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Demonstration of synaptic and resistive switching characteristics in W/TiO_(2)/HfO_(2)/TaN memristor crossbar array for bioinspired neuromorphic computing

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Journal of Materials Science & Technology 2022年第1期96卷 94-102页

作者： Muhammad Ismail Umesh Chand Chandreswar Mahata jamel nebhen Sungjun Kim Division of Electronics and Electrical Engineering Dongguk UniversitySeoul 04620South Korea Department of Electrical and Computer Engineering National University SingaporeSingapore 117583Singapore College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj 11942Saudi Arabia

In this study,resistive random-access memory(RRAM)-based crossbar arrays with a memristor W/TiO_(2)/HfO_(2)/TaN structure were fabricated through atomic layer deposition(ALD)to investigate synaptic plasticity and resistive switching(RS)characteristics for bioinspired neuromorphic computing.X-ray photoelectron spectroscopy(XPS)was employed to explore oxygen vacancy concentrations in bilayer TiO_(2)/HfO_(2)*** fitting for O1s peaks confirmed that the HfO_(2)layer contained a larger number of oxygen vacancies than the TiO_(2)*** addition,HfO_(2)had lower Gibbs free energy(ΔG°=-1010.8 kJ/mol)than the TiO_(2)layer(ΔG°=-924.0 kJ/mol),resulting in more oxygen vacancies in the HfO_(2)*** results andΔG°magnitudes confirmed that formation/disruption of oxygen-based conductive filaments took place in the TiO_(2)*** W/TiO_(2)/HfO_(2)/TaN memristive device exhibited excellent and repeatable RS characteristics,including superb 10^(3) dc switching cycles,outstanding 107 pulse endurance,and high-thermal stability(10^(4) s at 125℃)important for digital computing ***,some essential biological synaptic characteristics such as potentiation-depression plasticity,paired-pulse facilitation(PPF),and spike-timing-dependent plasticity(STDP,asymmetric Hebbian and asymmetric anti-Hebbian)were successfully mimicked herein using the crossbar-array memristive *** on experimental results,a migration and diffusion of oxygen vacancy based physical model is proposed to describe the synaptic plasticity and RS *** study demonstrates that the proposed W/TiO_(2)/HfO_(2)/TaN memristor crossbar-array has a significant potential for applications in non-volatile memory(NVM)and bioinspired neuromorphic systems.

关键词： Resistive switching Crossbar-array memristive device Synaptic plasticity TiO_(2)/HfO_(2)film Oxygen vacancy

Design of a Five-Band Dual-Port Rectenna for RF Energy Harvesting

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Computers, Materials & Continua 2021年第10期69卷 487-501页

作者： Surajo Muhammad Jun Jiat Tiang Sew Kin Wong jamel nebhen Amjad Iqbal Centre for Wireless Technology Faculty of EngineeringMultimedia UniversityCyberjaya63100Malaysia College of Computer Science and Engineering Prince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia

This paper proposed the design of a dual-port rectifier with multifrequency *** RF rectifier is achieved using a combination of L-section inductive impedance matching network(IMN)at Port-1 with a multiple stubs impedance transformer at *** fabricated prototype can harvest RF signal from GSM/900,GSM/1800,UMTS/2100,Wi-Fi/2.45 and LTE/2600 frequency bands at(0.94,1.80,2.10,2.46,and 2.63 GHz),*** rectifier occupies a small portion of a PCB board at 0.20λg×0.15λ*** proposed circuit realized a measured peak RF-to-dc(radio frequency direct current)power conversion efficiency(PCE)of(21%,22.76%,25.33%,21.57%,and 22.14%)for an input power of−20 *** RF harvester attains a measured peak RF-to-dc PCE of 72.70%and an output dc voltage of 154 mV for an input power of 3 dBm at 2.46 *** of the proposed rectifier in the ambiance gives a peak dc output voltage of 376.1 mV from the five signal ***,a low-powered bq25504-674 evaluation module(EVM)is integrated with the *** module boost and drive the rectifier output dc voltage to 945 *** performance of the proposed rectifier in the ambiance environment makes it a suitable module for low-powered RF applications.

关键词： RF energy harvesting impedance matching network power conversion efficiency multi-band rectifier

Training Multi-Layer Perceptron with Enhanced Brain Storm Optimization Metaheuristics

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Computers, Materials & Continua 2022年第2期70卷 4199-4215页

作者： Nebojsa Bacanin Khaled Alhazmi Miodrag Zivkovic K.Venkatachalam Timea Bezdan jamel nebhen Singidunum University Danijelova11000BelgradeSerbia National Center for Robotics and IoT Communication and Information Technology Research InstituteKing Abdulaziz City for Science and Technology(KACST)Riyadh12371Saudi Arabia Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Prince Sattam Bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia

In the domain of artificial neural networks,the learning process represents one of the most challenging *** the classification accuracy highly depends on theweights and biases,it is crucial to find its optimal or suboptimal values for the problem at ***,to a very large search space,it is very difficult to find the proper values of connection weights and *** traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local *** commonly,back-propagation is used formulti-layer-perceptron training and it can lead to vanishing gradient *** an alternative approach,stochastic optimization algorithms,such as nature-inspired metaheuristics are more reliable for complex optimization tax,such as finding the proper values of weights and biases for neural network *** thiswork,we propose an enhanced brain storm optimization-based algorithm for training neural *** the simulations,ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization *** results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-theart approaches on the majority of datasets in terms of classification accuracy and convergence speed,due to the capability of balancing the intensification and diversification and avoiding the local *** proposed approach obtained the best accuracy on eight out of ten observed dataset,outperforming all other algorithms by 1-2%on *** mean accuracy is observed,the proposed algorithm dominated on nine out of ten datasets.

关键词： Artificial neural network optimization metaheuristics algorithm hybridization brain storm optimization

A Hybrid Approach for Network Intrusion Detection

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Computers, Materials & Continua 2022年第1期70卷 91-107页

作者： Mavra Mehmood Talha Javed jamel nebhen Sidra Abbas Rabia Abid Giridhar Reddy Bojja Muhammad Rizwan Department of Computer Science Kinnaird College for WomenLahore54000Pakistan ASET Labs IslamabadPakistan Prince Sattam bin Abdulaziz University College of Computer Science and EngineeringAlkharj11942Saudi Arabia College of Business and Information Systems Dakota State UniversityMadisonUnited States of America

Due to the widespread use of the internet and smart devices,various attacks like intrusion,zero-day,Malware,and security breaches are a constant threat to any organization’s network ***,a Network Intrusion Detection System(NIDS)is required to detect attacks in network *** paper proposes a new hybrid method for intrusion detection and attack *** proposed approach comprises three steps to address high false and low false-negative rates for intrusion detection and attack *** the first step,the dataset is preprocessed through the data transformation technique and min-max ***,the random forest recursive feature elimination method is applied to identify optimal features that positively impact the model’s ***,we use various Support Vector Machine(SVM)types to detect intrusion and the Adaptive Neuro-Fuzzy System(ANFIS)to categorize probe,U2R,R2U,and DDOS *** validation of the proposed method is calculated through Fine Gaussian SVM(FGSVM),which is 99.3%for the binary *** Square Error(MSE)is reported as 0.084964 for training data,0.0855203 for testing,and 0.084964 to validate multiclass categorization.

关键词： Network security intrusion detection system machine learning attacks data mining classification feature selection

Design of Latency-Aware IoT Modules in Heterogeneous Fog-Cloud Computing Networks

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Computers, Materials & Continua 2022年第3期70卷 6057-6072页

作者： Syed Rizwan Hassan Ishtiaq Ahmad jamel nebhen Ateeq Ur Rehman Muhammad Shafiq Jin-Ghoo Choi Department of Electrical Engineering The University of LahoreLahore54000Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Electrical Engineering Government College UniversityLahore54000Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

The modern paradigm of the Internet of Things(IoT)has led to a significant increase in demand for latency-sensitive applications in Fog-based cloud ***,such applications cannot meet strict quality of service(QoS)*** large-scale deployment of IoT requires more effective use of network infrastructure to ensure QoS when processing big ***,cloud-centric IoT application deployment involves different modules running on terminal devices and cloud *** devices with different computing capabilities must process the data generated by the end device,so deploying latency-sensitive applications in a heterogeneous fog computing environment is a difficult *** addition,when there is an inconsistent connection delay between the fog and the terminal device,the deployment of such applications becomes more *** this article,we propose an algorithm that can effectively place application modules on network nodes while considering connection delay,processing power,and sensing data *** with traditional cloud computing deployment,we conducted simulations in iFogSim to confirm the effectiveness of the *** simulation results verify the effectiveness of the proposed algorithm in terms of end-to-end delay and network ***,latency and execution time is insensitive to the number of sensors.

关键词： IoT fog-cloud computing architecture module placement latency sensitive application resource aware placement

Energy Efficiency Trade-off with Spectral Efficiency in MIMO Systems

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Computers, Materials & Continua 2022年第3期70卷 5889-5905页

作者： Rao Muhammad Asif Mustafa Shakir jamel nebhen Ateeq Ur Rehman Muhammad Shafiq Jin-Ghoo Choi Department of Electrical Engineering Superior UniversityLahore54000Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Electrical Engineering Government College UniversityLahore54000Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

5G technology can greatly improve spectral efficiency(SE)and throughput of wireless *** this regard,multiple inputmultiple output(MIMO)technology has become the most influential technology using huge antennas and user equipment(UE).However,the use of MIMO in 5G wireless technology will increase circuit power consumption and reduce energy efficiency(EE).In this regard,this article proposes an optimal solution for weighing SE and throughput tradeoff with energy *** research work is based on theWyner model of uplink(UL)and downlink(DL)transmission under the multi-cell model *** SE-EE trade-off is carried out by optimizing the choice of antenna and UEs,while the approximation method based on the logarithmic function is used for *** this paper,we analyzed the combination of UL and DL power consumption models and precoding schemes for all actual circuit power consumption models to optimize the trade-off between EE and *** simulation results show that the SE-EE trade-off has been significantly improved by developing UL and DL transmission models with the approximation method based on logarithmic *** is also recognized that the throughput-EE trade-off can be improved by knowing the total actual power consumed by the entire network.

关键词： Energy efficiency spectral efficiency throughput massive MIMO downlink uplink base stations power consumption

Toward Optimal Cost-Energy Management Green Framework for Sustainable Future Wireless Networks

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Computers, Materials & Continua 2021年第7期68卷 1321-1339页

作者： Mohammed H.Alsharif Abu Jahid Mahmoud A.Albreem Peerapong Uthansakul jamel nebhen Khalid Yahya Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006Korea Department of Electrical and Computer Engineering University of OttawaOttawaK1N 6N5ONCanada Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra400Oman School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Mechatronics Faculty of Engineering and ArchitectureIstanbul Gelisim UniversityIstanbul34310Turkey

The design of green cellular networking according to the trafc arrivals has the capability to reduce the overall energy consumption to a cluster in a cost-effective *** cell zooming approach has appealed much attention that adaptively ofoads the BS load demands adjusting the transmit power based on the trafc intensity and green energy ***,the researchers are focused on implementing renewable energy resources,which are considered the most attractive practices in designing energy-efcient wireless networks over the long term in a cost-efcient way in the existing *** utilization of available solar can be adapted to acquire cost-effective and reliable power supply to the BSs,especially that sunlight is free,available everywhere,and a good alternative energy option for the remote ***,planning a photovoltaic scheme necessitates viability assessment to avoid poor power supply,particularly for ***,cellular operators need to consider both technical and economic factors before the implementation of solar-powered *** paper proposed the usercentric cell zooming policy of solar-powered cellular base stations taking into account the optimal technical criteria obtained by the HOMER software *** results have shown that the proposed system can provide operational expenditure(OPEX)savings of up to 47%.In addition,the efcient allocation of resource blocks(RBs)under the cell zooming technique attain remarkable energy-saving performance yielding up to 27%.

关键词： Wireless networks beyond 5G green communications sustainability OPEX communication systems

An Efficient Internet Traffic Classification System Using Deep Learning for IoT

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Computers, Materials & Continua 2022年第4期71卷 407-422页

作者： Muhammad Basit Umair Zeshan Iqbal Muhammad Bilal jamel nebhen Tarik Adnan Almohamad Raja Majid Mehmood Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Division of Computer and Electronics Systems Engineering Hankuk University of Foreign StudiesYongin-siKorea Electrical-Electronics Engineering Department Faculty of EngineeringKarabük University78050KarabükTurkey Prince Sattam bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia Information and Communication Technology Department School of Electrical and Computer EngineeringXiamen University MalaysiaSepang43900Malaysia

Internet of Things(IoT)defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central *** IoT devices are connected to a network therefore prone to *** management tasks and network operations such as security,intrusion detection,Quality-of-Service provisioning,performance monitoring,resource provisioning,and traffic engineering require traffic *** to the ineffectiveness of traditional classification schemes,such as port-based and payload-based methods,researchers proposed machine learning-based traffic classification systems based on shallow neural ***,machine learning-based models incline to misclassify internet traffic due to improper feature *** this research,an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet *** examine the performance of the proposed technique,Moore-dataset is used for training the *** proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network(DNN).In particular,the maximum entropy classifier is used to classify the internet *** experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification,i.e.,99.23%.Furthermore,the proposed algorithm achieved the highest accuracy compared to the support vector machine(SVM)based classification technique and k-nearest neighbours(KNNs)based classification technique.

关键词： Deep learning internet traffic classification network traffic management QoS aware application classification

Optimal Cost-Aware Paradigm for Off-Grid Green Cellular Networks in Oman

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Computers, Materials & Continua 2021年第8期68卷 2665-2680页

作者： Mohammed H.Alsharif Kannadasan Raju Abu Jahid Mahmoud A.Albreem Peerapong Uthansakul jamel nebhen Venkatesan Chandrasekaran Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006Korea Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India Department of Electrical and Computer Engineering University of OttawaOttawaK1N 6N5ONCanada Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra400Oman School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand Prince Sattam bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia

Green wireless networks or energy-efficient wireless networks have gained popularity as a research topic due to the ecological and economic concerns of cellular *** specific power supply requirements for the cellular base station,such as cost-effectiveness,efficiency,sustainability,and reliability,can be met by utilizing the technological advances in renewable *** are numerous drivers for the deployment of renewable energy technologies and the transition towards green *** energy is free,clean,and abundant in most locations throughout the ***,this work proposes a novel framework for energy-efficient solar-powered base stations for the Oman site,specifically for off-grid locations where fuel transportation for diesel generator(DG)is a serious *** demonstrate the effectiveness of the proposed system for off-grid sites,the Hybrid Optimization Model for Electric Renewables optimization software is adapted by considering real-time conditions and its technical *** cost factors such as capital cost,salvage cost,replacement cost,operational,and maintenance cost of PV panels,inverters,and batteries also undergo extensive *** the observed results,the total net present cost(NPC)of the proposed system is$27,887,while the net NPC of the DG is estimated at$32,***,the proposed scheme can potentially achieve considerable savings in the operational expenditure at approximately 15.24%.Indeed,these outcomes can provide profound economic,technical,and ecological benefits to the cellular operators of *** also ensures a sizeable reduction in greenhouse gas that supports sustainable green wireless network deployment in remote areas.

关键词： Wireless networks green wireless networks green communications sustainability OPEX