and post maintenance training during unplanned sidestepping. Maintenance training was effective in retaining reduced peak knee valgus moments in a ā€˜high-riskā€™ subgroup elicited from the initial training program. Conversely, although the total group demonstrated no benefits following initial training, they displayed a reduction (?-26.3%, g=0.30) in peak valgus knee moments following maintenance training, suggesting a prolonged albeit moderate dose of training was effective for this population

    Management of Children With Chronic Wet Cough and Protracted Bacterial Bronchitis CHEST Guideline and Expert Panel Report

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    BACKGROUND: Wet or productive cough is common in children with chronic cough. We formulated recommendations based on systematic reviews related to the management of chronic wet cough in children (aged METHODS: We used the CHEST expert cough panel\u27s protocol for systematic reviews and the American College of Chest Physicians (CHEST) methodologic guidelines and GRADE framework (the Grading of Recommendations Assessment, Development and Evaluation). Data from the systematic reviews in conjunction with patients\u27 values and preferences and the clinical context were used to form recommendations. Delphi methodology was used to obtain consensus for the recommendations/suggestions made. RESULTS: Combining data from the systematic reviews, we found high-quality evidence in children aged 4 weeks\u27 duration) wet/productive cough that using appropriate antibiotics improves cough resolution, and further investigations (eg, flexible bronchoscopy, chest CT scans, immunity tests) should be undertaken when specific cough pointers (eg, digital clubbing) are present. When the wet cough does not improve following 4 weeks of antibiotic treatment, there is moderate-quality evidence that further investigations should be considered to look for an underlying disease. New recommendations include the recognition of the clinical diagnostic entity of protracted bacterial bronchitis. CONCLUSIONS: Compared with the 2006 Cough Guidelines, there is now high-quality evidence for some, but not all, aspects of the management of chronic wet cough in specialist settings. However, further studies (particularly in primary health) are required

    A novel method to identify high order gene-gene interactions in genome-wide association studies: Gene-based MDR

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    <p>Abstract</p> <p>Background</p> <p>Because common complex diseases are affected by multiple genes and environmental factors, it is essential to investigate gene-gene and/or gene-environment interactions to understand genetic architecture of complex diseases. After the great success of large scale genome-wide association (GWA) studies using the high density single nucleotide polymorphism (SNP) chips, the study of gene-gene interaction becomes a next challenge. Multifactor dimensionality reduction (MDR) analysis has been widely used for the gene-gene interaction analysis. In practice, however, it is not easy to perform high order gene-gene interaction analyses via MDR in genome-wide level because it requires exploring a huge search space and suffers from a computational burden due to high dimensionality.</p> <p>Results</p> <p>We propose dimensional reduction analysis, Gene-MDR analysis for the fast and efficient high order gene-gene interaction analysis. The proposed Gene-MDR method is composed of two-step applications of MDR: within- and between-gene MDR analyses. First, within-gene MDR analysis summarizes each gene effect via MDR analysis by combining multiple SNPs from the same gene. Second, between-gene MDR analysis then performs interaction analysis using the summarized gene effects from within-gene MDR analysis. We apply the Gene-MDR method to bipolar disorder (BD) GWA data from Wellcome Trust Case Control Consortium (WTCCC). The results demonstrate that Gene-MDR is capable of detecting high order gene-gene interactions associated with BD.</p> <p>Conclusion</p> <p>By reducing the dimension of genome-wide data from SNP level to gene level, Gene-MDR efficiently identifies high order gene-gene interactions. Therefore, Gene-MDR can provide the key to understand complex disease etiology.</p

    COORDINATION AND VARIABILITY IN AUSTRALIAN RULES FOOTBALL KICKING: IMPLICATIONS FOR PERFORMANCE

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    The purpose of this study was to quantify coordination and coordination variability (CV) of drop-punt kicking in professional Australian Football players and investigate the association between CV and in-game kicking performance and professional playing experience. Intra-limb couplings described to be associated with kicking accuracy were investigated during 30m successful drop-punt kicking efforts in 14 players. Coordination and CV were quantified using a modified vector coding technique. Higher CV of frontal plane trunk/pelvis, frontal and transverse plane thigh/leg and frontal plane leg/foot coupled motion were associated with higher in-game kicking performance. In-game kicking performance and CV did not change following two years of professional experience. These results highlight the significance of junior level skill development and kicking performance in talent identification
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