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Differential evolution based computation intelligence solver for elliptic partial differential equations

Frontiers of Information Technology & Electronic Engineering 2019年第10期20卷 1445-1456页

作者： Muhammad Faisal FATEH Aneela ZAMEER Sikander mmirza Nasir MMIRZA Muhammad Saeed ASLAM Muhammad Asif Zahoor RAJA Department of Electrical Engineering Pakistan Institute of Engineering and Applied Sciences(PIEAS)Islamabad 45650Pakistan Department of Computer and Information Sciences Pakistan Institute of Engineering and Applied Sciences(PIEAS)Islamabad 45650Pakistan Department of Physics and Applied Mathematics Pakistan Institute of Engineering and Applied Sciences(PIEAS)Islamabad 45650Pakistan School of Electrical and Electronic Engineering University of AdelaideAdelaide 5005Australia Department of Electrical and Computer Engineering COMSATS University IslamabadAttock CampusAttock 43600Pakistan

A differential evolution based methodology is introduced for the solution of elliptic partial differential equations (PDEs) with Dirichlet and/or Neumann boundary conditions. The solutions evolve over bounded domains throughout the interior nodes by minimization of nodal deviations among the population. The elliptic PDEs are replaced by the corresponding system of finite difference approximation, yielding an expression for nodal residues. The global residue is declared as the root-mean-square value of the nodal residues and taken as the cost function. The standard differential evolution is then used for the solution of elliptic PDEs by conversion to a minimization problem of the global residue. A set of benchmark problems consisting of both linear and nonlinear elliptic PDEs has been considered for validation, proving the effectiveness of the proposed algorithm. To demonstrate its robustness, sensitivity analysis has been carried out for various differential evolution operators and parameters. Comparison of the differential evolution based computed nodal values with the corresponding data obtained using the exact analytical expressions shows the accuracy and convergence of the proposed methodology.

关键词： Differential evolution Boundary value problems Partial differential equation Finite difference scheme Numerical computing

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Can NogoA Be a Suitable Target to Treat Ischemic Stroke?

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NEUROSCIENCE BULLETIN 2024年第4期40卷 557-560页

作者： Khan, Suliman nasir, Abdul Zhengzhou Univ Med Res Ctr Affiliated Hosp 2 Zhengzhou 540014 Peoples R China

Treating stroke or restoring brain function after stroke remains challenging for clinicians[1,2].Researchers have largely focused on developing neuroprotective strategies and translating these discoveries from rodent experiments to the clinical setting;however,these have been typified by several failures[2].It is known that astrocytes play a crucial role in the pathogenesis of ischemic stroke[3,4].They are activated in response to stimuli arising from injury,characterized by drastic changes to their morphology and function-associated gene expression.Reactive astrocytes exacerbate secondary neurodegeneration(repair of nervous tissue by the generation of new neurons,glial cells,axons,myelin,or synapses)[5]as well as provide neuroprotection during CNS pathologies[6].It is worth noting that myelin-related neurite growth inhibitors induce the suppression of axon regeneration after stroke[7].

关键词： PROMOTES AXONAL REGENERATION FOCAL CEREBRAL-ISCHEMIA INHIBITOR NEURONS RATS

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Federated Learning Security and Privacy-Preserving Algorithm and Experiments Research Under Internet of Things Critical Infrastructure

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Tsinghua Science and Technology 2024年第2期29卷 400-414页

作者： nasir Ahmad Jalali Hongsong Chen Department of Computer Science University of Science and Technology Beijing(USTB)Beijing 100083China

The widespread use of the Internet of Things(IoTs)and the rapid development of artificial intelligence technologies have enabled applications to cross commercial and industrial band settings.Within such systems,all participants related to commercial and industrial systems must communicate and generate data.However,due to the small storage capacities of IoT devices,they are required to store and transfer the generated data to third-party entity called“cloud”,which creates one single point to store their data.However,as the number of participants increases,the size of generated data also increases.Therefore,such a centralized mechanism for data collection and exchange between participants is likely to face numerous challenges in terms of security,privacy,and performance.To address these challenges,Federated Learning(FL)has been proposed as a reasonable decentralizing approach,in which clients no longer need to transfer and store real data in the central server.Instead,they only share updated training models that are trained over their private datasets.At the same time,FL enables clients in distributed systems to share their machine learning models collaboratively without their training data,thus reducing data privacy and security challeges.However,slow model training and the execution of additional unnecessary communication rounds may hinder FL applications from operating properly in a distributed system.Furthermore,these unnecessary communication rounds make the system vulnerable to security and privacy issues,because irrelevant model updates are sent between clients and servers.Thus,in this work,we propose an algorithm for fully homomorphic encryption called Cheon-Kim-Kim-Song(CKKS)to encrypt model parameters for their local information privacy-preserving function.The proposed solution uses the impetus term to speed up model convergence during the model training process.Furthermore,it establishes a secure communication channel between IoT devices and the server.We also use a lightweight secure transport protocol

关键词： Federated Learning(FL) Internet of Things(IoTs) lightweight Transport Layer Security(iTLS) Cheon-Kim-Kim-Song(CKKS)

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Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems

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Computers, Materials & Continua 2023年第12期77卷 3921-3942页

作者： Abdulwahab Ali Almazroi nasir Ayub College of Computing and Information Technology at Khulais Department of Information TechnologyUniversity of JeddahJeddah21959Saudi Arabia Department of Creative Technologies Air University IslamabadIslamabad44000Pakistan

Effectively managing complex logistics data is essential for development sustainability and growth,especially in optimizing distribution routes.This article addresses the limitations of current logistics path optimization methods,such as inefficiencies and high operational costs.To overcome these drawbacks,we introduce the Hybrid Firefly-Spotted Hyena Optimization(HFSHO)algorithm,a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm(FO)with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm(SHO).HFSHO aims to improve logistics path optimization and reduce operational costs.The algorithm’s effectiveness is systematically assessed through rigorous comparative analyses with established algorithms like the Ant Colony Algorithm(ACO),Cuckoo Search Algorithm(CSA)and Jaya Algo-rithm(JA).The evaluation also employs benchmarking methodologies using standardized function sets covering diverse objective functions,including Schwefel’s,Rastrigin,Ackley,Sphere and the ZDT and DTLZ Function suite.HFSHO outperforms these algorithms,achieving a minimum path distance of 546 units,highlighting its prowess in logistics path optimization.This comprehensive evaluation authenticates HFSHO’s exceptional performance across various logistic optimization scenarios.These findings emphasize the critical significance of selecting an appropriate algorithm for logistics path navigation,with HFSHO emerging as an efficient choice.Through the synergistic use of FO and SHO,HFSHO achieves a 15%improvement in convergence,heightened operational efficiency and substantial cost reductions in logistics operations.It presents a promising solution for optimizing logistics paths,offering logistics planners and decision-makers valuable insights and contributing substantively to sustainable sectoral growth.

关键词： Hybrid optimization internet of things intelligent transport system optimal path finding smart logistics traffic congestion supply chain

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Outage Probability Analysis of Free Space Communication System Using Diversity Combining Techniques

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Computers, Materials & Continua 2022年第12期73卷 6001-6017页

作者： Hasnain Kashif Muhammad nasir Khan Department of Electrical Engineering The University of LahoreLahore54000Pakistan

Recently,free space optical(FSO)communication is gaining much attention towards the research community.The reason for this attention is the promises of high data-rate,license-free deployment,and non-interfering links.It can,however,give rise to major system difficulties concerning alignment and atmospheric turbulence.FSO is the degradation in the signal quality because of atmospheric channel impairments and conditions.The worst effect is due to fog particles.Though,Radio Frequency(RF)links are able to transmit the data in foggy conditions but not in rain.To overcome these issues related to both the FSO and RF links.A free space communication system(FSCS)is proposed,in which the hybrid technology is based on the individual FSO and RF channel.FSCS is a capable solution to overcome the difficulties of the existing systems(FSO and RF)as well as to enhance the overall link reliability and availability.In this paper,FSCS is investigated in terms of performance throughput(i.e.,outage probability and bit-error-rate(BER))by implementing the receive diversity combining techniques.An analysis of the outage probability of the proposed system along with the individual FSO and RF system is developed.Simulation results are presented to support the analysis.It is shown that the proposed system outperforms the individual FSO andRF system and gives a power gain of 3dB over a distinct number of receive antennas.

关键词： Atmospheric turbulence free space communication system power management signal independent noise line of sight

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Mixed convectional and chemical reactive flow of nanofluid with slanted MHD on moving permeable stretching/shrinking sheet through nonlinear radiation,energy omission

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Chinese Physics B 2024年第5期33卷 193-202页

作者： Saleem nasir Sekson Sirisubtawee Pongpol Juntharee Taza Gul Department of Mathematics Faculty of Applied ScienceKing Mongkut's University of Technology North BangkokBangkok 10800Thailand Department of Mathematics City University of Science and Information TechnologyPeshawarPakistan

Hybrid nanofluids are remarkable functioning liquids that are intended to reduce the energy loss while maximizing the heat transmission.In the involvement of suction and nonlinear thermal radiation effects,this study attempted to explore the energy transmission features of the inclined magnetohydrodynamic(MHD)stagnation flow of CNTs-hybrid nanofluid across the nonlinear permeable stretching or shrinking sheet.This work also included some noteworthy features like chemical reactions,variable molecular diffusivity,quadratic convection,viscous dissipation,velocity slip and heat omission assessment.Employing appropriate similarity components,the model equations were modified to ODEs and computed by using the HAM technique.The impact of various relevant flow characteristics on movement,heat and concentration profiles was investigated and plotted on a graph.Considering various model factors,the significance of drag friction,heat and mass transfer rate were also computed in tabular and graphical form.This leads to the conclusion that such factors have a considerable impact on the dynamics of fluid as well as other engineering measurements of interest.Furthermore,viscous forces are dominated by increasing the values ofλ_(p),δ_(m)andδ_(q),and as a result,F(ξ)accelerates while the opposite trend is observed for M andφ.The drag friction is boosted by the augmentation M,λ_(p)andφ,but the rate of heat transfer declined.According to our findings,hybrid nanoliquid effects dominate that of ordinary nanofluid in terms of F(ξ),Θ(ξ)andφ(ξ)profiles.The HAM and the numerical technique(shooting method)were found to be in good agreement.

关键词： hybrid nanofluid(SWCNT+MWCNT/H_(2)O) velocity slip conditions nonlinear thermal radiation exponential stretching/shrinking sheet inclined magnetohydrodynamic(MHD)stagnation flow

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基于人工神经网络的小型直流风力发电机控制研究

基于人工神经网络的小型直流风力发电机控制研究

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作者： Muhammad nasir 华北电力大学(北京)

学位级别：硕士

在过去的几年里,人们对风能的预测、规模和控制进行了大量的研究。然而,目前的知识体系仍然缺乏对小型风能的鲁棒和智能控制。因此,本论文提出一种基于人工神经网络(ANN)的永磁直流发电机(PMDC)智能控制方法,然后通过DC/DC变换器在输出... 详细信息

在过去的几年里,人们对风能的预测、规模和控制进行了大量的研究。然而,目前的知识体系仍然缺乏对小型风能的鲁棒和智能控制。因此,本论文提出一种基于人工神经网络(ANN)的永磁直流发电机(PMDC)智能控制方法,然后通过DC/DC变换器在输出端提供稳定的直流电压。整个模型由PMDC发电机、ANN控制模块、DC/DC转换器和DC负载模块组成,其中发电机模块由可变风速模型供电,以模拟汽轮发电系统的实际模型。仿真模型包括在MATLAB Simulink中开发的10KW额定功率的小型风力发电机系统,可以观察到,所提出的控制方法能够产生平衡且平滑的直流输出。在过去的几十年里,人们对风能的预测、可扩展性和控制进行了大量研究。看来早期的结果是有希望的(我们)。尽管近年来在这一领域取得了实质性进展,但在小规模风能的稳健和智能调节方面仍需要进一步的研究和开发。本文首先介绍了人工神经网络的基本原理,即利用机器学习,特别是人工神经网络对小型风力直流发电机进行调节。机器学习,即人工神经网络,用于调节风能。风能系统越来越复杂,需要改进控制方法。人工神经系统是一种复杂的机器学习技术,正被用来解决这个问题。在这项工作中,基于人工神经网络的算法被用于优化小型风力发电机。其次,boost变换器作为电压控制电流源,由使用人工神经网络(ANN)的智能控制器控制。这些控制器修改升压转换器的脉宽调制(PWM)。这种人工控制的升压转换器对发电机中感应的磁场进行调整,以便在风速变化的情况下产生一致的输出。人工神经网络(ANN)使用单个输入(本例中为风速)和单个输出(即升压转换器的PWM)进行训练。它由10个秘密层组成,而这10个隐藏层中的每一个都由10个神经元连接组成。在下一步中,通过使用单独的输入和输出示例对ANN系统进行训练、验证和测试,从而完成ANN系统的测试。此外,均方误差是用来评估前馈神经网络系统运行状况的指标。本文设计的控制模型利用风速的限制值开发和评估。利用 MATLAB Simulink建立了输出功率为10KW的小型风力发电系统的仿真模型。算例表明,如果实施得当,所提出的控制技术可以使风力发电机(DC)产生平衡、平滑的直流输出。

关键词：可再生能源风能人工神经网络弹性和智能控制永磁直流发电

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不同种源乌桕光合与生长特征对土壤养分和微生物的响应研究

不同种源乌桕光合与生长特征对土壤养分和微生物的响应研究

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作者： nasir Shad 江西农业大学

学位级别：硕士

Plant invasion is one of the factors of global change,threatening ecosystem services and functions.Invasive plants are different in physiological characteristics,which make them have a strong competitive advantage in ...

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Prediction of Extremist Behaviour and Suicide Bombing from Terrorism Contents Using Supervised Learning

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Computers, Materials & Continua 2022年第3期70卷 4411-4428页

作者： nasir Mahmood Muhammad Usman Ghani Khan Department of Computer Science University of Engineering and Technology54890Lahore

This study proposes an architecture for the prediction of extremist human behaviour from projected suicide bombings.By linking‘dots’of police data comprising scattered information of people,groups,logistics,locations,communication,and spatiotemporal characters on different social media groups,the proposed architecture will spawn beneficial information.This useful information will,in turn,help the police both in predicting potential terrorist events and in investigating previous events.Furthermore,this architecture will aid in the identification of criminals and their associates and handlers.Terrorism is psychological warfare,which,in the broadest sense,can be defined as the utilisation of deliberate violence for economic,political or religious purposes.In this study,a supervised learning-based approach was adopted to develop the proposed architecture.The dataset was prepared from the suicide bomb blast data of Pakistan obtained from the South Asia Terrorism Portal(SATP).As the proposed architecture was simulated,the supervised learning-based classifiers na飗e Bayes and Hoeffding Tree reached 72.17%accuracy.One of the additional benefits this study offers is the ability to predict the target audience of potential suicide bomb blasts,which may be used to eliminate future threats or,at least,minimise the number of casualties and other property losses.

关键词： Extremism terrorism suicide bombing crime prediction pattern recognition machine learning supervised learning

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Effects of periodical application of bioactive peptides derived from cottonseed on performance,immunity,total antioxidant activity of serum and intestinal development of broilers

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Animal Nutrition 2021年第1期7卷 134-141页

作者： nasir Landy Farshid Kheiri Mostafa Faghani Department of Animal Science Shahrekord BranchIslamic Azad UniversityShahrekord***Iran

This experiment aimed to examine the effect of periodical application of bioactive peptides derived from cottonseed(BPC)in comparison with using sub-therapeutic doses of lincomycin and the excessive in-clusion of vitamin E on performance,immunity,total antioxidant capacity of serum and intestinal morphology of broiler chickens.A total of 240 one-d-old male broiler chicks with similar initial weight(Ross strain)were randomly assigned to 6 groups(8 chicks/pen):non-treated group(basal diet),basal diet supplemented with 2 mg/kg lincomycin,basal diet supplemented with 50 IU vitamin E,basal diet supplemented with 6 g BPC/kg in starter period,basal diet supplemented with 6 g BPC/kg in starter and grower periods and basal diet supplemented with 6 g BPC/kg throughout the whole experiment.The highest final body weight was obtained in the group supplemented with BPC in starter and grower periods.In the finisher phase,broilers fed the diet containing BPC in the starter period and in the whole trial had significantly(P0.05).Broilers supplemented with BPC in starter and grower,and in the whole trial had significantly(P<0.05)higher antibody titers against sheep red blood cells(SRBC).The highest total antioxidant capacity was obtained in broilers supplemented with the excessive level of vitamin E,furthermore it tended to improve in broilers fed the diet containing BPC in the whole trial.In summary,the results of the study indicated that addition of BPC in broiler diets in the whole trial could improve FCR,immune responses a

关键词： Antibiotic Bioactive peptide Broiler Immunity Lincomycin Vitamin E

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