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Optimal Bidirectional LSTM for Modulation Signal Classification in Communication Systems

Computers, Materials & Continua 2022年第8期72卷 3055-3071页

作者： Manar Ahmed Hamza Siwar Ben Haj Hassine Souad Larabi-Marie-Sainte Mohamed K.nour Fahd n.Al-Wesabi Abdelwahed Motwakel Anwer Mustafa Hilal Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayil AsirSaudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Modulation signal classification in communication systems can be considered a pattern recognition *** works have focused on several feature extraction approaches such as fractal feature,signal constellation reconstruction,*** recent advent of deep learning(DL)models makes it possible to proficiently classify the modulation *** this view,this study designs a chaotic oppositional satin bowerbird optimization(COSBO)with bidirectional long term memory(BiLSTM)model for modulation signal classification in communication *** proposed COSBO-BiLSTM technique aims to classify the different kinds of digitally modulated *** addition,the fractal feature extraction process takes place by the use of Sevcik Fractal Dimension(SFD)***,the modulation signal classification process takes place using BiLSTM with fully convolutional network(BiLSTM-FCn).Furthermore,the optimal hyperparameter adjustment of the BiLSTM-FCn technique takes place by the use of COSBO *** order to ensure the enhanced classification performance of the COSBO-BiLSTM model,a wide range of simulations were carried *** experimental results highlighted that the COSBO-BiLSTM technique has accomplished improved performance over the existing techniques.

关键词： Complex systems communication system signal processing modulation signals classification artificial intelligence deep learning parameter tuning

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Design of Machine Learning Based Smart Irrigation System for Precision Agriculture

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Computers, Materials & Continua 2022年第7期72卷 109-124页

作者： Khalil Ibrahim Mohammad Abuzanouneh Fahd n.Al-Wesabi Amani Abdulrahman Albraikan Mesfer Al Duhayyim M.Al-Shabi Anwer Mustafa Hilal Manar Ahmed Hamza Abu Sarwar Zamani K.Muthulakshmi Department of Information Technology College of ComputerQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel Aseer62529Saudi Arabia&Faculty of Computer and ITSana’a UniversitySana’a61101Yemen Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Management Information System College of Business and AdministrativeTaibah UniversityMedina42353Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Electronics and Communication Engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India

Agriculture 4.0,as the future of farming technology,comprises numerous key enabling technologies towards sustainable *** use of state-of-the-art technologies,such as the Internet of Things,transform traditional cultivation practices,like irrigation,to modern solutions of precision *** achieve effectivewater resource usage and automated irrigation in precision agriculture,recent technologies like machine learning(ML)can be *** this motivation,this paper design an IoT andML enabled smart irrigation system(IoTML-SIS)for precision *** proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for *** proposed IoTML-SIS model involves different IoT based sensors for soil moisture,humidity,temperature sensor,and ***,the sensed data are transmitted to the cloud server for processing and decision ***,artificial algae algorithm(AAA)with least squares-support vector machine(LS-SVM)model is employed for the classification process to determine the need for ***,the AAA is applied to optimally tune the parameters involved in the LS-SVM model,and thereby the classification efficiency is significantly *** performance validation of the proposed IoTML-SIS technique ensured better performance over the compared methods with the maximum accuracy of 0.975.

关键词： Automatic irrigation precision agriculture smart farming machine learning cloud computing decision making internet of things

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Machine Learning Based Cybersecurity Threat Detection for Secure IoT Assisted Cloud Environment

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Computer Systems Science & Engineering 2023年第10期47卷 855-871页

作者： Z.Faizal Khan Saeed M.Alshahrani Abdulrahman Alghamdi Someah Alangari nouf Ibrahim Altamami khalid A.Alissa Sana Alazwari Mesfer Al Duhayyim Fahd n.Al-Wesabi Department of Computer Engineering College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Science College of Science and Humanities DawadmiShaqra UniversityShaqraSaudi Arabia Department of Mathematics College of EducationShaqra UniversityShaqraSaudi Arabia Saudi Aramco Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAlaflaj16828Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia

The Internet of Things(IoT)is determine enormous economic openings for industries and allow stimulating innovation which obtain between domains in childcare for eldercare,in health service to energy,and in developed to *** develops a difficult problem in IoT platform whereas the presence of cyber-attack requires that *** progress of automatic devices for cyber-attack classifier and detection employing Artificial Intelligence(AI)andMachine Learning(ML)devices are crucial fact to realize security in IoT *** can be required for minimizing the issues of security based on IoT devices ***,this research proposal establishes novel mayfly optimized with regularized Extreme Learning Machine technique called as MFO-rELM model for Cybersecurity Threat classification and detection fromthe cloud and IoT *** proposed MFOrELM model provides the effective detection of cybersecurity threat which occur in the cloud and IoT *** accomplish this,the MFO-rELM technique pre-processed the actual cloud and IoT data as to meaningful ***,the proposed models will receive the pre-processing data and carry out the classifier *** boosting the efficiency of the proposed models,theMFOtechnique was utilized to *** experiential outcome of the proposed technique was tested utilizing the standard CICIDS 2017 dataset,and the outcomes are examined under distinct aspects.

关键词： Mayfly optimization machine learning artificial intelligence cybersecurity threat detection

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《IPSec VPn设计》

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计算机安全 2014年第2期 43-43页

作者： Vijay Bollapragada Mohamed khalid Scott Wainner

出版社:人民邮电出版社出版时间:2012-11I S B n:978-7-115-29577-4内容简介:IPSec是一种流行的VPn技术,有关IPSec协议的技术细节和产品级配置的图书很多,但都没有讨论IPSec VPn总体设计方面的问题,《IPSec VPn设计》旨在填补

关键词： IPSec VPn 配置 VPn

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Association of gene variants with susceptibility to type 2 diabetes among Omanis

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World Journal of Diabetes 2015年第2期6卷 358-366页

作者： Sawsan Al-Sinani nicolas Woodhouse Ali Al-Mamari Omaima Al-Shafie Mohammed Al-Shafaee Said Al-Yahyaee Mohammed Hassan Deepali Jaju Khamis Al-Hashmi Mohammed Al-Abri khalid Al-rassadi Syed rizvi Yengo Loic Philippe Froguel riad Bayoumi Department of Biochemistry College of Medicine and Health SciencesSultan Qaboos University Genomics and Metabolic Disease Institute Pasteur of Lille Lille2 University

AIM:To investigate the association of 10 known common gene variants with susceptibility to type 2diabetes mellitus(T2D)among ***:Using case-control design,a total of992 diabetic patients and 294 normoglycemic Omani Arabs were genotyped,by an allelic discrimination assay-by-design TaqMan method on fast real time polymerase chain reaction system,for the following gene variants:KCnJ11(rs5219),TCF7L2(rs7903146),CDKAL1(rs10946398),CDKn2A/B(rs10811661),FTO(rs9939609 and rs8050136),IGF2BP2(rs4402960),SLC30A8(rs13266634)CAPn10(rs3792267)and HHEX(rs1111875).T2D patients were recruited from the Diabetes Clinic(n=243)and inpatients(n=749)at Sultan Qaboos Univesity Hospital(SQUH),Muscat,*** control participants(n=294)were volunteers from the community and from those visiting Family Medicine Clinic at SQU,for regular medical *** difficulty in recruiting Omani participants with no family history of diabetes was the main reason behind the small number of control participants in this *** all volunteers questioned had a relativewith diabetes *** of the small number of normoglycemic controls in this study,this sample was sufficient for detection of genes and loci for common alleles influencing T2D with an odds ratio of≥1.3reaching at least 80%*** was collected from June 2010 to February ***:Using binary logistic regression analysis,four gene variants showed significant association with T2D risk:KCnJ11(rs5219,P=5.8×10^(-6),Or=1.74),TCF7L2(rs7903146,P=0.001,Or=1.46),CDKAL1(rs10946398,P=0.002,Or=1.44)and CDKn2A/B(rs10811661,P=0.020,Or=1.40).The fixation index analysis of these four gene variants indicated significant genetic differentiation between diabetics and controls{[KCnJ11(rs5219),Prs7903146),Prs10946398),Pn2A/B(rs10811661),Pnotype variation%between diabetics and controls was found at KCnJ11(2.07%)and TCF7L2(1.62%).This study was not able to detect an as

关键词： Type 2 diabetes Genetics Oman Casecontrol Association Gene Variants

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The Global Soil Mycobiome consortium dataset for boosting fungal diversity research

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Fungal Diversity 2021年第6期111卷 573-588页

作者： Leho Tedersoo Vladimir Mikryukov Sten Anslan Mohammad Bahram Abdul nasir khalid Adriana Corrales Ahto Agan Aída-M.Vasco-Palacios Alessandro Saitta Alexandre Antonelli Andrea C.rinaldi Annemieke Verbeken Bobby P.Sulistyo Boris Tamgnoue Brendan Furneaux Camila Duarte ritter Casper nyamukondiwa Cathy Sharp César Marín D.Q.Dai Daniyal Gohar Dipon Sharmah Elisabeth Machteld Biersma Erin K.Cameron Eske De Crop Eveli Otsing Evgeny A.Davydov Felipe E.Albornoz Francis Q.Brearley Franz Buegger Genevieve Gates Geoffrey Zahn Gregory Bonito Indrek Hiiesalu Inga Hiiesalu Irma Zettur Isabel C.Barrio Jaan Pärn Jacob Heilmann-Clausen Jelena Ankuda John Y.Kupagme Joosep Sarapuu Jose G.Maciá-Vicente Joseph Djeugap Fovo József Geml Juha M.Alatalo Julieta Alvarez-Manjarrez Jutamart Monkai Kadri Põldmaa Kadri runnel Kalev Adamson Kari A.Bråthen Karin Pritsch Kassim I.Tchan Kęstutis Armolaitis Kevin D.Hyde Kevin K.newsham Kristel Panksep Lateef A.Adebola Louis J.Lamit Malka Saba Marcela Eda Silva Cáceres Maria Tuomi Marieka Gryzenhout Marijn Bauters Miklós Bálint nalin Wijayawardene niloufar Hagh-Doust nourou S.Yorou Olavi Kurina Peter E.Mortimer Peter Meidl rHenrik nilsson rasmus Puusepp rebeca Casique-Valdés rein Drenkhan roberto Garibay-Orijel roberto Godoy Saleh Alfarraj Saleh rahimlou Sergei Põlme Sergey V.Dudov Sunil Mundra Talaat Ahmed Tarquin netherway Terry W.Henkel Tomas roslin Vladimir E.Fedosov Vladimir G.Onipchenko WAErandi Yasanthika Young Woon Lim Meike Piepenbring Darta Klavina Urmas Kõljalg Kessy Abarenkov Mycology and Microbiology Center University of TartuTartuEstonia Institute of Ecology and Earth Sciences TartuEstonia Department of Ecology Swedish University of Agricultural SciencesUppsalaSweden Department of Botany University of the PunjabQuaid-e-Azam CampusLahorePakistan Centro de Investigaciones en Microbiología y Biotecnología-Ur(CIMBIUr) Facultad de Ciencias NaturalesUniversidad del RosarioBogotáColombia Grupo de Microbiología Ambiental y BioMicro Escuela de MicrobiologíaUniversidad de Antioquia UdeAMedellínColombia Department of Agricultural Food and Forest SciencesUniversity of PalermoPalermoItaly royal Botanic Gardens SurreyUK Department of Biomedical Sciences University of CagliariCagliariItaly research Group Mycology Department of BiologyGhent UniversityGhentBelgium Department of Biomedicine Indonesia International Institute for Life SciencesJakartaIndonesia Plant Pathology and Agricultural Zoology research Unit Department of Plant ProtectionFaculty of Agronomy and Agricultural SciencesUniversity of DschangDschangCameroon Department of Ecology and Genetics Uppsala UniversityUppsalaSweden Eukaryotic Microbiology University of Duisburg-EssenEssenGermany Department of Biological Sciences and Biotechnology Botswana International University of Science and TechnologyPalapyeBotswana natural History Museum of Zimbabwe BulawayoZimbabwe Institute of Botany Czech Academy of SciencesPrůhoniceCzech Republic Center for Yunnan Plateau Biological resources Protection and Utilization College of Biological Resource and Food EngineeringQujing Normal UniversityQujingPeople’s Republic of China Department of Botany Jawaharlal Nehru Rajkeeya MahavidyalayaPondicherry UniversityPort BlairIndia British Antarctic Survey NERCCambridgeUK natural History Museum of Denmark University of CopenhagenCopenhagenDenmark Department of Environmental Science Saint Mary’s UniversityHalifaxNSCanada Altai State University BarnaulRussia CSIrO Land and Water WembleyWAAustralia Department of n

Fungi are highly important biotic components of terrestrial ecosystems,but we still have a very limited understanding about their diversity and *** data article releases a global soil fungal dataset of the Global Soil Mycobiome consortium(GSMc)to boost further research in fungal diversity,biogeography and *** dataset comprises 722,682 fungal operational taxonomic units(OTUs)derived from PacBio sequencing of full-length ITS and 18S-V9 variable regions from 3200 plots in 108 countries on all *** plots are supplied with geographical and edaphic *** OTUs are taxonomically and functionally assigned to guilds and other functional *** entire dataset has been corrected by excluding chimeras,index-switch artefacts and potential *** dataset is more inclusive in terms of geographical breadth and phylogenetic diversity of fungi than previously published *** GSMc dataset is available over the PlutoF repository.

关键词： Soil fungi Global dataset PacBio sequencing Fungal richness

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Evaluation of the Influence of Fixed Orthodontic Treatment Duration on the Severity of Inflammatory Gingival Enlargement (Fixed Orthodontic Induced Gingival Enlargements) and Some Properties of Saliva

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International Journal of Clinical Medicine 2022年第3期13卷 132-146页

作者： Mohammed M. A. Abdullah Al-Abdaly Abdullah Mohammed A. Asiri Ghadeer Mohammed Mohammed Al-Abdaly Mohammed Abdullah Ghabri Moayad Abdullah H. Alqaysi Abdulmajeed Mohammed S. Aljathnan Yahya Saleem M. Al naser naser Ali n. Alshahrani Periodontics and Community Dental Sciences Department College of Dentistry King Khalid University Abha KSA College of Dentistry King Khalid University Abha KSA Faculty of Dentistry Sana’a University Sanaa Republic of Yemen

Background: Inflammatory gingival enlargement is a more common clinical feature with orthodontic therapy than other features. Therefore, this study was designed to the evaluation of the influence of fixed orthodontic treatment duration on the severity of inflammatory gingival enlargement (fixed orthodontic induced gingival enlargements) and some properties of saliva. Material and Methods: The sample size comprised 145 patients undergoing fixed orthodontic treatment for at least 6 months aged 13 - 32 years. They were divided according to orthodontic treatment duration into three groups. Group I (n = 47) included the patients who were treated for less than 6 months, group II (n = 51) included the patients who were treated for a period of 6 - 12 months, and group III (n = 47) included the patients who were managed for more than 12 months. Data were obtained from the outpatient clinics, college of dentistry, King khalid University, Abha, Saudi Arabia, and some dental centers in Sana’a city, the republic of Yemen. This study was conducted from October 2021 G to January 2022 G. Clinical examination was done for plaque index (PLI), gingival index (GI), and gingival enlargement indexes (GEI). Saliva was collected in sterile test tubes then salivary flow and pH were measured. Statistical analysis was done with SPSS (version 23) and AnOVA test to evaluate the impact of orthodontic treatment duration on the severity of inflammatory gingival enlargement and some properties of saliva. results: The statistical analysis demonstrated the highest mean plaque index (PLI) was among groups III and I participants whereas, the highest mean gingival index and mean gingival enlargement were among groups II and III participants. The present study revealed an increase in salivary flow with decreased salivary pH values with an increase in orthodontic therapy duration. There were statistically significant differences in clinical findings and salivary flow and pH values were observed in the com

关键词： Inflammatory Gingival Enlargement Orthodontic Treatment Duration Some Salivary Properties

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Fungal diversity notes 1277-1386:taxonomic and phylogenetic contributions to fungal taxa

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Fungal Diversity 2020年第5期104卷 1-266页

作者： Hai-Sheng Yuan Xu Lu Yu-Cheng Dai Kevin D.Hyde Yu-He Kan Ivana Kušan Shuang-Hui He ning-Guo Liu V.Venkateswara Sarma Chang-Lin Zhao Bao-Kai Cui nousheen Yousaf Guangyu Sun Shu-Yan Liu Fang Wu Chuan-Gen Lin Monika C.Dayarathne Tatiana Baptista Gibertoni Lucas B.Conceição roberto Garibay-Orijel Margarita Villegas-ríos rodolfo Salas-Lizana Tie-Zheng Wei Jun-Zhi Qiu Ze-Fen Yu rungtiwa Phookamsak Ming Zeng Soumitra Paloi Dan-Feng Bao Pranami DAbeywickrama De-Ping Wei Jing Yang Ishara S.Manawasinghe Dulanjalee Harishchandra rashika S.Brahmanage nimali Ide Silva Danushka S.Tennakoon Anuruddha Karunarathna Yusufjon Gafforov Dhandevi Pem Sheng-nan Zhang AndréL.C.Mde Azevedo Santiago Jadson Diogo Pereira Bezerra Bálint Dima Krishnendu Acharya Julieta Alvarez-Manjarrez Ali H.Bahkali Vinod K.Bhatt Tor Erik Brandrud Timur S.Bulgakov E.Camporesi Ting Cao Yu-Xi Chen Yuan-Yuan Chen Bandarupalli Devadatha Abdallah M.Elgorban Long-Fei Fan Xing Du Liu Gao Camila Melo Gonçalves Luis F.P.Gusmão naruemon Huanraluek Margita Jadan ruvishika S.Jayawardena Abdul nasir khalid Ewald Langer Diogo X.Lima nelson Correia de Lima-Júnior Carla rejane Sousa de Lira Jian-Kui(Jack)Liu Shun Liu Saisamorn Lumyong Zong-Long Luo neven Matočec M.niranjan Joséribamar Costa Oliveira-Filho Viktor Papp Eduardo Pérez-Pazos Alan J.L.Phillips Peng-Lei Qiu Yihua ren rafael F.Castañeda ruiz Kamal C.Semwal Karl Soop Carlos A.Fde Souza Cristina Maria Souza-Motta Li-Hua Sun Meng-Le Xie Yi-Jian Yao Qi Zhao Li-Wei Zhou 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 School of Ecology and nature Conservation Beijing Advanced Innovation Center for Tree Breeding By Molecular DesignBeijing Forestry UniversityBeijing 100083People’s Republic of China CAS Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China Centre of Excellence in Fungal research Mae Fah Luang UniversityChiang Rai 57100Thailand School of Science Mae Fah Luang UniversityChiang Rai 57100Thailand Mushroom research Foundation 128 M.3 Ban Pa Deng T.Pa PaeA.Mae TaengChiang Mai 50150Thailand East and Central Asia regional Office World Agroforestry Centre(ICRAF)Kunming 650201YunnanChina ruđer BoškovićInstitute Bijenička cesta 5410000 ZagrebCroatia Faculty of Agriculture Natural Resources and EnvironmentNaresuan UniversityPhitsanulok 65000Thailand Department of Biotechnology School of Life SciencesPondicherry UniversityR.V.NagarKalapetPondicherry 605014India College of Biodiversity Conservation Southwest Forestry UniversityKunming 650224People’s Republic of China Department of Botany Govt.College UniversityKatchery RoadLahorePakistan State Key Laboratory of Crop Stress Biology in Arid Areas and College of Plant Protection Northwest A&F UniversityYanglingShaanxiPeople’s Republic of China Laboratory of Plant Pathology College of Plant ProtectionJilin Agricultural UniversityChangchun 130118Jilin ProvincePeople’s Republic of China Centro de Biociências Departamento de MicologiaUniversidade Federal de PernambucoCidade UniversitáriaAvenida da Engenharia s/nRecifePernambuco 50740-600Brazil Departamento de Ciências Biológicas Universidade Estadual de Feira de SantanaAv.Transnordestina s/nNovo HorizonteFeira de SantanaBA 44036-900Brazil L

This is the twelfth contribution to the Fungal Diversity notes series on fungal taxonomy,based on materials collected from many countries which were examined and described using the methods of morphology,anatomy,and strain culture,combined with DnA sequence analyses.110 taxa are described and illustrated,including five new genera,92 new species,eight new combinations and other taxonomic contributions(one new sequenced species,one new host and three new records)which are accommodated in 40 families and 1 incertae sedis in *** new genera are Amyloceraceomyces,Catenuliconidia,Hansenopezia,Ionopezia and *** new species are Amyloceraceomyces angustisporus,Amylocorticium ellipsosporum,Arthrinium sorghi,Catenuliconidia uniseptata,Clavulina sphaeropedunculata,Colletotrichum parthenocissicola,Coniothyrium triseptatum,Cortinarius indorusseus,***,***,***,***,Diaporthe pimpinel-lae,Dictyosporella guizhouensis,Diplodia torilicola,Fuscoporia marquesiana,***,Hansenopezia decora,Helicoarcta-tus thailandicus,Hirsutella hongheensis,Humidicutis brunneovinacea,Lentaria gossypina,***,Lycoperdon lahorense,***,Magnopulchromyces scorpiophorus,Moelleriella gracilispora,neodevriesia manglicola,neodidymelliopsis salvia,***,neoroussoella magnoliae,neottiella gigaspora,Ophiosphaerella chiangraiensis,Phaeotremella yunnanensis,Podosphaera yulii,rigidoporus juniperinus,rhodofomitopsis pseudofeei,russula benghalensis,Scleroramularia vermispora,Scytinopogon minisporus,Sporormurispora paulsenii,Thaxteriellopsis obliqus,Tomentella asiae-orientalis,***,***,***,***,***,***,***,***,***-nocystidiata,***,***,***,***,***,***,***,***,***,***,***,***,***,***,***,

关键词： 110 taxa Agaricomycetes Ascomycota Basidiomycota Mucoromycota new combinations new genera new species Phylogeny Taxonomy

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