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Fault Pattern Diagnosis and Classification in Sensor nodes Using Fall Curve

Computers, Materials & Continua 2022年第7期72卷 1799-1814页

作者： Mudita Uppal Deepali Gupta Divya Anand fahd S.alharithi Jasem almotiri Arturo Mansilla Dinesh Singh nitin Goyal Chitkara University institute of Engineering and Technology Chitkara UniversityPunjabIndia Computer Science&Engineering Department Lovely Professional UniversityJalandharPunjabIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Higher Polytechnic School/industrial Organization Engineering Universidad Europea del AtlánticoIsabel Torres 2139011SantanderSpain Department of Project Management Universidad Internacional IberoamericanaCampeche24560Mexico Computer Science and Engineering Department Deenbandhu Chhotu Ram University of Science and TechnologyMurthalSonipatHaryanaIndia

The rapid expansion of internet of Things(ioT)devices deploys various sensors in different applications like homes,cities and *** applications depend upon the accuracy of sensor ***,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor *** technique identifies the faulty sensor and determines the correct working of the *** sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in ioT devices are also presented in tabular *** prediction in digital and analog sensors along with methods of sensor fault prediction are *** are several advantages and disadvantages of sensor fault prediction methods and the fall curve ***,some solutions are provided to overcome the limitations of the fall curve *** this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five *** novelty is to predict a fault before its occurrence by looking at the fall *** sensing of current flow in devices is important to prevent a major ***,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty *** analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to *** evaluation metrics for fault prediction are also described in this *** last,this paper also addresses some possible open research issues which are important to deal with false ioT sensor data.

关键词： Fault identification fault classification ioT sensor nodes analog sensors digital sensors fall curve

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Authenblue: A new Authentication Protocol for the industrial internet of Things

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Computers, Materials & Continua 2021年第4期67卷 1103-1119页

作者： Rachid Zagrouba Asayel alAbdullatif Kholood alAjaji norah al-Serhani fahd alhaidari Abdullah almuhaideb Atta-ur-Rahman Department of Computer information System College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

The internet of Things(ioT)is where almost anything can be controlled and managed remotely by means of *** the ioT evolution led to quality of life enhancement,many of its devices are *** lack of robust key management systems,efficient identity authentication,low fault tolerance,and many other issues lead to ioT devices being easily targeted by *** this paper we propose a new authentication protocol called Authenblue that improve the authentication process of ioT devices and Coordinators of Personal Area network(CPAns)in an industrial ioT(iioT)*** study proposed Authenblue protocol as a new Blockchainbased authentication *** enhance the authentication process and make it more secure,Authenblue modified the way of generating iioT identifiers and the shared secret keys used by the iioT devices to raise the efficiency of the authentication *** enhance the authentication protocol that other models rely on by enhancing the approach used to generate the User identifier(Ui).The Ui values changed from being static values,sensors MAC addresses,to be generated values in the inception *** approach makes the process of renewing the sensor keys more secure by renewing their Ui values instead of changing the secret *** this study,Authenblue has been simulated in the network Simulator 3(nS3).Simulation results show an improved performance compared to the related work.

关键词： Authentication industrial internet of things security Authenblue blockchain nS3

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Molecular Simulation of Cement-Based Materials and Their Properties

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Engineering 2022年第8期8卷 165-178页

作者： Ashraf A.Bahraq Mohammed A.al-Osta Omar S.Baghabra al-Amoudi i.B.Obot Mohammed Maslehuddin Habib-ur-Rehman Ahmed Tawfik A.Saleh Department of Civil and Environmen.al Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia interdisciplinary Research Center for Construction and Building Materials King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia interdisciplinary Research Center for Advanced Materials King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Department of Chemistry King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia

Hydrated cement is one of the complex composite systems due to the presence of multi-scale phases with varying *** silicate hydrate,which is the principal binder phase in the hydrated cement,is responsible for the stiffness,strength,and durability of Portland cement *** understand the mechanical and durability behavior of concrete,it is important to investigate the interactions of hydrated cement phases with other materials at the *** this regard,the molecular simulation of cement-based materials is an effective approach to study the properties and interactions of the cement system at the fundamen.al ***,many studies have been published regarding atomistic simulations to investigate the cement phases to define/explain the microscopic physical and chemical properties,thereby improving the macroscopic performance of hardened *** research in molecular simulation of cementitious systems involves researchers with multidisciplinary backgrounds,mainly in two areas:(1)cement chemistry,where the hydration reactions govern most of the chemical and physical properties at the atomic scale;and(2)computational materials science and engineering,where the bottom-up approach is *** latter approach is still in its infancy,and as such,a study of the prevailing knowledge is useful,namely through an exhaustive literature *** state-of-theart report provides a comprehensive survey on studies that were conducted in this area and cites the important findings.

关键词： Atomistic simulation Molecular dynamics Cement phases Hydration products nanoengineering

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Storytelling and environmen.al information: connecting schoolchildren and herpetofauna in Morocco

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integrative Zoology 2009年第2期4卷 188-195页

作者： Lucia FAnini Soumia fahd Department of Evolutionary Biology University of FlorenceItaly Laboratory for Diversity and Conservation of Biological Systems Department of BiologyFaculty of ScienceAbdelmalek Essâadi UniversityTétouanMorocco

northwestern Morocco is undergoing a sudden change in the level of infrastructure growth and pressure on the environment from increased *** ongoing changes are raising questions about how the ecosystem will react,and the relevant drivers of these *** Oued Laou valley in north-west Morocco hosts high landscape,species and human cultural *** Talassemtane national Park has been established to preserve the envi-ronment in this region;however,what information tools are available to children regarding this environment?The ecosystem is illustrated here using three components:herpetofauna(representing ecosystem components),prob-lems related to water quantity and quality(representing interactions within ecosystem components)and Talassemtane national Park(representing a case of ecosystem management).A children’s book was written on this topic,and when the book was delivered to pupils,a questionnaire was included,aimed at determining their sources of environ-men.al *** results identified major changes in the sources of information utilized by children in this part of Morocco,a clear role of schools in explaining ecosystem components,and an increasing role of TV in environmen.al information *** role of the family was found to be less important than TV or *** major source of pupils’environmen.al knowledge is personal observation and hands-on experience,both for rural and urban *** are willing to discover and understand complex systems,and researchers should be encouraged to supply children with correct and up-to-date information on environmen.al systems,focusing at first on the local environment,as a background for sustainable development.

关键词： environmen.al education herpetofauna information sources Moroccan Rif primary school.

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intelligent Deep Learning Model for Privacy Preserving iioT on 6G Environment

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Computers, Materials & Continua 2022年第7期72卷 333-348页

作者： Anwer Mustafa Hilal Jaber Salzahrani ibrahim Abunadi nadhem nemri fahd nal-wesa.i Abdelwahed Motwakel ishfaq Yaseen Abu Sarwar Zamani Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of information Systems Prince Sultan UniversityRiyadh11586Saudi Arabia Department of information Systems King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Computer Science King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and iT Sana’a UniversitySana’a61101Yemen

in recent times,industrial internet of Things(iioT)experiences a high risk of cyber attacks which needs to be *** technology can be incorporated into iioT system to help the entrepreneurs realize industry 4.0 by overcoming such cyber *** blockchain-based iioT network renders a significant support and meet the service requirements of next generation network,the performance arrived at,in existing studies still needs *** this scenario,the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for industrial ioT(PPBDL-iioT)on 6G *** proposed PPBDLiioT technique aims at identifying the existence of intrusions in ***,PPBDL-iioT technique also involves the design of Chaos Game Optimization(CGO)with Bidirectional Gated Recurrent neural network(BiGRnn)technique for both detection and classification of intrusions in the ***,CGO technique is applied to fine tune the hyperparameters in BiGRnn *** algorithm is applied to optimally adjust the learning rate,epoch count,and weight decay so as to considerably improve the intrusion detection performance of BiGRnn ***,Blockchain enabled integrity Check(BEiC)scheme is also introduced to avoid the misrouting attacks that tamper the OpenFlow rules of SDn-based iioT *** performance of the proposed PPBDL-iioT methodology was validated using industrial Control System Cyber-attack(iCSCA)dataset and the outcomes were analysed under various *** experimen.al results highlight the supremacy of the presented PPBDL-iioT technique than the recent state-of-the-art techniques with the higher accuracy of 91.50%.

关键词： 6G networks industrial iot blockchain security intrusion detection artificial intelligence

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Current updates of CRiSPR/Cas9-mediated genome editing and targeting within tumor cells:an innovative strategy of cancer management

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Cancer Communications 2022年第12期42卷 1257-1287页

作者： Khaled S.allemailem Mohammed A alsahli Ahmad almatroudi Faris alrumaihi fahd Khaleefah alkhaleefah Arshad Husain Rahmani Amjad ali Khan Department of Medical Laboratories College of Applied Medical SciencesQassim UniversityBuraydahSaudi Arabia Department of Laboratory and Blood Bank Al Rass General HospitalAl RassSaudi Arabia Department of Basic Health Sciences College of Applied Medical SciencesQassim UniversityBuraydahSaudi Arabia

Clustered regularly interspaced short palindromic repeats-associated protein(CRiSPR/Cas9),an adaptive microbial immune system,has been exploited as a robust,accurate,efficient and programmable method for genome targeting and *** innovative and revolutionary technique can play a significant role in animal modeling,in vivo genome therapy,engineered cell therapy,cancer diagnosis and *** CRiSPR/Cas9 endonuclease system targets a specific genomic locus by single guide RnA(sgRnA),forming a heteroduplex with target *** Streptococcus pyogenes Cas9/sgRnA:DnA complex reveals a bilobed architecture with target recognition and nuclease ***/Cas9 assembly can be hijacked,and its nanoformulation can be engineered as a delivery system for different clinical ***,the efficient and safe delivery of the CRiSPR/Cas9 system to target tissues and cancer cells is very challenging,limiting its clinical *** delivery strategies of this system may have many advantages,but disadvantages such as immune system stimulation,tumor promotion risk and small insertion size outweigh these ***,there is a desperate need to develop an efficient non-viral physical delivery system based on simple *** delivery strategies of CRiSPR/Cas9 by a nanoparticle-based system have shown tremendous potential,such as easy and large-scale production,combination therapy,large insertion size and efficient in vivo *** review aims to provide in-depth updates on Streptococcus pyogenic CRiSPR/Cas9 structure and its mechanistic *** addition,the advances in its nanoformulation-based delivery systems,including lipid-based,polymeric structures and rigid nPs coupled to special ligands such as aptamers,TAT peptides and cell-penetrating peptides,are ***,the clinical applications in different cancers,clinical trials and future prospects of CRiSPR/Cas9 delivery and genome targeting are also discussed.

关键词： cancer clinical trials CRiSPR/Cas9 genome editing mechanism nanoparticles structure

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An Optimized Deep Learning Model for Emotion Classification in Tweets

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Computers, Materials & Continua 2022年第3期70卷 6365-6380页

作者： Chinu Singla fahd nal-wesa.i Yash Singh Pathania Badria Sulaiman.alfurhood Anwer Mustafa Hilal Mohammed Rizwanullah Manar Ahmed Hamza Mohammad Mahzari Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatialaIndia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and iT Sana’a UniversitySana’aYemen Department of Computer Science College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

The task of automatically analyzing sentiments from a tweet has more use now than ever due to the spectrum of emotions expressed from national leaders to the average *** this data can be critical for any *** are often expressed with different intensity and topics which can provide great insight into how something affects *** analysis in Twittermitigates the various issues of analyzing the tweets in terms of views expressed and several approaches have already been proposed for sentiment analysis in *** used for analyzing tweet emotions are also briefly presented in literature survey *** this paper,hybrid combination of different model’s LSTM-Cnn have been proposed where LSTMis Long Short TermMemory andCnnrepresents Convolutionalneural ***,the main contribution of our work is to compare various deep learning and machine learning models and categorization based on the techniques *** main drawback of LSTM is that it’s a timeconsuming process whereas Cnn do not express content information in an accurate way,thus our proposed hybrid technique improves the precision rate and helps in achieving better *** step of our mentioned technique is to preprocess the data in order to remove stop words and unnecessary data to improve the efficiency in terms of time and accuracy also it shows optimal results when it is compared with predefined approaches.

关键词： Meta level features lexical mistakes sentiment analysis count vector natural language processing deep learning machine learning naive bayes

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Visualizing risk factors of dementia from scholarly literature using knowledge maps and next-generation data models

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Visual Computing for industry,Biomedicine,and Art 2021年第1期4卷 165-182页

作者： Kiran fahd Sitalakshmi Venkatraman Department of information Technology Melbourne Polytechnic3181 PrahranVICAustralia

Scholarly communication of knowledge is predominantly document-based in digital repositories,and researchers find it tedious to automatically capture and process the semantics among related *** the present digital era of big data,there is a lack of visual representations of the knowledge present in scholarly articles,and a time-saving approach for a literature search and visual navigation is *** majority of knowledge display tools cannot cope with current big data trends and pose limitations in meeting the requirements of automatic knowledge representation,storage,and dynamic *** address this limitation,the main aim of this paper is to model the visualization of unstructured data and explore the feasibility of achieving visual navigation for researchers to gain insight into the knowledge hidden in scientific articles of digital *** topics of research and practice,including modifiable risk factors leading to a dramatic increase in.alzheimer’s disease and other forms of dementia,warrant deeper insight into the evidence-based knowledge available in the *** goal is to provide researchers with a visual-based easy traversal through a digital repository of research *** paper takes the first step in proposing a novel integrated model using knowledge maps and next-generation graph datastores to achieve a semantic visualization with domain-specific knowledge,such as dementia risk *** model facilitates a deep conceptual understanding of the literature by automatically establishing visual relationships among the extracted knowledge from the big data resources of research *** also serves as an automated tool for a visual navigation through the knowledge repository for faster identification of dementia risk factors reported in scholarly ***,it facilitates a semantic visualization and domain-specific knowledge discovery from a large digital repository and their associations.

关键词： Big data Data visualization Knowledge maps Dementia non-relational database Graph database neo4j Semantic visualization

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Hamiltonian Formulation of Singular Lagrangians on Time Scales

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Chinese Physics Letters 2008年第5期25卷 1720-1723页

作者： JARAD fahd BalEAnU Dumitru MARAABA Abdeljawad Thabet Department of Mathematics and Computer Science Faculty of Arts and Sciences Cankaya University-06530 Ankara Turkey

The Hamiltonian formulation of Lagrangian on time scale is investigated and the equivalence of Hamilton and Euler-Lagrange equations is obtained. The role of Lagrange multipliers is discussed.

关键词： supernova explosion proto-neutron star shock wave

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Automatic Channel Detection Using Dnn on 2D Seismic Data

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Computer Systems Science & Engineering 2021年第1期36卷 57-67页

作者： fahd A.alhaidari Saleh A.al-Dossary ilyas A.Salih Abdlrhman M.Salem Ahmed S.Bokir Mahmoud O.Fares Mohammed i.Ahmed Mohammed S.Ahmed imam Abdulrahman Bin Faisal University College of Computer Science and Information TechnologyDammam34212Saudi Arabia Saudi Aramco Oil Company EXPEC-IIDhahranSaudi Arabia

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon *** are among the most important geological features interpreters analyze to locate petroleum ***,man.al channel picking is both time consuming and ***,similar to any other process dependent on human intervention,man.al channel picking is error prone and *** address these issues,automatic channel detection is both necessary and important for efficient and accurate seismic *** systems make use of real-time image processing techniques for different *** channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil *** this paper,we propose an innovative automatic channel detection.algorithm based on machine learning *** new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation *** algorithm uses deep neural network to train the classifier with both the channel and non-channel *** provide a field data example to demonstrate the performance of the new *** training phase gave a maximum accuracy of 84.6%for the classifier and it performed even better in the testing phase,giving a maximum accuracy of 90%.

关键词： Deep neural networks deep learning channel detection image processing two-dimensional seismic data

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