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Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

Computers, Materials & Continua 2021年第5期67卷 1413-1427页

作者： Bilal Shoaib Yasir Javed Muhammad Adnan Khan Fahad Ahmad Rizwan Majeed Muhammad Saqib Nawaz Muhammad Adeel Ashraf abid iqbal Muhammad Idrees School of Computer Science Minhaj University LahoreLahore54000Pakistan Prince Sultan University Riyadh11586Saudi Arabia Department of Computer Science Riphah International University Lahore CampusLahore54000Pakistan Department of Basic Sciences Deanship of Common First YearJouf UniversitySakakaAljouf72341Saudi Arabia Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science University of Management and TechnologyLahore54770Pakistan PUCIT University of the PunjabLahore54000Pakistan

For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this *** proposed algorithm lends itself towards the parallel implementation as in the FPGA *** the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is *** computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this *** proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its *** the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than *** new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input *** experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm.

关键词： Kernel methods square root adaptive filtering givens rotation mackey glass time series prediction recursive least squares kernel recursive least squares extended kernel recursive least squares square root extended kernel recursive least squares algorithm

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Cybernet Model:A New Deep Learning Model for Cyber DDoS Attacks Detection and Recognition

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Computers, Materials & Continua 2024年第1期78卷 1275-1295页

作者： Azar abid Salih Maiwan Bahjat Abdulrazaq Department of Information Technology Technical College of DuhokDuhok Polytechnic UniversityDuhokIraq Department of Computer Science Faculty of ScienceUniversity of ZakhoDuhokIraq

Cyberspace is extremely dynamic,with new attacks arising *** cybersecurity controls is vital for network *** Learning(DL)models find widespread use across various fields,with cybersecurity being one of the most crucial due to their rapid cyberattack detection capabilities on networks and *** capabilities of DL in feature learning and analyzing extensive data volumes lead to the recognition of network traffic *** study presents novel lightweight DL models,known as Cybernet models,for the detection and recognition of various cyber Distributed Denial of Service(DDoS)*** models were constructed to have a reasonable number of learnable parameters,i.e.,less than 225,000,hence the name“lightweight.”This not only helps reduce the number of computations required but also results in faster training and inference ***,these models were designed to extract features in parallel from 1D Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM),which makes them unique compared to earlier existing architectures and results in better performance *** validate their robustness and effectiveness,they were tested on the CIC-DDoS2019 dataset,which is an imbalanced and large dataset that contains different types of DDoS *** results revealed that bothmodels yielded promising results,with 99.99% for the detectionmodel and 99.76% for the recognition model in terms of accuracy,precision,recall,and F1 ***,they outperformed the existing state-of-the-art models proposed for the same ***,the proposed models can be used in cyber security research domains to successfully identify different types of attacks with a high detection and recognition rate.

关键词： Deep learning CNN LSTM Cybernet model DDoS recognition

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Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid iqbal Yonis Gulzar Kauser Hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of Information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

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Film Flow of Nano-Micropolar Fluid with Dissipation Effect

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2487-2512页

作者： Abuzar abid Siddiqui Mustafa Turkyilmazoglu Department of Basic Sciences&Humanities Faculty of Engineering&TechnologyBahauddin Zakariya UniversityMultanPakistan Department of Mathematics Hacettepe UniversityAnkaraTürkiye Department of Medical Research China Medical University HospitalChina Medical UniversityTaichungTaiwanChina

The physical problem of the thin film flow of a micropolar fluid over a dynamic and inclined substrate under the influence of gravitational and thermal forces in the presence of nanoparticles is *** different types of nanoparticle samples are accounted for in this current study,namely gold Au,silver Ag,molybdenum disulfide MoS_(2),aluminum oxide Al_(2)O_(3),and silicon dioxide SiO_(2).Blood,a micropolar fluid,serves as the common base *** exact closed-form solution for this problem is derived for the first time in the *** results are particularly validated against those for the Newtonian fluid and show excellent *** was found that increasing values of the spin boundary condition and micropolarity lead to a reduction in both the thermal and momentum boundary layers.A quantitative decay in the Nusselt number for a micropolar fluid,as compared to a Newtonian one for all the tested nanoparticles,is *** and silver nanoparticles(i)intensify in the flow parameter as the concentration of nanoparticles increases(ii)yield a higher thermal transfer rate,whereas molybdenum disulfide,aluminum oxide,and silicon dioxide exhibit a converse attitude for both Newtonian and micropolar *** reduction in film thickness for fluid comprising gold particles,as compared to the rest of the nanoparticles,is remarkable.

关键词： Thin film flow micropolar fluid nanoparticles molybdenum disulfide inclined substrate

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Experimental Study on Heat Storage Properties Comparison of Paraffin/Metal Foams Phase Change Material Composites

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Journal of Thermal Science 2024年第2期33卷 469-478页

作者： Waqar AHMED abid HUSSAIN Hanzla SHAHID Imran ALI Hafiz Muhammad ALI Department of Mechanical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Mechanical Engineering Institute of Space TechnologyIslamabadPakistan Department of Mechanical Mechatronics and Manufacturing EngineeringUniversity of Engineering and Technology LahoreFaisalabad CampusPunjabPakistan Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

Heat storage properties of phase change materials(PCMs) are essential characteristics that perform a key role in thermal heat energy storage *** thermal properties of PCMs can be improved by developing metal foam/PCM *** addition of metal foam in PCMs has a significant effect on the thermal characteristics of *** this paper,the heat storage properties of two different metal foam/PCM composites were experimentally *** behavior of paraffin in metal foam(copper and iron-nickel)/paraffin composites concerning pure paraffin at a constant heat flux of 1000 W/m^(2) in three directions simultaneously(x,y,and z) was *** was infiltrated into copper and iron-nickel foams to develop composite materials which resulted in enhancing the thermal conductivity of the paraffin.A comparative analysis is made on the heat storage properties of paraffin in copper and iron-nickel foams/paraffin *** temperature distribution during the phase transition process is experimentally *** comparison indicates that temperature uniformity in copper foam/paraffin composite is better than in iron-nickel foam/paraffin composite and pure paraffin at the same heat *** results show that at heat flux of 1000 W/m^(2),the heat storage time for copper foam/paraffin composite is 20.63% of that of iron-nickel foam/paraffin composite.

关键词： heat storage capacity paraffin/metal foam composite temperature uniformity heat storage rate phase transition process

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Computational Fluid Dynamics Approach for Predicting Pipeline Response to Various Blast Scenarios: A Numerical Modeling Study

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2747-2777页

作者： Farman Saifi Mohd Javaid abid Haleem S.M.Anas Department of Mechanical Engineering Jamia Millia Islamia(A Central University)New Delhi110025India Department of Civil Engineering Jamia Millia Islamia(A Central University)New Delhi110025India

Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infras-tructure systems and networks capable of withstanding blast *** centered on high-profile facilities such as embassies and petrochemical plants,this concern now extends to a wider array of infrastructures and *** and scholars increasingly prioritize structural safety against explosions,particularly to prevent disproportionate collapse and damage to nearby *** has further amplified the reliance on oil and gas pipelines,making them vital for urban life and prime targets for terrorist ***,there is a growing imperative for computational engineering solutions to tackle blast loading on pipelines and mitigate associated risks to avert *** this study,an empty pipe model was successfully validated under contact blast conditions using Abaqus software,a powerful tool in mechanical engineering for simulating blast effects on buried *** a Eulerian-Lagrangian computational fluid dynamics approach,the investigation extended to above-surface and below-surface blasts at standoff distances of 25 and 50 *** descriptions in the numerical model relied on Abaqus’default mechanical *** analysis revealed varying pipe performance,with deformation decreasing as explosion-to-pipe distance *** explosion’s location relative to the pipe surface notably influenced deformation levels,a key finding highlighted in the ***,quantitative findings indicated varying ratios of plastic dissipation energy(PDE)for different blast scenarios compared to the contact blast(P0).Specifically,P1(25 mm subsurface blast)and P2(50 mm subsurface blast)showed approximately 24.07%and 14.77%of P0’s PDE,respectively,while P3(25 mm above-surface blast)and P4(50 mm above-surface blast)exhibited lower PDE values,accounting for about 18.08%and 9.67%of P0’s PDE,***

关键词： Blast loading computational fluid dynamics computer modeling pipe networks response prediction structural safety

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A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

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Computers, Materials & Continua 2024年第5期79卷 3373-3395页

作者： Farhan Ullah Xuexia Zhang Mansoor Khan Muhammad abid Abdullah Mohamed School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China College of Intelligent Manufacturing and Control Engineering Qilu Institute of TechnologyJinan250200China College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China Research Centre Future University in EgyptNew Cairo11835Egypt

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance *** approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering *** approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

关键词： Ensemble learning machine learning real-time data analysis stakeholder analysis temporal convolutional network wind power forecasting

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Toward sustainable waste management in small islands developing states: integrated waste-to-energy solutions in Maldives context

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Frontiers of Environmental Science & Engineering 2024年第2期18卷 133-148页

作者： Yao Wang Alejandro Ruiz-Acevedo Eemaan Rameez Vijaya Raghavan abid Hussain Xunchang Fei School of Civil and Environmental Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore United Nations Office for Project Services(UNOPS) United Nations BuildingBuruzu MaguMale’20184Maldives Department of Bioresource Engineering McGill UniversitySte-Anne-De-BellevueQuebec H9X 3V9Canada Department of Civil and Environmental Engineering Carleton UniversityOttawaOntario K1S 5B6H9X 3V9Canada

Effective waste management is a major challenge for Small Island Developing States (SIDS) like Maldives due to limited land availability. Maldives exemplifies these issues as one of the most geographically dispersed countries, with a population unevenly distributed across numerous islands varying greatly in size and population density. This study provides an in-depth analysis of the unique waste management practices across different regions of Maldives in relation to its natural and socioeconomic context. Data shows Maldives has one of the highest population density and per capita waste generation among SIDS, despite its small land area and medium GDP per capita. Large disparities exist between the densely populated capital Male’ with only 5.8 km2 area generating 63% of waste and the ~194 scattered outer islands with ad hoc waste management practices. Given Male’s dense population and high calorific waste, incineration could generate up to ~30 GW/a energy and even increase Maldives’ renewable energy supply by 200%. In contrast, decentralized anaerobic digestion presents an optimal solution for outer islands to reduce waste volume while providing over 40%–100% energy supply for daily cooking in local families. This timely study delivers valuable insights into designing context-specific waste-to-energy systems and integrated waste policies tailored to Maldives’ distinct regions. The framework presented can also guide other SIDS facing similar challenges as Maldives in establishing sustainable, ecologically sound waste management strategies.

关键词： Anaerobic digestion Waste incineration Waste management Maldives Small Island Developing States Waste-to-energy

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Composite Fractional Trapezoidal Rule with Romberg Integration

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2729-2745页

作者： iqbal M.Batiha Rania Saadeh iqbal H.Jebril Ahmad Qazza Abeer A.Al-Nana Shaher Momani Department of Mathematics Al Zaytoonah University of JordanAmman11733Jordan Nonlinear Dynamics Research Center(NDRC) Ajman UniversityAjman 346United Arab Emirates Department of Mathematics Faculty of ScienceZarqa UniversityZarqa13110Jordan Department of Mathematics Prince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Mathematics The University of JordanAmman11942Jordan

The aim of this research is to demonstrate a novel scheme for approximating the Riemann-Liouville fractional integral *** would be achieved by first establishing a fractional-order version of the 2-point Trapezoidal rule and then by proposing another fractional-order version of the(n+1)-composite Trapezoidal *** particular,the so-called divided-difference formula is typically employed to derive the 2-point Trapezoidal rule,which has accordingly been used to derive a more accurate fractional-order formula called the(n+1)-composite Trapezoidal ***,in order to increase the accuracy of the proposed approximations by reducing the true errors,we incorporate the so-called Romberg integration,which is an extrapolation formula of the Trapezoidal rule for integration,into our proposed *** numerical examples are provided and compared with a modern definition of the Riemann-Liouville fractional integral operator to illustrate the efficacy of our scheme.

关键词： Composite fractional Trapezoidal rule Romberg integration

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Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

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Computers, Materials & Continua 2024年第3期78卷 3413-3429页

作者： Rabia abid Muhammad Rizwan Abdulatif Alabdulatif Abdullah Alnajim Meznah Alamro Mourade Azrour Department of Computer Science Kinnaird College for WomenLahorePakistan College of Science and Engineering University of DerbyDerbyDE221GBUK Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia STI Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsMeknesMorocco

Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and *** Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data *** this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare *** experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)*** experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.

关键词： Artificial intelligence data privacy federated machine learning healthcare system security

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