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

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 *** article addresses the limitations of current logistics path optimization methods,such as inefficiencies and high operational *** 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 *** 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 *** outperforms these algorithms,achieving a minimum path distance of 546 units,highlighting its prowess in logistics path *** comprehensive evaluation authenticates HFSHO’s exceptional performance across various logistic optimization *** findings emphasize the critical significance of selecting an appropriate algorithm for logistics path navigation,with HFSHO emerging as an efficient *** the synergistic use of FO and SHO,HFSHO achieves a 15%improvement in convergence,heightened operational efficiency and substantial cost reductions in logistics *** 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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Exploring Multi-Task Learning for Forecasting Energy-Cost Resource Allocation in IoT-Cloud Systems

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Computers, Materials & Continua 2024年第6期79卷 4603-4620页

作者： Mohammad Aldossary Hatem A.Alharbi nasir ayub Department of Computer Engineering and Information College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Al-Dawasir11991Saudi Arabia Department of Computer Engineering College of Computer Science and EngineeringTaibah UniversityMadinah42353Saudi Arabia Department of Creative Technologies Air University IslamabadIslamabad44000Pakistan

Cloud computing has become increasingly popular due to its capacity to perform computations without relying on physical infrastructure,thereby revolutionizing computer ***,the rising energy consumption in cloud centers poses a significant challenge,especially with the escalating energy *** paper tackles this issue by introducing efficient solutions for data placement and node management,with a clear emphasis on the crucial role of the Internet of Things(IoT)throughout the research *** IoT assumes a pivotal role in this study by actively collecting real-time data from various sensors strategically positioned in and around data *** sensors continuously monitor vital parameters such as energy usage and temperature,thereby providing a comprehensive dataset for *** data generated by the IoT is seamlessly integrated into the Hybrid TCN-GRU-NBeat(NGT)model,enabling a dynamic and accurate representation of the current state of the data center *** the incorporation of the Seagull Optimization Algorithm(SOA),the NGT model optimizes storage migration strategies based on the latest information provided by IoT *** model is trained using 80%of the available dataset and subsequently tested on the remaining 20%.The results demonstrate the effectiveness of the proposed approach,with a Mean Squared Error(MSE)of 5.33%and a Mean Absolute Error(MAE)of 2.83%,accurately estimating power prices and leading to an average reduction of 23.88%in power ***,the integration of IoT data significantly enhances the accuracy of the NGT model,outperforming benchmark algorithms such as DenseNet,Support Vector Machine(SVM),Decision Trees,and *** NGT model achieves an impressive accuracy rate of 97.9%,surpassing the rates of 87%,83%,80%,and 79%,respectively,for the benchmark *** findings underscore the effectiveness of the proposed method in optimizing energy efficiency and enhancing the predictive

关键词： Cloud computing energy efficiency data center optimization internet of things(IoT) hybrid models

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Energy Theft Identification Using Adaboost Ensembler in the Smart Grids

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Computers, Materials & Continua 2022年第7期72卷 2141-2158页

作者： Muhammad Irfan nasir ayub Faisal Althobiani Zain Ali Muhammad Idrees Saeed Ullah Saifur Rahman Abdullah Saeed Alwadie Saleh Mohammed Ghonaim Hesham Abdushkour Fahad Salem Alkahtani Samar Alqhtani Piotr Gas Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science Federal Urdu University of Science and TechnologyIslamabad44000Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Engineering University of Engineering and TechnologyNarowal CampusLahore54000Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia Department of Electrical and Power Engineering AGH University of Science and Technology Mickiewicza 30 AvenueKrakow30-059Poland

One of the major concerns for the utilities in the Smart Grid(SG)is electricity *** the implementation of smart meters,the frequency of energy usage and data collection from smart homes has increased,which makes it possible for advanced data analysis that was not previously *** this purpose,we have taken historical data of energy thieves and normal *** avoid imbalance observation,biased estimates,we applied the interpolation ***,the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further *** proposing an improved version of Zeiler and Fergus Net(ZFNet)as a feature extraction approach,we had able to reduce the model’s time *** minimize the overfitting issues,increase the training accuracy and reduce the training loss,we have proposed an enhanced method by merging Adaptive Boosting(AdaBoost)classifier with Coronavirus Herd Immunity Optimizer(CHIO)and Forensic based Investigation Optimizer(FBIO).In terms of low computational complexity,minimized over-fitting problems on a large quantity of data,reduced training time and training loss and increased training accuracy,our model outperforms the benchmark *** proposed algorithms Ada-CHIO andAda-FBIO,have the low MeanAverage Percentage Error(MAPE)value of error,i.e.,6.8%and 9.5%,***,due to the stability of our model our proposed algorithms Ada-CHIO and Ada-FBIO have achieved the accuracy of 93%and 90%.Statistical analysis shows that the hypothesis we proved using statistics is authentic for the proposed technique against benchmark algorithms,which also depicts the superiority of our proposed techniques.

关键词： Smart grids and meters electricity theft detection machine learning AdaBoost optimization techniques

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Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

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Computers, Materials & Continua 2022年第9期72卷 4249-4265页

作者： Muhammad Irfan Ali Raza Faisal Althobiani nasir ayub Muhammad Idrees Zain Ali Kashif Rizwan Abdullah Saeed Alwadie Saleh Mohammed Ghonaim Hesham Abdushkour Saifur Rahman Omar Alshorman Samar Alqhtani Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadWah Campus22060Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Federal Urdu University of ArtsScience and TechnologyIslamabad44000Pakistan School of Electrical Engineering and Computer Science National University of Science and TechnologyIslamabad44000Pakistan Department of Computer Science and Engineering University of Engineering and TechnologyNarowal CampusLahore54000Pakistan Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia

In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial ***,electricity demand and price forecasting play a significant role and can help in terms of reliability and *** to the massive amount of data,big data analytics for forecasting becomes a hot topic in the SG *** this paper,the changing and non-linearity of consumer consumption pattern complex data is taken as *** minimize the computational cost and complexity of the data,the average of the feature engineering approaches includes:Recursive Feature Eliminator(RFE),Extreme Gradient Boosting(XGboost),Random Forest(RF),and are upgraded to extract the most relevant and significant *** this end,we have proposed the DensetNet-121 network and Support Vector Machine(SVM)ensemble with Aquila Optimizer(AO)to ensure adaptability and handle the complexity of data in the ***,the AO method helps to tune the parameters of DensNet(121 layers)and SVM,which achieves less training loss,computational time,minimized overfitting problems and more training/test *** evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark *** proposed method has achieved a minimal value of the Mean Average Percentage Error(MAPE)rate i.e.,8%by DenseNet-AO and 6%by SVM-AO and the maximum accurateness rate of 92%and 95%,respectively.

关键词： Smart grid deep neural networks consumer demand big data analytics load forecasting price forecasting

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Power Scheduling with Max User Comfort in Smart Home:Performance Analysis and Tradeoffs

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Computer Systems Science & Engineering 2023年第8期46卷 1723-1740页

作者： Muhammad Irfan Ch.Anwar Ul Hassan Faisal Althobiani nasir ayub Raja Jalees Ul Hussen Khan Emad Ismat Ghandourah Majid A.Almas Saleh Mohammed Ghonaim V.R.Shamji Saifur Rahman Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Creative Technologies Air University Islamabad44000IslamabadPakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Engineering Captial University of Science and Technology44000IslamabadPakistan Department of Software Engineering Superior University Lahore53400Pakistan Nuclear Engineering Department King Abdulaziz UniversityJeddah21589Saudi Arabia Marine Engineering Department Faculty of Maritime StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia

The smart grid has enabled users to control their home energy more effectively and efficiently.A home energy management system(HEM)is a challenging task because this requires the most effective scheduling of intelligent home appliances to save ***,we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm(GWA)and Harmony Search Algorithms(HSA).Moreover,a fusion initiated on HSA and GWA operators is used to optimize energy ***,many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain *** has proven beneficial in achieving numerous objectives simultaneously,decreasing the peak-to-average ratio and power *** MATLAB simulations are cast-off to evaluate the routine of the anticipated method,Harmony GWA(HGWA).The simulations are for a multifamily housing complex outfitted with various cool *** simulation results indicate that GWA functions better regarding cost savings than *** reputes of PAR,HSA is significantly more effective than *** suggested method reduces costs for single and ten-house construction by up to 2200.3 PKR,as opposed to 503.4 in GWA,398.10 in HSA and 640.3 in *** suggested approach performed better than HSA and GWA in PAR *** single-family homes in HGWA,GWA and HSA,the reduction in PAR is 45.79%,21.92%and 20.54%,*** hybrid approach,however,performs better than the currently used nature-inspired techniques in terms of Cost and PAR.

关键词： Metaheuristics techniques artificial intelligence energy management data analytics smart grid smart home

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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 *** such systems,all participants related to commercial and industrial systems must communicate and generate ***,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 ***,as the number of participants increases,the size of generated data also ***,such a centralized mechanism for data collection and exchange between participants is likely to face numerous challenges in terms of security,privacy,and *** 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 ***,they only share updated training models that are trained over their private *** 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 ***,slow model training and the execution of additional unnecessary communication rounds may hinder FL applications from operating properly in a distributed ***,these unnecessary communication rounds make the system vulnerable to security and privacy issues,because irrelevant model updates are sent between clients and ***,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 *** proposed solution uses the impetus term to speed up model convergence during the model training ***,it establishes a secure communication channel between IoT devices and the *** a

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

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In vitro Selection for Fusarium Wilt Resistance in Gladiolus

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Journal of Integrative Plant Biology 2008年第5期50卷 601-612页

作者： Idrees Ahmad nasir Sheikh Riazuddin National Centre of Excellence in Molecular Biology University of the PunjabCanal BankThokar Niaz Baig Lahore 53700Pakistan

Cormels pieces of four Fusarium susceptible Gladiolus cultivars （Friendship, Peter Pears, Victor Borge and Novalux） formed friable calli when cultured in vitro on Murashige and Skoog basal medium containing various concentrations of auxin and cytokinin. The friable calli established cell suspensions. Plantlet regeneration was obtained from the control callus, control cell suspension derived callus and in vitro selected Fusarium oxysporum Schlecht. resistant cell-lines of Friendship. The in vitro cormlets showed 85-95% germination after breaking dormancy of 8 weeks at 4℃. Cell suspensions of all four Gladiolus cultivars were found to be highly sensitive to fusaric acid. Gradual increase in fusaric acid concentrations to the cell-suspension cultures decreased cell growth considerably. One albino plant was found from the second generation of the in vitro selected cell line of Friendship. The albino plant was found to be highly susceptible to F. oxysporum. The cormlets of all in vitro selected cell lines of Friendship were inoculated with a conidial suspension of the F. oxysporum before planting and were also sprayed with the same spore suspension for further characterization when the height of plants was about 6cm. The four selected cell lines showed the same response whether or not they were inoculated with conidia of the F. oxysporum. Plantlets of all of the selected cell lines exhibited significant growth as compared with the control after application of conidia of the F. oxysporum.

关键词： cell suspension fusaric acid fusadum Gladiolus in vitro selection regeneration.

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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： Suliman Khan Abdul nasir Medical Research Center The Second Affiliated Hospital of Zhengzhou UniversityZhengzhou540014China

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 *** 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： protective NogoA clinical

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Effects of f(R) Model on Dynamics of Axial Shear-Free Dissipative Fluids

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Communications in Theoretical Physics 2016年第4期65卷 483-491页

作者： M.Sharif Zunaira nasir Department of Mathematics University of the Punjab

We present a general analysis on non-static axial system with dissipative shear-free anisotropic fluid using polynomial inflationary f(R) *** study the effects of dissipation on the dynamics of geodesic matter *** leads the system either to rotation-free or expansion-free but not both simultaneously under geodesic *** is found that the system preserves its symmetry in both *** the rotation-free case,when there is no dissipation and Ricci scalar is constant,the axial system reduces to FRW universe *** is exactly the same result obtained in general relativity.

关键词： f(R) gravity dissipative systems self-gravitating systems

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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 *** highest final body weight was obtained in the group supplemented with BPC in starter and grower *** 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 *** summary,the results of the study indicated that addition of BPC in broiler diets in the

关键词： Antibiotic Bioactive peptide Broiler Immunity Lincomycin Vitamin E

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