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A Low Complexity ML-Based Methods for Malware Classification

Computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura.a.mad Alkhatib Deema Mohammed Alsekait Mohammad Alshinwan sa.a. A.el-Rahman Didi Rosiyadi Diaa sa.a.a.a.d elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer systems Program-electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Ja.a.a Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAs malware da.a.et,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the da.a.et is transformed,reducing the number of features while maintaining essential da.a.for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and sca.a.le cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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a.a.ysis of cerium substitution in Co-sr based spinel ferrites for high frequency application

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Journal of Rare Earths 2024年第9期42卷 1755-1763,I0005页

作者： Laura Khudaysh Inas a.a.med syeda Rabia Ejaz sajjad Ahmad Khan Yasir A.Haleem Mohamed M.Ibrahim Mahmood Ali Hafiz Muhammad Tahir Farid Zeinhom M.el-Bahy Department of Physics Faculty of ScienceJazan UniversityJazan45142Saudi Arabia Department of Chemistry Faculty of ScienceKing Khalid UniversityAbha62224Saudi Arabia Department of Physics The Government Sadiq College Women UniversityBahawalpur63100Pakistan Institute of Physics Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Centre of Excellence in solid state Physics University of the PunjabLahorePakistan Department of Physics Government CollegeTaunsa Sharif32200Pakistan Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City11884CairoEgypt

spinel ferrites exhibit exceptional magnetic properties,making them a distinctive class of magnetic *** sol-gel technique was utilized for the synthesis of spinel ferrites with the chemical formula Co_(0.6)sr_(0.4)Ce_(x)Fe_(2-x)O_(4). Following that,a comprehensive X-ray diffraction a.a.ysis unveiled the crystalline cubic structure of the synthesized *** the utilization of the M-H loop approach,the ferromagnetic attributes of ferrites were assessed,and the assimilation of rare earth elements led to substantial enhancements in saturation magnetization,remanence,and *** ferrites with a high concentration of rare earth elements have improved direct current resistivity and activation *** logarithm of a material's resistance increased from 5.29 to 8.12 Ω·cm as cerium is *** a change in the amount of cerium,the activation energy goes up from 0.19 to *** changing the frequency from 5.5 to 9.5 GHz,the dielectric cha.a.teristics were *** the frequency goes up,the dielectric constant goes *** ferrites that have been made better in every way can be used in high-frequency applications.

关键词： Activation energy DC electrical resistance Remanence magnetization Cobalt strontium spinel ferrites High frequency application Rare earths

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Extended Deep Learning Algorithm for Improved Brain Tumor Diagnosis system

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Intelligent Automation & soft Computing 2024年第1期39卷 33-55页

作者： M.Adimoolam K.Maithili N.M.Ba.a.urugan R.Rajkumar s.Leela.a.hy Raju Kanna.a.an Mohd Anul Haq Ilyas Khan elsayed M.Tag el Din Arfat Ahmad Khan Department of Computer Engineering Government Polytechnic CollegeSevvapetTiruvallurTamil Nadu602025India Department of Computer science and Engineering KG Reddy College of Engineering and TechnologyHyderabadTelangana500075India Department of Computer science and Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India Department of Computer science and Engineering Annamalai UniversityChidambaramTamil Nadu608002India Department of Computer science and Engineering Aarupadai Veedu Institute of TechnologyVinayaka Mission Research FoundationPaiyanurTamil Nadu603104India Department of electrical and electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Department of Computer science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand

At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are a.a.ted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system ***,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance pa.a.eters such as accuracy,sensitivity,and false positive and false negative *** addition,these iterated measures were a.a.yzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the sPss tool,and respective graphical illustrations were *** results were that the mean performance measures for the proposed EDLa.a.gorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten *** in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved *** EDLa.a.gorithm introduces novelty concerning its performance and particular activation *** proposed method will be utilized effectively in brain tumor detection in a precise and accurate *** algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses *** the quantity of da.a.et records is enormous,then themethod’s computation power has to be updated.

关键词： Brain tumor extended deep learning algorithm convolution neural network tumor detection deep learning

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Enhancing fatigue performance of AZ31 magnesium alloy components fabricated by cold metal transfer-based wire arc directed energy deposition through LPB

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Journal of Magnesium and Alloys 2024年第4期12卷 1638-1662页

作者： shambhu Kumar Manjhi srikanth Bontha.a.s.s.Ba.a. Department of Mechanical Engineering National Institute of Technology KarnatakaSurathkalSrinivasanagarMangaloreKarnataka 575025India

Cold Metal Transfer-Based Wire Arc Directed Energy Deposition(CMT-wa-DED)presents a promising avenue for the rapid fabrication of components crucial to automotive,shipbuilding,and aerospace ***,the susceptibility to fatigue of CMT-wa-DED-produced AZ31 Mg alloy components has impeded their widespread adoption for critical load-bearing *** this study,a comprehensive investigation into the fatigue behaviour of wa-DED-fabricated AZ31 Mg alloy has been carried out and compared to commercially a.a.lable wrought AZ31 *** findings indicate that the as-deposited parts exhibit a lower fatigue life than wrought Mg alloy,primarily due to poor surface finish,tensile residual stress,porosity,and coarse grain microstructure inherent in the wa-DED *** Plasticity Burnishing(LPB)treatment is applied to mitigate these issues,which induce significant plastic deformation on the *** treatment resulted in a remarkable improvement of fatigue life by 42%,accompanied by a reduction in surface roughness,grain refinement and enhancement of compressive residual stress ***,during cyclic deformation,wa-DED specimens exhibited higher plasticity and dislocation density compared to both wrought and wa-DED+LPB specimens.A higher fraction of Low Angle Grain Boundaries(LAGBs)in wa-DED specimens contributed to multiple crack initiation sites and convoluted crack paths,ultimately leading to premature *** contrast,wrought and wa-DED+LPB specimens displayed a higher percentage of High Angle Grain Boundaries(HAGBs),which hindered dislocation movement and resulted in fewer crack initiation sites and less complex crack paths,thereby extending fatigue *** findings underscore the effectiveness of LPB as a post-processing technique to enhance the fatigue performance of wa-DED-fabricated AZ31 Mg alloy *** study highlights the importance of LPB surface treatment on AZ31 Mg components produced by CMT-wa-DED to remove surface d

关键词： Wire arc additive manufacturing AZ31 Mg alloy Low plasticity burnishing Low cycle fatigue test strain amplitude

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Rational design of natural leather-based water evaporator for electricity generation and functional applications

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Journal of Energy Chemistry 2024年第9期96卷 129-144页

作者： Bingyuan Zhang Xiaoyu Guan Qingxin Han Haoxiang Guo sai Zheng Xuhui sun Afnan H.el-Gowily Mohammed a.a.osheasha Yanxia Zhu Motoki Ueda Meng An Haojun Fan Yoshihiro Ito College of Bioresources Chemical and Materials Engineering Key Laboratory of Auxiliary Chemistry and Technology for Chemical IndustryMinistry of EducationShaanxi Collaborative Innovation Center of Industrial Auxiliary Chemistry and TechnologyShaanxi University of Science&TechnologyXi'an 710021ShaanxiChina Nano Medical Engineering Laboratory RIKEN Cluster for Pioneering Research2-1 HirosawaWako 351-0198SaitamaJapan Key Laboratory of Leather Chemistry and Engineering(sichuan University) Ministry of EducationChengdu 610065SichuanChina College of Mechanical and electrical Engineering Shaanxi University of Science&TechnologyXi'an 710021ShaanxiChina Biochemistry Division Chemistry DepartmentFaculty of ScienceTanta UniversityTanta 31527Egypt

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting *** abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and una.a.table shape have restricted their wide ***,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and *** numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-sA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series ***,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and sea.a.er demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.

关键词： Energy conversion water evaporation-induced electricity Functional leather Flexible self-powered sensor Desalination

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Long-term monitoring reveals the effect of precipitation and silviculture on Nothofagus regeneration in Northern Pa.a.onia mixed forests

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Ecological Processes 2024年第2期13卷 103-117页

作者： Georgina sola Camila Mateo Alejandro Dezzotti Paula Marchelli Hernán Attis Beltrán Renato sbrancia Luis Chauchard Marcelo González Pe?alba Martín La.a.Verónica el Mujtar Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Asentamiento Universitario san Martín de los Andes (AUsMA-UNCo) Instituto de Investigaciones Forestales y Agropecuarias Bariloche (IFAB) Instituto Nacional de Tecnología Agropecuaria (INTA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Departamento de Conservación y Manejo Parque Nacional Lanín- Administración de Parques Nacionales (PNL-APN)

Background Tree regeneration is a key component of resilience because it promotes post-disturbance recovery of forests. Northwestern Pa.a.onia from Argentina is occupied by Nothofagus alpina（Na）, N. obliqua（No）, and N. dombeyi（Nd） forests that grow along an intense precipitation gradient, ma.a.ed throughout shelterwood silvicultural system by technicians of the Lanin Natural Reserve. The objective of this study was to evaluate the influence of seeding cuttings over the dynamics of Nothofagus mixed forests across landscape（precipitation gradient） based mainly on the composition and abundance of tree regeneration, permanent sampling plots and generalized linear mixed models. In particular, we a.a.ysed:（i） the structure of sexual and asexual regeneration during 20 years after harvest（the dynamics of ma.a.ed forests）, and（ii） the structure of sexual regeneration in primary and ma.a.ed forests after > 20 years of harvest（the effect of silviculture）.Results Nd was the most abundant species in the regeneration of ma.a.ed forests during all periods in both sites despite its lower contribution to the adult cohort. During the 10–20 years period after harvest, the humid site exhibited higher regeneration density than the mesic site(120,000 and 6000 ind ha-1, respectively), and it decreased afterwards. The number of established regeneration（> 2 m height） was lower for Na in the mesic site and for No in the humid site(0 and 57 ind ha-1, respectively). However, in comparison to No, Na showed a higher number of sprouted stumps and sprouts per stump, and a higher sprout height in the mesic site. No exhibited higher sprout mortality in the humid site. Finally, the regeneration of primary forests showed lower density and height, and a more ba.a.ced composition than that of ma.a.ed *** The silvicultural effects on the mixed forest regeneration dynamics was strongly influenced by the condition of sites. Therefore, ma.a.ement prescriptions should be adj

关键词： Nothofagus alpina Nothofagus obliqua Nothofagus dombeyi Ba.a. sprouting shelterwood silvicultural system Ecological resilience

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Optimizing Grey Wolf Optimization: A Novel Agents’ Positions Updating Technique for Enhanced Efficiency and Performance

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Open Journal of Optimization 2024年第1期13卷 21-30页

作者： Mahmoud Kha.a. Mohamed el-Gamel Ahmed I. saleh Asmaa H. Rabie a.a.lah el-shenawy Department of Mathematics and Engineering Physics Faculty of Engineering Mansoura University Mansoura Egypt Department of Computers and Control Faculty of Engineering Mansoura University Mansoura Egypt Department of Mathematics Faculty of Science New Mansoura University Mansoura Egypt

Grey Wolf Optimization (GWO) is a nature-inspired metaheuristic algorithm that has gained popularity for solving optimization problems. In GWO, the success of the algorithm heavily relies on the efficient updating of the agents’ positions relative to the leader wolves. In this paper, we provide a brief overview of the Grey Wolf Optimization technique and its significance in solving complex optimization problems. Building upon the foundation of GWO, we introduce a novel technique for updating agents’ positions, which aims to enhance the algorithm’s effectiveness and efficiency. To evaluate the performance of our proposed approach, we conduct comprehensive experiments and compare the results with the original Grey Wolf Optimization technique. Our compa.a.ive a.a.ysis demonstrates that the proposed technique achieves superior optimization outcomes. These findings underscore the potential of our approach in addressing optimization challenges effectively and efficiently, making it a valuable contribution to the field of optimization algorithms.

关键词： Grey Wolf Optimization (GWO) Metaheuristic Algorithm Optimization Problems Agents’ Positions Leader Wolves Optimal Fitness Values Optimization Challenges

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Ren-integrable and ren-symmetric integrable systems

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Communications in Theoretical Physics 2024年第3期76卷 62-69页

作者： s Y Lou school of Physical science and Technology Ningbo UniversityNingbo315211China

A new type of symmetry,ren-symmetry,describing anyon physics and corresponding topological physics,is ***-symmetry is a generalization of super-symmetry which is widely applied in super-symmetric physics such as super-symmetric quantum mechanics,super-symmetric gravity,super-symmetric string theory,super-symmetric integrable systems and so *** and Grassmann numbers are,in some sense,dual conceptions,and it turns out that these conceptions coincide for the ren situation,that is,a similar conception of ren-number(R-number)is devised for *** particular,some basic results of the R-number and ren-symmetry are exposed which allow one to derive,in principle,some new types of integrable systems including ren-integrable models and ren-symmetric integrable *** examples of ren-integrable KdV-type systems and ren-symmetric KdV equations are explicitly given.

关键词： symmetries integrable systems anyon physics extended supersymmetry ren-symmetry

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search for production of dark fermion candidates in association with heavy neutral gauge boson decaying to dimuon in proton-proton collisions at√s=8 TeV using CMs open data

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Chinese Physics C 2024年第4期48卷 6-13页

作者： Y.Mahmoud H.Abdallah M.T.Hussein s.elgammal Centre for theoretical physics The British University in EgyptEgypt Physics Department Faculty of ScienceCairo UniversityEgypt

In this study,we conducted a search for dark matter using a part of the da.a.recorded by the CMs experiment during run-I of the LHC in 2012 with a center of mass energy of 8 TeV and an integrated luminosity of 11.6 fb−*** da.a.were gathered from the CMs open *** matter,in the framework of the simplified model(mono-Z′),can be produced from proton-proton collisions in association with a new hypothetical gauge boson,Z′.Thus,the search was conducted in the dimuon plus large missing transverse momentum *** benchmark scenario of mono-Z′,which is known as light vector,was used for interpreting the CMs open *** evidence of dark matter was observed,and exclusion limits were set on the masses of dark matter and Z′at 95%confidence level.

关键词： dark matter large hadron collider CMs open data search for new physics dark fermion

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AutoRhythmAI: A Hybrid Machine and Deep Learning Approach for Automated Diagnosis of Arrhythmias

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Computers, Materials & Continua 2024年第2期78卷 2137-2158页

作者： s.Ja.a.thi s.Pra.a.na Devi Department of Computer science and Engineering SRM Institute of Science and Technology-Vadapalani CampusChennaiTamil NaduIndia

In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation *** glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between da.a.preprocessing and model *** validate our system,we have rigorously tested AutoRhythmAI using a multimodal da.a.et,surpassing the accuracy achieved using a single da.a.et and underscoring the robustness of our *** the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by da.a.ba.a.cing and split for *** second pipeline is dedicated to feature extraction and classification,utilizing deep learning ***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then a.a.ga.a.es all models,considering their respective weights,resulting in an optimal model *** our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-ba.a.ced performance metrics.

关键词： Automated machine learning neural networks deep learning arrhythmias

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