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Feature extraction for machine learning-based intrusion detection in IoT networks

Digital Communications and Networks 2024年第1期10卷 205-216页

作者： Mohanad Sarhan Siamak Layeghy Nour Moustafa Marcus Gallagher Marius Portmann university of Queensland BrisbaneQLD4072Australia Universiy of New South Wales CanberraACT2612Australia

A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems(NIDSs).Consequently,network interruptions and loss of sensitive data have occurred,which led to an active research area for improving NIDS technologies.In an analysis of related works,it was observed that most researchers aim to obtain better classification results by using a set of untried combinations of Feature Reduction(FR)and Machine Learning(ML)techniques on NIDS datasets.However,these datasets are different in feature sets,attack types,and network design.Therefore,this paper aims to discover whether these techniques can be generalised across various datasets.Six ML models are utilised:a Deep Feed Forward(DFF),Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),Decision Tree(DT),Logistic Regression(LR),and Naive Bayes(NB).The accuracy of three Feature Extraction(FE)algorithms is detected;Principal Component Analysis(PCA),Auto-encoder(AE),and Linear Discriminant Analysis(LDA),are evaluated using three benchmark datasets:UNSW-NB15,ToN-IoT and CSE-CIC-IDS2018.Although PCA and AE algorithms have been widely used,the determination of their optimal number of extracted dimensions has been overlooked.The results indicate that no clear FE method or ML model can achieve the best scores for all datasets.The optimal number of extracted dimensions has been identified for each dataset,and LDA degrades the performance of the ML models on two datasets.The variance is used to analyse the extracted dimensions of LDA and PCA.Finally,this paper concludes that the choice of datasets significantly alters the performance of the applied techniques.We believe that a universal(benchmark)feature set is needed to facilitate further advancement and progress of research in this field.

关键词： Feature extraction Machine learning Network intrusion detection system IoT

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Injury and illness in short-course triathletes:A systematic review

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Journal of Sport and Health Science 2024年第2期13卷 172-185页

作者： Sara A.Guevara Melissa L.Crunkhorn Michael Drew Gordon Waddington Julien D.Périard Naroa Etxebarria Liam A.Toohey Paula Charlton university of canberra Research Institute for Sport and Exercise(UCRISE) BruceACT 2617Australia New South Wales Institute of Sport SydneyNSW 2127Australia Queensland Academy of Sport BrisbaneQLD 4111Australia Triathlon Australia Gold CoastQLD 4227Australia Australian Institute of Sport BruceACT 2617Australia

Background:Determining the incidence and prevalence of injury and illness in short-course triathletes would improve understanding of their etiologies and therefore assist in the development and implementation of prevention strategies.This study synthesizes the existing evidence on the incidence and prevalence of injury and illness and summarizes reported injury or illness etiology and risk factors affecting short-course triathletes.Methods:This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.Studies reporting health problems(injury and illness)in triathletes(all sexes,ages,and experience levels)training and/or competing in short-course distances were included.Six electronic databases(Cochrane Central Register of Controlled Trials,MEDLINE,Embase,APA PsychINFO,Web of Science Core Collection,and SPORTDiscus)were searched.Risk of bias was independently assessed by 2 reviewers using the Newcastle-Ottawa Quality Assessment Scale.Two authors independently completed data extraction.Results:The search yielded 7998 studies,with 42 studies eligible for inclusion.Twenty-three studies investigated injuries,24 studies investigated illnesses,and 5 studies investigated both injuries and illnesses.The injury incidence rate ranged 15.7-24.3 per 1000 athlete exposures,and the illness incidence rate ranged 1.8-13.1 per 1000 athlete days.Injury and illness prevalence ranged between 2%-15%and 6%-84%,respectively.Most injuries reported occurred during running(45%-92%),and the most frequently reported illnesses affected the gastrointestinal(7%-70%),cardiovascular(14%-59%),and respiratory systems(5%-60%).Conclusion:The most frequently reported health problems in short-course triathletes were:overuse and lower limb injuries associated with running;gastrointestinal illnesses and altered cardiac function,primarily attributable to environmental factors;and respiratory illness mostly caused by infection.

关键词： Athlete illnesses Athletic injuries Epidemiology Triathlon

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A systematic scoping review of study methodology for randomized controlled trials investigating probiotics in athletic and physically active populations

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Journal of Sport and Health Science 2024年第1期13卷 61-71页

作者： Alex E.Mohr David B.Pyne Geovana Silva Fogaça Leite Deborah Akins Jamie Pugh College of Health Solutions Arizona State UniversityPhoenixAZ 85004USA Research Institute for Sport and Exercise University of CanberraCanberraACT 2617Australia Laboratory of Functional Fermented Food Faculty of Pharmaceutical SciencesUniversity of São PauloSão Paulo 05508-030Brazil Research Institute for Sport and Exercise Sciences Liverpool John Moores UniversityLiverpool L33AFUK

Background:The purported ergogenic and health effects of probiotics have been a topic of great intrigue among researchers,practitioners,and the lay public alike.There has also been an increased research focus within the realm of sports science and exercise medicine on the athletic gut microbiota.However,compared to other ergogenic aids and dietary supplements,probiotics present unique study challenges.The objectives of this systematic scoping review were to identify and characterize study methodologies of randomized controlled trials investigating supplementation with probiotics in athletes and physically active individuals.Methods:Four databases(MEDLINE,CINAHL,Cochrane CENTRAL,and Cochrane Database of Systematic Reviews)were searched for randomized controlled studies involving healthy athletes or physically active individuals.An intervention with probiotics and inclusion of a control and/or placebo group were essential.Only peer-reviewed articles in English were considered,and there were no date restrictions.Results were extracted and presented in tabular form to detail study protocols,characteristics,and outcomes.Bias in randomized controlled trials was determined with the RoB 2.0 tool.Results:A total of 45 studies were included in the review,with 35 using a parallel group design and 10 using a cross-over design.Approximately half the studies used a single probiotic and the other half a multi-strain preparation.The probiotic dose ranged from 2×10^(8)to 1×10^(11)colony forming units daily,and the length of intervention was between 7 and 150 days.Fewer than half the studies directly assessed gastrointestinal symptoms,gut permeability,or the gut microbiota.The sex ratio of participants was heavily weighted toward males,and only 3 studies exclusively investigated females.Low-level adverse events were reported in only 2 studies,although the methodology of reporting varied widely.The risk of bias was generally low,although details on randomization were lacking in some studies.Conclusion:There is a substantial body of

关键词： Exercise Experimental methodology Gastrointestinal symptoms Gut microbiota Probiotic supplementation

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Schauder Estimates for Elliptic and Parabolic Equations

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Chinese Annals of Mathematics,Series B 2006年第6期27卷 637-642页

作者： Xu-Jia WANG Centre for Mathematics and its Applications Australian National University Canberra ACT 0200 Australia

在这笔记，作者为椭圆形、抛物线的方程为 Schauderestimates 给一个基本、简单的证明。证明也适用于非线性的方程。

关键词： Schauder估计椭圆方程抛物线方程数学分析偏微分方程

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High-Q resonant terahertz metasurfaces

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Opto-Electronic Advances 2024年第4期7卷 1-3页

作者： Manukumara Manjappa Yuri Kivshar Department of Instrumentation and Applied Physics Indian Institute of ScienceBengaluru 560012India Nonlinear Physics Center Australian National UniversityCanberra ACT 2601Australia

In photonics,the quest for high-quality(high Q)reson-ances driven by the physics of bound states in the con-tinuum(BIC)1,2 has motivated researchers to explore in-novative avenues for realizing groundbreaking applica-tions in lasing3,sensing4 and nonlinear photonics5.A conventional strategy to harness the properties of BICs involves breaking the symmetry of resonators in a uni-form lattice,allowing uncoupled modes to interact with free space that opens a leaky channel in the form of so-called(quasi)qBIC6 modes.It is imperative that to un-lock the full potential of photonic BICs,the approach should involve not only a fundamental understanding of their underlying physics but also innovative engineering strategies to tailor their properties for various applica-tions.

关键词： breaking resonant symmetry

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A three-dimensional feature extraction-based method for coal cleat characterization using X-ray μCT and its application to a Bowen Basin coal specimen

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 153-166页

作者： Yulai Zhang Matthew Tsang Mark Knackstedt Michael Turner Shane Latham Euan Macaulay Rhys Pitchers ARC Training Centre for M3D Innovation Research School of PhysicsAustralian National UniversityCanberraACT2601Australia Department of Materials Physics Research School of PhysicsAustralian National UniversityCanberraACT2601Australia Anglo American Steelmaking Coal BrisbaneQLD4000Australia SCT Operations Pty Ltd. WollongongNSW2500Australia

Cleats are the dominant micro-fracture network controlling the macro-mechanical behavior of coal.Improved understanding of the spatial characteristics of cleat networks is therefore important to the coal mining industry.Discrete fracture networks(DFNs)are increasingly used in engineering analyses to spatially model fractures at various scales.The reliability of coal DFNs largely depends on the confidence in the input cleat statistics.Estimates of these parameters can be made from image-based three-dimensional(3D)characterization of coal cleats using X-ray micro-computed tomography(m CT).One key step in this process,after cleat extraction,is the separation of individual cleats,without which the cleats are a connected network and statistics for different cleat sets cannot be measured.In this paper,a feature extraction-based image processing method is introduced to identify and separate distinct cleat groups from 3D X-ray m CT images.Kernels(filters)representing explicit cleat features of coal are built and cleat separation is successfully achieved by convolutional operations on 3D coal images.The new method is applied to a coal specimen with 80 mm in diameter and 100 mm in length acquired from an Anglo American Steelmaking Coal mine in the Bowen Basin,Queensland,Australia.It is demonstrated that the new method produces reliable cleat separation capable of defining individual cleats and preserving 3D topology after separation.Bedding-parallel fractures are also identified and separated,which has his-torically been challenging to delineate and rarely reported.A variety of cleat/fracture statistics is measured which not only can quantitatively characterize the cleat/fracture system but also can be used for DFN modeling.Finally,variability and heterogeneity with respect to the core axis are investigated.Significant heterogeneity is observed and suggests that the representative elementary volume(REV)of the cleat groups for engineering purposes may be a complex problem requiring careful consideration.

关键词： Cleat separation Cleat statistics Feature extraction Discrete fracture network(DFN)modeling

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Quantum state tomography from observable time traces in closed quantum systems

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Control Theory and Technology 2024年第2期22卷 222-234页

作者： Shuixin Xiao Yuanlong Wang Qi Yu Jun Zhang Daoyi Dong Ian R.Petersen university of Michigan–Shanghai Jiao Tong university Joint Institute Shanghai Jiao Tong UniversityShanghai200240China School of Engineering The Australian National UniversityCanberraACT2601Australia Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China Centre for Quantum Computation and Communication Technology(Australian Research Council) Centre for Quantum DynamicsGriffith UniversityBrisbaneQLD4111Australia School of Engineering and Technology University of New South WalesCanberraACT2600Australia

The task to estimate all the parameters of an unknown quantum state, also called quantum state tomography, is essential for characterizing and controlling quantum systems. In this paper, we utilize observable time traces to identify the initial quantum state of a closed quantum system, based on the state space approach in the control theory. In the informationally complete scenario, we show that with a linear regression estimation (LRE), the mean squared error (MSE) scales as , where N is the resource number. In the informationally incomplete scenario, we introduce regularization LRE to perform the state tomography task. We employ PBH test to demonstrate that closed quantum systems with only one observable are informationally incomplete and propose using observables, where d is the dimension of the quantum state, for informational completeness. Numerical examples demonstrate the effectiveness of our method.

关键词： Quantum state tomography Time trace Quantum system identification

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Rodent biology and ecologically based rodent management(EBRM)-25 years of progress through promoting multidisciplinary research

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Integrative Zoology 2024年第1期19卷 2-7页

作者： Grant R. SINGLETON Lyn A. HINDS Rhodes MAKUNDI Steven R. BELMAIN Natural Resources Institute University of Greenwich Kent UK CSIRO Health and Biosecurity Canberra ACT Australia African Centre of Excellence for Innovative Rodent Pest Management and Biosensor Technology Development Sokoine University of Agriculture Morogoro Tanzania Institute of Pest Management Sokoine University of Agriculture Morogoro Tanzania

“During rodent outbreak years in eastern Africa,lo-cally,more than 80%of the potential harvest may be lost,but even in non-outbreak periods,rodents cause chronic damage to crops….The pest rodent story in Africa in-volves several species embedded in a broad and variable landscape with highly variable densities.”(Leirs et al.2010).

关键词： damage crops

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Data-driven Distributionally Adjustable Robust Chance-constrained DG Capacity Assessment

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 115-127页

作者： Masoume Mahmoodi Seyyed Mahdi Noori Rahim Abadi Ahmad Attarha Paul Scott Lachlan Blackhall the College of Engineering and Computer Science The Australian National UniversityCanberraAustralia

Moving away from fossil fuels towards renewable sources requires system operators to determine the capacity of distribution systems to safely accommodate green and distributed generation(DG).However,the DG capacity of a distribution system is often underestimated due to either overly conservative electrical demand and DG output uncertainty modelling or neglecting the recourse capability of the available components.To improve the accuracy of DG capacity assessment,this paper proposes a distributionally adjustable robust chance-constrained approach that utilises uncertainty information to reduce the conservativeness of conventional robust approaches.The proposed approach also enables fast-acting devices such as inverters to adjust to the real-time realisation of uncertainty using the adjustable robust counterpart methodology.To achieve a tractable formulation,we first define uncertain chance constraints through distributionally robust conditional value-at-risk(CVaR),which is then reformulated into convex quadratic constraints.We subsequently solve the resulting large-scale,yet convex,model in a distributed fashion using the alternating direction method of multipliers(ADMM).Through numerical simulations,we demonstrate that the proposed approach outperforms the adjustable robust and conventional distributionally robust approaches by up to 15%and 40%,respectively,in terms of total installed DG capacity.

关键词： Distributed generation(DG)capacity assessment distributionally robust optimisation chance-constrained optimisation distribution system

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Computational and dark-field ghost imaging with ultraviolet light

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Photonics Research 2024年第2期12卷 226-234页

作者： JIAQI SONG BAOLEI LIU YAO WANG CHAOHAO CHEN XUCHEN SHAN XIAOLAN ZHONG LING-AN WU FAN WANG School of Physics Beihang UniversityBeijing 102206China Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems Department of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT 2600Australia Institute of Physics Chinese Academy of SciencesBeijing 100190China

Ultraviolet(UV)imaging enables a diverse array of applications,such as material composition analysis,biological fluorescence imaging,and detecting defects in semiconductor manufacturing.However,scientific-grade UV cameras with high quantum efficiency are expensive and include complex thermoelectric cooling systems.Here,we demonstrate a UV computational ghost imaging(UV-CGI)method to provide a cost-effective UV imaging and detection strategy.By applying spatial–temporal illumination patterns and using a 325 nm laser source,a singlepixel detector is enough to reconstruct the images of objects.We use UV-CGI to distinguish four UV-sensitive sunscreen areas with different densities on a sample.Furthermore,we demonstrate dark-field UV-CGI in both transmission and reflection schemes.By only collecting the scattered light from objects,we can detect the edges of pure phase objects and small scratches on a compact disc.Our results showcase a feasible low-cost solution for nondestructive UV imaging and detection.By combining it with other imaging techniques,such as hyperspectral imaging or time-resolved imaging,a compact and versatile UV computational imaging platform may be realized for future applications.

关键词： ghost illumination versatile

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