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Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

Computers, Materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami khafaga El-Sayed M.El-kenawy faten khalid k.rim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),k-NearestRegression(kNR),Multi-Layer Perceptron(MLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and k-nearest neighbors(kNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： Metamaterial antenna dipper throated optimization feature selection parameters prediction

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami khafaga faten khalid k.rim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend k.Alkahtani Nima khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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Fungal diversity notes 1387-1511:taxonomic and phylogenetic contributions on genera and species of fungal taxa

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Fungal Diversity 2021年第6期111卷 1-335页

作者： Saranyaphat Boonmee Dhanushka N.Wanasinghe Mark S.Calabon Naruemon Huanraluek Sajini k.U.Chandrasiri Gareth E.B.Jones Walter Rossi Marco Leonardi Sanjay k.Singh Shiwali Rana Paras N.Singh Deepak k.Maurya Ajay C.Lagashetti Deepika Choudhary Yu-Cheng Dai Chang-Lin Zhao Yan-Hong Mu Hai-Sheng Yuan Shuang-Hui He Rungtiwa Phookamsak Hong-Bo Jiang María P.Martín Margarita Dueñas MTeresa Telleria Izabela L.kałucka Andrzej M.Jagodziński kare Liimatainen Diana S.Pereira Alan J.L.Phillips Nakarin Suwannarach Jaturong kumla Surapong khuna Saisamorn Lumyong Tarynn B.Potter Roger G.Shivas Adam H.Sparks Niloofar Vaghefi Mohamed A.Abdel-Wahab faten A.Abdel-Aziz Guo-Jie Li Wen-Fei Lin Upendra Singh Rajendra P.Bhatt Hyang Burm Lee Thuong T.T.Nguyen Paul M.kirk Arun kumar Dutta krishnendu Acharya VVenkateswara Sarma M.Niranjan kunhiraman C.Rajeshkumar Nikhil Ashtekar Sneha Lad Nalin N.Wijayawardene Darbe J.Bhat Rong-Ju Xu Subodini N.Wijesinghe Hong-Wei Shen Zong-Long Luo Jing-Yi Zhang Phongeun Sysouphanthong Naritsada Thongklang Dan-Feng Bao Janith V.S.Aluthmuhandiram Jafar Abdollahzadeh Alireza Javadi Francesco Dovana Muhammad Usman Abdul Nasir khalid Asha J.Dissanayake Anusha Telagathoti Maraike Probst Ursula Peintner Isaac Garrido-Benavent Lilla Bóna Zsolt Merényi Lajos Boros Bratek Zoltán JBenjamin Stielow Ning Jiang Cheng-Ming Tian Esmaeil Shams Farzaneh Dehghanizadeh Adel Pordel Mohammad Javan-Nikkhah Teodor T.Denchev Cvetomir M.Denchev Martin kemler Dominik Begerow Chun-Ying Deng Emma Harrower Tohir Bozorov Tutigul kholmuradova Yusufjon Gafforov Aziz Abdurazakov Jian-Chu Xu Peter E.Mortimer Guang-Cong Ren Rajesh Jeewon Sajeewa S.N.Maharachchikumbura Chayanard Phukhamsakda Ausana Mapook kevin D.Hyde Center of Excellence in Fungal Research Mae Fah Luang UniversityChiang Rai 57100Thailand School of Science Mae Fah Luang UniversityChiang Rai 57100Thailand CAS key Laboratory for Plant Biodiversity and Biogeography of East Asia(kLPB) Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China CIFOR-ICRAF China Program World Agroforestry(ICRAF)Kunming 650201YunnanPeople’s Republic of China Honghe Center for Mountain Futures Kunming Institute of BotanyHonghe CountyKunming 654400YunnanPeople’s Republic of China Department of Botany and Microbiology College of ScienceKing Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia Section Environmental Sciences Department MeSVAUniversity of L’Aquila67100 CoppitoAQItaly National Fungal Culture Collection of India(NFCCI) Biodiversity and Palaeobiology GroupMACS Agharkar Research InstituteG.G.Agarkar RoadPune 411004India Institute of Microbiology School of Ecology and Nature ConservationBeijing Forestry UniversityBeijing 100083People’s Republic of China College of Biodiversity Conservation Southwest Forestry UniversityKunming 650224People’s Republic of China CAS key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110164People’s Republic of China University of the Chinese Academy of Sciences Beijing 100049People’s Republic of China Centre for Mountain Futures(CMF) Kunming Institute of BotanyKunming 650201YunnanPeople’s Republic of China Department of Mycology Real Jardín Botánico-CSICPlaza de Murillo 228014 MadridSpain Department of Algology and Mycology Faculty of Biology and Environmental ProtectionUniversity of LodzBanacha 12/1690-237ŁódźPoland Institute of Dendrology Polish Academy of SciencesParkowa 562-035 KórnikPoland Jodrell Laboratory Royal Botanic GardensKewRichmond TW93DSSurreyUK Faculdade de Ciências Biosystems and Integrative Sciences Institute(BioISI)Universidade de LisboaCampo Grande1749-016 LisbonPortugal Dep

This article is the 13th contribution in the Fungal Diversity Notes series,wherein 125 taxa from four phyla,ten classes,31 orders,69 families,92 genera and three genera incertae sedis are treated,demonstrating worldwide and geographic *** taxa described and illustrated in the present study include three new genera,69 new species,one new com-bination,one reference specimen and 51 new records on new hosts and new geographical *** new genera,Cylindrotorula(Torulaceae),Scolecoleotia(Leotiales genus incertae sedis)and Xenovaginatispora(Lindomycetaceae)are introduced based on distinct phylogenetic lineages and unique *** described species are Aspergillus lan-naensis,Cercophora dulciaquae,Cladophialophora aquatica,Coprinellus punjabensis,Cortinarius alutarius,***-latus,***,Coryneum fagi,Cruentomycena uttarakhandina,Cryptocoryneum rosae,Cyathus uniperidiolus,Cylindrotorula indica,Diaporthe chamaeropicola,Didymella azollae,Diplodia alanphillipsii,Dothiora coronicola,Efibula rodriguezarmasiae,Erysiphe salicicola,Fusarium queenslandicum,Geastrum gorgonicum,***,Helicosporium sexualis,Helminthosporium chiangraiensis,Hongkongmyces kokensis,Hydrophilomyces hydraenae,Hygrocybe boertmannii,Hyphoderma australosetigerum,Hyphodontia yunnanensis,khaleijomyces umikazeana,Laboulbenia divisa,Laboulbenia triarthronis,Laccaria populina,Lactarius pallidozonarius,Lepidosphaeria strobelii,Longipedicellata megafusiformis,Lophiotrema lincangensis,Marasmius benghalensis,***,***,Mariannaea camelliae,Mel-anographium smilaxii,Microbotryum polycnemoides,Mimeomyces digitatus,Minutisphaera thailandensis,Mortierella solitaria,Mucor harpali,Nigrograna jinghongensis,Odontia huanrenensis,***,Paraconiothyrium ajrekarii,Par-afuscosporella niloticus,Phaeocytostroma yomensis,Phaeoisaria synnematicus,Phanerochaete hainanensis,Pleopunctum thailandicum,Pleurotheciella dimorphospora,Pseudochaetosphaeronema

关键词： 72 new taxa One new combination One reference specimen 51 new records Agaricomycetes Ascomycota Bartheletiomycetes Basidiomycota Dothideomycetes Eurotiomycetes Exobasidiomycetes Laboulbeniomycetes Leotiomycetes Mortierellomycetes Mortierellomycota Mucoromycetes Mucoromycota Phylogeny Sordariomycetes Taxonomy

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