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Novel Framework for an Intrusion Detection System Using multiple Feature Selection methods Based on Deep Learning

Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.E.m.Eljialy mohammed yousuf Uddin Sultan Ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. machine learning (mL) techniques are extensively applied to build robust IDSs. many researchers have utilized different mL methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the mL model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

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Distribution, health and ecological risk assessments of trace elements in Nigerian oil sands

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Acta Geochimica 2024年第1期43卷 59-71页

作者： Odunayo T.Ore Festus m.Adebiyi Department of Chemistry Obafemi Awolowo UniversityIle-Ife 220005Nigeria Department of Chemical Sciences Achievers UniversityOwoNigeria

The Nigerian oil sands represent the largest oil sand deposit in Africa, yet there is little published information on the distribution and potential health and ecological risks of trace elements in the oil resource. In the present study, we investigated the distribution pattern of 18trace elements(including biophile and chalcophile elements) as well as the estimated risks associated with exposure to these elements. The results of the study indicated that Fe was the most abundant element, with a mean concentration of 22,131 mg/kg while Br had the lowest mean concentration of 48 mg/kg. The high occurrence of Fe and Ti suggested a possible occurrence of ilmenite(Fe TiO_(3)) in the oil sands. Source apportionment using positive matrix factorization showed that the possible sources of detected elements in the oil sands were geogenic, metal production, and crustal. The contamination factor, geo-accumulation index, modified degree of contamination, pollution load index, and Nemerow pollution index indicated that the oil sands are heavily polluted by the elements. Health risk assessment showed that children were relatively more susceptible to the potentially toxic elements in the oil sands principally via ingestion exposure route(HQ > 1E-04). Cancer risks from inhalation are unlikely due to CR mal contact pose severe risks(CR > 1E-04). The high concentrations of the elements pose serious threats due to the potential for atmospheric transport, bioaccessibility, and bioavailability.

关键词： Biophile Chalcophile Oil sand Risk assessment Trace element

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Unveiling the potential of electrocautery-enhanced lumen-apposing metal stents in endoscopic ultrasound-guided biliary drainage

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World Journal of Gastrointestinal Surgery 2024年第7期16卷 1956-1959页

作者： meer m Chisthi Department of General Surgery Government Medical College PathanamthittaKonni 689691KeralaIndia

This editorial delves into Peng et al's article,published in the World Journal of Gastrointestinal *** et al's meta-analysis investigates the effectiveness of electrocautery-enhanced lumen-apposing metal stents(ECE-LAmS)in ultrasound-guided biliary drainage for alleviating malignant biliary *** 14 studies encompassing 620 participants,the research underscores a robust technical success rate of 96.7%,highlighting the efficacy of ECE-LAmS,particularly in challenging cases which have failed endoscopic retrograde cholangio pancreatography.A clinical success rate of 91.0% underscores its impact on symptom alleviation,while a reasonably tolerable adverse event rate of 17.5% is ***,the 7.3% re-intervention rate stresses the need for post-procedural *** analyses validate consistent outcomes,bolstering the applicability of *** findings advocate for the adoption of ECELAmS as an appropriate approach for biliary palliation,urging further exploration in real-world clinical *** offer valuable insights for optimizing interventions targeting malignant biliary obstruction management.

关键词： Biliary drainage Electrocautery-enhanced lumen-apposing metal stent Endoscopic retrograde cholangiopancreatography Endoscopic ultrasound malignant biliary obstruction

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Emerging role of galectin 3 in neuroinflammation and neurodegeneration

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Neural Regeneration Research 2024年第9期19卷 2004-2009页

作者： Brian m.Lozinski Khanh Ta yifei Dong Department of Clinical Neuroscience University of CalgaryCalgaryABCanada Deparment of Biochemistry Microbiology&ImmunologyUniversity of SaskatchewanSaskatoonSKCanada

Neuroinflammation and neurodegeneration are key processes that mediate the development and progression of neurological ***,the mechanisms modulating these processes in different diseases remain incompletely *** in single cell based multi-omic analyses have helped to identify distinct molecular signatures such as Lgals3 that is associated with neuroinflammation and neurodegeneration in the central nervous system(CNS).Lgals3 encodes galectin-3(Gal3),aβ-galactoside and glycan binding glycoprotein that is frequently upregulated by reactive microglia/macrophages in the CNS during various neurological *** Gal3 has previously been associated with non-CNS inflammatory and fibrotic diseases,recent studies highlight Gal3 as a prominent regulator of inflammation and neuroaxonal damage in the CNS during diseases such as multiple sclerosis,Alzheimer’s disease,and Parkinson’s *** this review,we summarize the pleiotropic functions of Gal3 and discuss evidence that demonstrates its detrimental role in neuroinflammation and neurodegeneration during different neurological *** also consider the challenges of translating preclinical observations into targeting Gal3 in the human CNS.

关键词： Alzheimer’s disease Galectin 3 microglia multiple sclerosis neurodegeneration neuroinflammation Parkinson’s disease therapeutics

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Substrate control in track registration and preservation:insights across the Triassic—Jurassic boundary in southern Africa

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Journal of Palaeogeography 2024年第2期13卷 351-371页

作者： Loyce mpangala miengah Abrahams Emese m.Bordy Department of Geological Sciences University of Cape TownCape TownSouth Africa

Tracks registration is influenced by the dynamic interplay between the pedal anatomy of the trackmaker,its behaviour,and the substrate conditions it interacts *** in substrate conditions,especially those linked to grain size and moisture content,often result in the most dramatic variations in track *** the upper Stormberg Group,main Karoo Basin of southern Africa,diverse trace fossils,primarily comprising Late Triassic—Early Jurassic dinosaur tracks,are *** studies have extensively documented individual ichnosites,investigating variations between sites over time,with recent studies suggesting that track abundance and anatomical fidelity increase *** the well-established link between substrate and track morphology,past studies have not specifically focused on substrate conditions,often emphasizing macro-sedimentary features ***,we examine the micro-sedimentary features of track-bearing units in the upper Stormberg Group using petrographic techniques to better understand the palaeosubstrate and its effect on fossil track registration and *** analysis revealed that very fine-grained sandstones and substrates modified by microbial activity tend to preserve tracks with greater abundance and/or higher anatomical ***,the prevalence of very fine-grained and microbially modified strata,and their associated track trends increases in younger stratigraphic *** the Triassic—Jurassic boundary in southern Africa,a boom in dinosaur track abundances is observed and credited to the proliferation of dinosaur populations during the Early *** findings,however,suggest that the observed local increase in track abundance(and anatomical fidelity)up-stratigraphy may be linked to substrate composition differences,which were ultimately controlled by large-scale changes in the palaeoenvironment from high-energy meandering fluvial to lower-energy aeolian-lacustrine settings in the L

关键词： Dinosaur tracks Footprint anatomical fidelity micro-sedimentary features Substrate conditions Track registration Palaeoenvironmental context

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Investigation of material composition,design,and performance of open-graded asphalt mixtures for semi-flexible pavement:A comprehensive experimental study

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第1期11卷 92-116页

作者： mohammad Taghipoor Abolfazl Hassani mohammad m.Karimi Department of Civil and Environmental Engineering Tarbiat Modares UniversityTehranIran

The primary goal of this study is the design and construction of semi-flexible pavement(SFP)mixture in accordance with the engineering and mechanical *** study involves the use of a range of gradation curves,air void contents,cellulose and synthesized fibers,and neat and modified asphalt binders to prepare the open-graded asphalt(OGA)*** analyze the characteristics of these mixtures,a variety of test,namely binder drainage,semi-circular bending(SCB),Cantabro,wheel tracking,indirect tensile strength(ITS),and permeability tests were ***,to analyze the prepared grouting material,flexural strength,compressive strength,and fluidity tests were *** the final stage,SFP was compared to HmA in terms of engineering characteristics and *** to the results,SFP was more resistant to skid,rutting,fire,and moisture damage,while HmA had a better performance in fracture tests,including SCB *** to the results of the mechanical performance tests conducted on OGA mixtures,the highest and lowest values for air void content to achieve the highest mechanical performance level were 30%-35%and 25%,***,based on the laboratory results,it was determined that the required void ratio for constructing OGA mixtures was 24%-26%based on the bitumen type and fibers amount in the ***,SFP mixture can be regarded as a viable alternative to common pavements thanks to its high resistance to rutting and moisture damage,long freezing-thawing fatigue life,and adequate fire and skid resistance.

关键词： Semi-flexible pavement mixture Open-graded asphalt mixture Engineering properties Cantabro test Hot mix asphalt

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Fire resistance evaluation through synthetic fire tests and generative adversarial networks

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Frontiers of Structural and Civil Engineering 2024年第4期18卷 587-614页

作者： Aybike Özyüksel Çiftçioğlu m.Z.Naser Department of Civil Engineering Manisa Celal Bayar University45140Türkiye School of Civil&Environmental Engineering and Earth Sciences(SCEEES) Clemson UniversityClemsonSC 29631USA Artificial Intelligence Research Institute for Science and Engineering(AIRISE) Clemson UniversityClemsonSC 29631USA

This paper introduces a machine learning approach to address the challenge of limited data resulting from costly and time-consuming fire experiments by enlarging small fire test data sets and predicting the fire resistance of reinforced concrete *** approach begins by creating deep learning models,namely generative adversarial networks and variational autoencoders,to learn the spatial distribution of real fire *** then use these models to generate synthetic tabular samples that closely resemble realistic fire resistance values for reinforced concrete *** generated data are employed to train state-of-the-art machine learning techniques,including Extreme Gradient Boost,Light Gradient Boosting machine,Categorical Boosting Algorithm,Support Vector Regression,Random Forest,Decision Tree,multiple Linear Regression,Polynomial Regression,Support Vector machine,Kernel Support Vector machine,Naive Bayes,and K-Nearest Neighbors,which can predict the fire resistance of the columns through regression and *** learning analyses achieved highly accurate predictions of fire resistance values,outperforming traditional models that relied solely on limited experimental *** study highlights the potential for using machine learning and deep learning analyses to revolutionize the field of structural engineering by improving the accuracy and efficiency of fire resistance evaluations while reducing the reliance on costly and time-consuming experiments.

关键词： deep learning fire resistance generative adversarial networks machine learning

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Review of Artificial Neural Networks for Wind Turbine Fatigue Prediction

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SDHm Structural Durability and Health monitoring 2024年第6期18卷 707-737页

作者： AlShannaq Aly A.m. Windstorm Impact Science and Engineering (WISE) Research Lab Louisiana State University Baton Rouge 70803 LA United States

Wind turbines have emerged as a prominent renewable energy source globally. Efficient monitoring and detection methods are crucial to enhance their operational effectiveness, particularly in identifying fatigue-related issues. This review focuses on leveraging artificial neural networks (ANNs) for wind turbine monitoring and fatigue detection, aiming to provide a valuable reference for researchers in this domain and related areas. Employing various ANN techniques, including General Regression Neural Network (GRNN), Support Vector machine (SVm), Cuckoo Search Neural Network (CSNN), Backpropagation Neural Network (BPNN), Particle Swarm Optimization Artificial Neural Network (PSO-ANN), Convolutional Neural Network (CNN), and nonlinear autoregressive networks with exogenous inputs (NARX), we investigate the impact of average wind speed on stress transfer function and fatigue damage in wind turbine structures. Our findings indicate significant precision levels exhibited by GRNN and SVm, making them suitable for practical implementation. CSNN demonstrates superiority over BPNN and PSO-ANN in predicting blade fatigue life, showcasing enhanced accuracy, computational speed, precision, and convergence rate towards the global minimum. Furthermore, CNN and NARX models display exceptional accuracy in classification tasks. These results underscore the potential of ANNs in addressing challenges in wind turbine monitoring and fatigue detection. However, it’s important to acknowledge limitations such as data availability and model complexity. Future research should explore integrating real-time data and advanced optimization techniques to improve prediction accuracy and applicability in real-world scenarios. In summary, this review contributes to advancing the understanding of ANNs’ efficacy in wind turbine monitoring and fatigue detection, offering insights and methodologies that can inform future research and practical applications in renewable energy systems. © 2024 The Authors.

关键词： artificial neural network fatigue prediction Wind turbine

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STCF conceptual design report (Volume 1): Physics & detector

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Frontiers of physics 2024年第1期19卷 1-154页

作者： m.Achasov X.C.Ai L.P.An R.Aliberti Q.An X.Z.Bai y.Bai O.Bakina A.Barnyakov V.Blinov V.Bobrovnikov D.Bodrov A.Bogomyagkov A.Bondar I.Boyko Z.H.Bu F.m.Cai H.Cai J.J.Cao Q.H.Cao X.Cao Z.Cao Q.Chang K.T.Chao D.y.Chen H.Chen H.X.Chen J.F.Chen K.Chen L.L.Chen P.Chen S.L.Chen S.m.Chen S.Chen S.P.Chen W.Chen X.Chen X.F.Chen X.R.Chen y.Chen y.Q.Chen H.y.Cheng J.Cheng S.Cheng T.G.Cheng J.P.Dai L.y.Dai X.C.Dai D.Dedovich A.Denig I.Denisenko J.m.Dias D.Z.Ding L.y.Dong W.H.Dong V.Druzhinin D.S.Du y.J.Du Z.G.Du L.m.Duan D.Epifanov y.L.Fan S.S.Fang Z.J.Fang G.Fedotovich C.Q.Feng X.Feng y.T.Feng J.L.Fu J.Gao y.N.Gao P.S.Ge C.Q.Geng L.S.Geng A.Gilman L.Gong T.Gong B.Gou W.Gradl J.L.Gu A.Guevara L.C.Gui A.Q.Guo F.K.Guo J.C.Guo J.Guo y.P.Guo Z.H.Guo A.Guskov K.L.Han L.Han m.Han X.Q.Hao J.B.He S.Q.He X.G.He y.L.He Z.B.He Z.X.Heng B.L.Hou T.J.Hou y.R.Hou C.y.Hu H.m.Hu K.Hu R.J.Hu W.H.Hu X.H.Hu y.C.Hu J.Hua G.S.Huang J.S.Huang m.Huang Q.y.Huang W.Q.Huang X.T.Huang X.J.Huang y.B.Huang y.S.Huang N.Hüsken V.Ivanov Q.P.Ji J.J.Jia S.Jia Z.K.Jia H.B.Jiang J.Jiang S.Z.Jiang J.B.Jiao Z.Jiao H.J.Jing X.L.Kang X.S.Kang B.C.Ke m.Kenzie A.Khoukaz I.Koop E.Kravchenko A.Kuzmin y.Lei E.Levichev C.H.Li C.Li D.y.Li F.Li G.Li G.Li H.B.Li H.Li H.N.Li H.J.Li H.L.Li J.m.Li J.Li L.Li L.Li L.y.Li N.Li P.R.Li R.H.Li S.Li T.Li W.J.Li X.Li X.H.Li X.Q.Li X.H.Li y.Li y.y.Li Z.J.Li H.Liang J.H.Liang y.T.Liang G.R.Liao L.Z.Liao y.Liao C.X.Lin D.X.Lin X.S.Lin B.J.Liu C.W.Liu D.Liu F.Liu G.m.Liu H.B.Liu J.Liu J.J.Liu J.B.Liu K.Liu K.y.Liu K.Liu L.Liu Q.Liu S.B.Liu T.Liu X.Liu y.W.Liu y.Liu y.L.Liu Z.Q.Liu Z.y.Liu Z.W.Liu I.Logashenko y.Long C.G.Lu J.X.Lu N.Lu Q.F.Lü y.Lu y.Lu Z.Lu P.Lukin F.J.Luo T.Luo X.F.Luo y.H.Luo H.J.Lyu X.R.Lyu J.P.ma P.ma y.ma y.m.ma F.maas S.malde D.matvienko Z.X.meng R.mitchell A.Nefediev y.Nefedov S.L.Olsen Q.Ouyang P.Pakhlov G.Pakhlova X.Pan y.Pan E.Passemar y.P.Pei H.P.Peng L.Peng X.y.Peng X.J.Peng K.Peters S.Pivovarov E.Pyata B.B.Qi y.Q.Qi W.B.Qian y.Qian C.F.Qiao J.J.Qin J.J.Qin L.Q.Qin X.S.Qin T.L.Qiu J.Rademacker C.F.Redmer H.y.Sang Anhui University Hefei 230039China Beihang University Beijing 100191China Budker Institute of Nuclear Physics Novosibirsk 630090Russia CAS Key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China Cavendish Laboratory University of CambridgeJJ Thomson AveCambridge CB30HEUnited Kingdom Central China Normal University Wuhan 430079China Central South University Changsha 410083China China University of Geosciences Wuhan 430074China China University of mining and Technology Xuzhou 221116China École Polytechnique Fédérale de Lausanne(EPFL) LausanneSwitzerland Fudan University Shanghai 200433China Goethe University Frankfurt D-60325 Frankfurt am MainGermany Guangxi Normal University Guilin 541004China Guangxi Uninversity Nanning 530004China Hangzhou Institute for Advanced Study UCASHangzhou 310024China Hebei Normal University Shijiazhuang 050024China Hebei University Baoding 071002China Hefei University of Technology Hefei 230601China Helmholtz Institute mainz Staudinger Weg 18D-55099 MainzGermany Henan Normal University Xinxiang 453007China Henan University Kaifeng 475004China High Energy Physics Center Chung-Ang UniversitySeoul 06974Korea Higher School of Economy 11 Pokrovsky Bulvar Moscow 109028Russia Huangshan University Huangshan 245000China Hubei University of Automotive Technology Shiyan 442002China Hunan Normal University Changsha 410081China Hunan University of Science and Technology Xiangtan 411201China Hunan University Changsha 410082China Indiana University BloomingtonIndiana 47405USA Inner mongolia University Hohhot 010021China Institute of Advanced Science Facilities Shenzhen 518107China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China Institute of modern Physics Chinese Academy of SciencesLanzhou 730000China Institute of Physics Academia SinicaTaipeiTaiwan 11529China Institute of Theoretical Physics Chinese Academy of SciencesBeijing 100190China Jilin University Changch

The superτ-charm facility(STCF)is an electron–positron collider proposed by the Chinese particle physics *** is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of 0.5×10^(35) cm^(–2)·s^(–1) or *** STCF will produce a data sample about a factor of 100 larger than that of the presentτ-charm factory—the BEPCII,providing a unique platform for exploring the asymmetry of matter-antimatter(charge-parity violation),in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions,as well as searching for exotic hadrons and physics beyond the Standard *** STCF project in China is under development with an extensive R&D *** document presents the physics opportunities at the STCF,describes conceptual designs of the STCF detector system,and discusses future plans for detector R&D and physics case studies.

关键词： electron–positron collider tau-charm region high luminosity STCF detector conceptual design

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Analysis of synthetic parameters for coating aluminum powders with phenyltriethoxysilane coupling agent and their effects on powder flow behavior

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Particuology 2024年第7期90卷 412-417页

作者： Lillian m.mawby Bellamarie Ludwig Benjamin J.Lear Department of Chemistry The Pennsylvania State UniversityUniversity ParkPA16802USA Applied Research Laboratory The Pennsylvania State UniversityUniversity ParkPA16802USA

Though silanization of aluminum powder is currently used to improve its flow properties,for use as an alternative fuel source,there are a wide range of experimental parameters for the process and not all of them have been thoroughly *** this is complete,it is unknown if the process is optimized in terms of time,efficiency,and ***,we report on a study into the effects of changes in humidity,degree of agitation,reaction temperature,and curing time upon the deposition of phenyl triethoxysilane into 20μm(d50)aluminum *** confirm the deposition of the coating via diffuse reflectance infrared spectroscopy and x-ray photoelectron *** then characterize the coated particles using apparent density measurements and Carney flow *** analysis of variance,we find that,of the parameters explored,only changes in cure time and reaction temperature provide meaningful changes to the apparent density,while none of our parameters produced statistically significant changes in Carney flow ***,we conclude that,when optimizing silanization of aluminum particles,environmental control of humidity is unneeded and that the reaction can be run with minimal *** ability to largely ignore these parameters is a benefit to large-scale processing.

关键词： Aluminum powder Silane Fluidization Apparent density Carney flow

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