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Peptides-based vaccine against SARS-nCoV-2 antigenic fragmented synthetic epitopes recognized by T cell and β-cell initiation of specific antibodies tofightthe infection

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Bio-Design and Manufacturing 2021年第3期4卷 490-505页

作者： Zainularifeen Abduljaleel Faisal A.Al-Allaf Syed a.aziz Department of Medical Genetics Faculty of MedicineUmm Al-Qura UniversityP.O.Box715Mecca21955Kingdom of Saudi Arabia Science and Technology Unit UmmAl-Qura UniversityP.O.Box 715Mecca21955Kingdom of SaudiArabia The Regional Laboratory Molecular Diagnostics UnitDepartment of Molecular BiologyMinistry of Health(MOH)P.O.Box 6251MeccaKingdom of SaudiArabia Department of Pathology and Lab Medicine University of Ottawa451Smyth RoadOttawaONK1H8M5Canada

The World Health Organization has declared the rapidly spreading coronavirus to be a global *** FDA is yet to approve a vaccine for human novel ***,we developed a peptide-based vaccine and used high-throughput screening by molecular dynamics simulation to identify T-cell-and p-cell-recognized epitopes for producing specific antibod-ies against *** construct~12 P'antigenic epitope peptides to develop a more effective vaccine and identify specific *** epitope peptides selectively presented the best antigen presentation scores for both human pMHC class I and II alleles to develop a strong binding *** antigens identified of SARS-nCoV-2 different proteins by each attached specific~1-7 L linker adaptor were used to construct a broad single peripheral peptide *** is expected to be highly antigenic with a minimum allergic *** a result of these exciting outcomes,expressing a vaccine using the intimated peptide was highly promising and positive to be highly proposed as epitope-based peptide vaccine of specific antibody against SARS-nCoV-2 by initiating T cells and β-*** in vitro study for the proposed peptide-based vaccine *** *** clinical trials are required to check the efficacy of this vaccine.

关键词： COVID-19 SARS-nCoV-2 Peptide-based vaccine Cell-penetrating peptides Lipid membrane Vaccine efficacy

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Analytical and finite-element study of optimal strain distribution in various beam shapes for energy harvesting applications

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Acta Mechanica Sinica 2016年第4期32卷 670-683页

作者： B.L.Ooi J.M.Gilbert A.Rashid a.aziz Faculty of Integrative Sciences and Technology Quest International University Perak (QIUP) Faculty of Science and Engineering School of EngineeringUniversity of Hull Center for Automotive Research and Electric Mobility(CAREM) Universiti Teknologi PETRONAS (UTP)

Owing to the increasing demand for harvesting energy from environmental vibration for use in self-powered electronic applications, cantilever-based vibration energy harvesting has attracted considerable interest from various parties and has become one of the most common approaches to converting redundant mechanical energy into electrical energy. As the output voltage produced from a piezoelectric material depends largely on the geometric shape and the size of the beam, there is a need to model and compare the performance of cantilever beams of differing *** paper presents the study of strain distribution in various shapes of cantilever beams, including a convex and concave edge profile elliptical beam that have not yet been discussed in any prior literature. Both analytical and finite-element models are derived and the resultant strain distributions in the beam are computed based on a MATLAB solver and ANSYS finite-element analysis tools. An optimum geometry for a vibration-based energy harvesting system is ***, experimental results comparing the power density for triangular and rectangular piezoelectric beams are also presented to validate the findings of the study, and the claim, as suggested in the literature, is verified.

关键词： harvesting triangular elliptical verified normalized piezoelectric cantilever redundant validate rectangular

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A wavelet transform method for studying the energy distribution characteristics of microseismicities associated rock failure

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Journal of Traffic and Transportation Engineering(English Edition) 2019年第6期6卷 631-646页

作者： Yumei Kang Hongyuan Liu Md Maniruzzaman a.aziz Khairul Anuar Kassim College of Resources and Civil Engineering Northeastern UniversityShenyang 110004China School of Engineering University of TasmaniaHobartTAS 7001Australia Faculty of Civil Engineering Universiti Teknologi Malaysia81310 SkudaiJohorMalaysia

Microseismicity signals released during rock failure process are firstly recorded using microseismicity monitoring system.A wavelet transform scheme is then developed on the basis of the discrete wavelet transform and implemented into MATLAB to study the energy distribution characteristics of the monitored microseismicity *** wavelet transform scheme decomposes the recorded microseismicity signals into various wavelets at seven scales and eight frequency *** microseismicity energy at each frequency band is then calculated by integrating the wavelets in each *** is found that,for the microseismicity signals recorded during the uniaxial loading of the granite,the microseismicity energies are mainly distributed between the bands 7.8125-15.625 kHz,15.625-31.250 kHz and 31.25-62.5 kHz and the percentages of the released energies at these frequency bands are 8.24%,62.72%,28.08% of the total energies,*** results reveal that the microseismicity energies at these levels are directly related to the damage mechanisms of the granite although further studies are need to identify the failure *** these monitored signals were processed using wavelet transformation to find out the frequency distribution rule and the frequency band energy varying rule of the acoustic emission(AE) signals during the different rock damage and failure *** rock failure mechanism was interpreted from the perspective of the relationship between AE signal frequency change and crack *** frequency band energy distribution histograms of the microseismicity signals at different damage stages were computed and drawn by the energy calculation method of wavelet transformation implemented into *** energy percentage of the low frequency band(d7-a7) and that of the dominated frequency band(d4-d6) and their variation rule were analyzed ***,the critical damage point is that the low frequency energy percentage is above a certain threshol

关键词： Microseismicity signal Rock fracture Wavelet transform Band energy Grack

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Three-dimensional oscillation of an acoustic microbubble between two rigid curved plates

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Journal of Hydrodynamics 2021年第5期33卷 1019-1034页

作者： Kawa M.A.Manmi Imad a.aziz Arun Arjunan Rostam K.Saeed Abdolrahman Dadvand Department ofMathematics College of ScienceSalahaddin University-ErbilKurdistan RegionIraq Department of Information Technology College of Engineering and Computer ScienceLebanese French UniversityKurdistan RegionIraq Faculty of Science and Engineering University of WolverhamptonWolverhamptonUK Faculty of Mechanical Engineering Urmia University of TechnologyUrmiaIran Karlsruhe Institute of Technology(KIT) Institute for Chemical Technology and Polymer ChemistryKarlsruheGermany

Understanding the near boundary acoustic oscillation of microbubbles is critical for the effective design of ultrasonic biomedical devices and surface cleaning ***,this study investigates the three-dimensional microbubble oscillation between two curved rigid plates experiencing a planar acoustic field using boundary integral method(BIM).The numerical model is validated via comparison with the nonlinear oscillation of the bubble governed by the modified Rayleigh-Plesset equation and with the axisymmetric model for an acoustic microbubble in infinite fluid ***,the influence of the wave direction and horizontal standoff distance(h)on the bubble dynamics(including jet velocity,jet direction,centroid movement,total energy,and Kelvin impulse)were *** was concluded that the jet velocity,the maximum radius and the total energy of the bubble are not significantly influenced by the wave direction,while the jet direction and the high-pressure region depend strongly on *** importantly,it was found that the jet velocity and the high-pressure region around the jet in acoustic bubble are drastically larger than their counterparts in the gas bubble.

关键词： Acoustic microbubble bubble dynamics boundary integral method(BIM) two curved plates potential flow

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Blockchain Driven Metaheuristic Route Planning in Secure Vehicular Adhoc Networks

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Computers, Materials & Continua 2022年第12期73卷 6461-6477页

作者： Siwar Ben Haj Hassine Saud SAlotaibi Hadeel Alsolai Reem Alshahrani Lilia Kechiche Mrim M.Alnfiai Amira Sayed a.aziz Manar Ahmed Hamza Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Sciences and Technology Taif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Nowadays,vehicular ad hoc networks(VANET)turn out to be a core portion of intelligent transportation systems(ITSs),that mainly focus on achieving continual Internet connectivity amongst vehicles on the *** VANET was utilized to enhance driving safety and build an ITS in modern *** safety is a main portion of VANET,the privacy and security of these messages should be *** this aspect,this article presents a blockchain with sunflower optimization enabled route planning scheme(BCSFO-RPS)for secure *** presented BCSFO-RPSmodel focuses on the identification of routes in such a way that vehicular communication is *** addition,the BCSFO-RPS model employs SFO algorithm with a fitness function for effectual identification of ***,the proposed BCSFO-RPS model derives an intrusion detection system(IDS)encompassing two processes namely feature selection and *** detect intrusions,correlation based feature selection(CFS)and kernel extreme machine learning(KELM)classifier is *** performance of the BCSFO-RPS model is tested using a series of experiments and the results reported the enhancements of the BCSFO-RPS model over other approaches with maximum accuracy of 98.70%.

关键词： VANET sunflower optimization machine learning blockchain intrusion detection

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Remote Sensing Image Encryption Using Optimal Key Generation-Based Chaotic Encryption

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Computer Systems Science & Engineering 2023年第9期46卷 3209-3223页

作者： Mesfer Al Duhayyim Fatma S.Alrayes Saud S.Alotaibi Sana Alazwari Nasser Allheeib Ayman Yafoz Raed Alsini Amira Sayed a.aziz Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Information Systems-College of Computer and Information Sciences King Saud UniversityRiyadhSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

The Internet of Things(IoT)offers a new era of connectivity,which goes beyond laptops and smart connected devices for connected vehicles,smart homes,smart cities,and connected *** massive quantity of data gathered from numerous IoT devices poses security and privacy concerns for *** the increasing use of multimedia in communications,the content security of remote-sensing images attracted much attention in academia and *** encryption is important for securing remote sensing images in the IoT ***,researchers have introduced plenty of algorithms for encrypting *** study introduces an Improved Sine Cosine Algorithm with Chaotic Encryption based Remote Sensing Image Encryption(ISCACE-RSI)technique in IoT *** proposed model follows a three-stage process,namely pre-processing,encryption,and optimal key *** remote sensing images were preprocessed at the initial stage to enhance the image ***,the ISCACERSI technique exploits the double-layer remote sensing image encryption(DLRSIE)algorithm for encrypting the *** DLRSIE methodology incorporates the design of Chaotic Maps and deoxyribonucleic acid(DNA)Strand Displacement(DNASD)*** chaotic map is employed for generating pseudorandom sequences and implementing routine scrambling and diffusion processes on the plaintext ***,the study presents three DNASD-related encryption rules based on the variety of DNASD,and those rules are applied for encrypting the images at the DNA sequence *** an optimal key generation of the DLRSIE technique,the ISCA is applied with an objective function of the maximization of peak signal to noise ratio(PSNR).To examine the performance of the ISCACE-RSI model,a detailed set of simulations were *** comparative study reported the better performance of the ISCACE-RSI model over other existing approaches.

关键词： Remote sensing internet of things image encryption security optimal key generation

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Metaheuristics Enabled Clustering with Routing Scheme for Wireless Sensor Networks

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Computers, Materials & Continua 2022年第12期73卷 5491-5507页

作者： Mashael M.Asiri Saud S.Alotaibi Dalia H.Elkamchouchi Amira Sayed a.aziz Manar Ahmed Hamza Abdelwahed Motwakel Abu Sarwar Zamani Ishfaq Yaseen Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Wireless Sensor Network(WSN)is a vital element in Internet of Things(IoT)as the former enables the collection of huge quantities of data in energy-constrained *** offers independent access to the target region and performs data collection in an effective *** energy constraints remain a challenging issue in WSN since it operates on in-built *** studies conducted earlier recommended that the energy spent on communication processmust be considerably reduced to improve the efficiency of *** organization and optimal selection of the routes are considered as NP hard optimization problems which can be resolved with the help of metaheuristic *** and routing are considered as effective approaches in enhancing the energy effectiveness and lifespan of *** this background,the current study develops an Improved Duck and Traveller Optimization(IDTO)-enabled cluster-based Multi-Hop Routing(IDTOMHR)technique for ***,IDTO algorithm is exploited for the selection of Cluster Head(CH)and construction of ***,Artificial Gorilla Troops Optimization(ATGO)technique is also used to derive an optimal set of routes to the *** clustering and routing approaches derive a fitness function with the inclusion of multiple input *** proposed IDTOMHR model was experimentally validated for its performance under different *** extensive experimental results confirmed the better performance of IDTOMHR model over other recent approaches.

关键词： Wireless sensor network clustering routing metaheuristics energy efficiency lifetime

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Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

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Computers, Materials & Continua 2023年第5期75卷 3239-3255页

作者： Majdy M.Eltahir Adil Yousif Fadwa Alrowais Mohamed K.Nour Radwa Marzouk Hatim Dafaalla Asma Abbas Hassan Elnour Amira Sayed a.aziz Manar Ahmed Hamza Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Arts and Science Najran UniversitySharourahSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Applied SciencesKing Khalid UniversityMuhayil63772Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event *** is especially applicable in the case of elderly or disabled people who live self-reliantly in their *** sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during *** is one of the most important problems confronted by older people and people with movement *** previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled ***,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor ***,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s *** this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)*** presented IWODL-FDDP model aims to identify the fall events to assist disabled *** presented IWODLFDDP model applies an image filtering approach to pre-process the ***,the EfficientNet-B0 model is utilized to generate valuable feature vector ***,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall ***,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the *** experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.

关键词： Fall detection disabled people deep learning improved whale optimization assisted living

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Chaotic Pigeon Inspired Optimization Technique for Clustered Wireless Sensor Networks

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Computers, Materials & Continua 2022年第12期73卷 6547-6561页

作者： Anwer Mustafa Hilal Aisha Hassan Abdalla Hashim Sami Dhahbi Dalia H.Elkamchouchi Jaber S.Alzahrani Mrim M.Alnfiai Amira Sayed a.aziz Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University Malaysia53100Kuala LumpurMalaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaifP.O.Box 11099Taif21944Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Wireless Sensor Networks(WSN)interlink numerous Sensor Nodes(SN)to support Internet of Things(loT)*** the data gathered from SNs can be divulged,tempered,and *** WSN data processes manage the data in a centralized format at terminal *** devices are prone to attacks and the security of systems can get *** is a distributed and decentralized technique that has the ability to handle security issues in *** security issues include transactions that may be copied and spread across numerous nodes in a peer-peer network *** breaches the mutual trust and allows data immutability which in turn permits the network to go *** some instances,few nodes die or get compromised due to heavy power *** current article develops an Energy Aware Chaotic Pigeon Inspired Optimization based Clustering scheme for Blockchain assisted WSN technique abbreviated as EACPIO-CB *** primary objective of the proposed EACPIO-CB model is to proficiently group the sensor nodes into clusters and exploit Blockchain(BC)for inter-cluster communication in the *** select ClusterHeads(CHs)and organize the clusters,the presented EACPIO-CB model designs a fitness function that involves distinct input ***,BC technology enables the communication between one CH and the other and with the Base Station(BS)in the *** authors conducted comprehensive set of simulations and the outcomes were investigated under different *** simulation results confirmed the better performance of EACPIO-CB method over recent methodologies.

关键词： Blockchain wireless sensor networks clustering energy efficiency security data transmission

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Hybrid Metaheuristics Feature Selection with Stacked Deep Learning-Enabled Cyber-Attack Detection Model

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Computer Systems Science & Engineering 2023年第5期45卷 1679-1694页

作者： Mashael M Asiri Heba G.Mohamed Mohamed K Nour Mesfer Al Duhayyim Amira Sayed a.aziz Abdelwahed Motwakel Abu Sarwar Zamani Mohamed I.Eldesouki Department of Computer Science College of Science&Art atMahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Due to exponential increase in smart resource limited devices and high speed communication technologies,Internet of Things(IoT)have received significant attention in different application ***,IoT environment is highly susceptible to cyber-attacks because of memory,processing,and communication *** traditional models are not adequate for accomplishing security in the IoT environment,the recent developments of deep learning(DL)models find *** study introduces novel hybrid metaheuristics feature selection with stacked deep learning enabled cyber-attack detection(HMFS-SDLCAD)*** major intention of the HMFS-SDLCAD model is to recognize the occurrence of cyberattacks in the IoT *** the preliminary stage,data pre-processing is carried out to transform the input data into useful *** addition,salp swarm optimization based on particle swarm optimization(SSOPSO)algorithm is used for feature selection ***,stacked bidirectional gated recurrent unit(SBiGRU)model is utilized for the identification and classification of ***,whale optimization algorithm(WOA)is employed for optimal hyperparameter optimization *** experimental analysis of the HMFS-SDLCAD model is validated using benchmark dataset and the results are assessed under several *** simulation outcomes pointed out the improvements of the HMFS-SDLCAD model over recent approaches.

关键词： Cyberattacks security deep learning internet of things feature selection data classification

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