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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.MUHAMMAD M.SARFRAZ department of Humanities and Sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

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Energy-Efficient Resource Optimization for Massive MIMO Networks Considering Network Load

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computers, Materials & Continua 2022年第4期71卷 871-888页

作者： Samira Mujkic Suad Kasapovic Mohammed Abuibaid department of Telecommunications Faculty of Electrical EngineeringUniversity of TuzlaTuzla75000Bosnia herzegovina 2department of systems and computer engineering Faculty of Engineering and DesignCarleton UniversityOttawaK1S 5B6Canada

This paper investigates the resource optimization problem for a multi-cell massive multiple-input multiple-output(MIMO)network in which each base station(BS)is equipped with a large number of antennas and each base station(BS)adapts the number of antennas to the daily load profile(DLP).This paper takes into consideration user location distribution(ULD)variation and evaluates its impact on the energy efficiency of load adaptive massive MIMO *** variation is modeled by dividing the cell into two coverage areas with different user densities:boundary focused(BF)and center focused(CF)*** cells are assumed identical in terms of BS configurations,cell loading,and ULD variation and each BS is modeled as an M/G/m/m state dependent queue that can serve a maximum number of users at the peak *** with energy efficiency(EE)we analyzed deployment and spectrum efficiency in our adaptive massive MIMO system by evaluating the impact of cell size,available bandwidth,output power level of the BS,and maximum output power of the power amplifier(PA)at different cell *** also analyzed average energy consumption on an hourly basis per BS for the model proposed for data traffic in Europe and also the model proposed for business,residential,street,and highway areas.

关键词： Massive MIMO traffic load energy efficiency user location distribution optimization

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Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

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computer Modeling in engineering & Sciences 2025年第1期142卷 1-48页

作者： Hariharasakthisudhan Ponnarengan Sivakumar Rajendran Vikas Khalkar Gunapriya Devarajan Logesh Kamaraj department of Mechanical engineering Dr.Mahalingam College of Engineering and TechnologyPollachiCoimbatoreTamil Nadu642003India department of Mechanical engineering JKKN College of Engineering and TechnologyKumarapalayamNamakkalTamil Nadu637209India department of Mechanical engineering Gharda Institute of TechnologyLavelMaharashtra415708India department of Electrical and Electronics engineering Sri Eshwar College of EngineeringCoimbatoreTamilnadu641202India department of Mechanical engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical *** review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health *** findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and *** synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment ***,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease *** review emphasizes the need for interdisciplinary collaboration to further advance this *** research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and *** fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

关键词： Computational models biomedical engineering bioinformatics machine learning wearable technology

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Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

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Nano-Micro Letters 2025年第1期17卷 262-280页

作者： Dongxiao Li Hong Zhou Zhihao Ren Cheng Xu Chengkuo Lee department of Electrical and computer engineering National University of SingaporeSingapore 117583Singapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance ***,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning *** observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano *** characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 *** findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

关键词： Plasmonic nanoantennas Light-matter interaction Surface-enhanced infrared absorption Overcoupled Biosensing

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A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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computer Modeling in engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India computer engineering Ronin InstituteMontclairNJ 07043USA department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&department of computer Science and Information engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

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Personalized real-time pricing for efficient and fair demandresponse in energy cooperatives and highly competitive flexibility markets

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Journal of Modern Power systems and Clean Energy 2019年第1期7卷 151-162页

作者： Georgios TSAOUSOGLOU Nikolaos EFTHYMIOPOULOS Prodrommos MAKRIS Emmanouel VARVARIGOS department of Electrical and computer engineering Institute of Communication and Computer Systems National Technical University of Athens Electrical and computer systems engineering Monash University

This paper contributes to the well-known challenge of active user participation in demand side management(DSM).In DSM, there is a need for modern pricing mechanisms that will be able to effectively incentivize selfishly behaving users in modifying their energy consumption pattern towards system-level goals like energy *** generally desired properties of DSM algorithms are: user satisfaction, energy cost minimization and *** this paper, a personalized real-time pricing(P-RTP) mechanism design framework is proposed that fairly allocates the energy cost reduction only to the users that provoke ***, the proposed mechanism achieves significant reduction of the energy cost without sacrificing at all the welfare(user satisfaction)of electricity *** business model that the proposed mechanism envisages is highly competitive flexibility market environments as well as energy cooperatives.

关键词： Demand response Smart grid Electricity pricing Scheduling Demand side management Personalized real-time pricing Energy cooperative

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A pricing scheme for electric utility’s participation in day-ahead and real-time flexibility energy markets

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Journal of Modern Power systems and Clean Energy 2019年第5期7卷 1294-1306页

作者： Ioannis MAMOUNAKIS Nikolaos EFTHYMIOPOULOS Dimitrios J.VERGADOS Georgios TSAOUSOGLOU Prodromos MAKRIS Emmanouel Manos VARVARIGOS department of Electrical and computer engineering Institute of Communication and Computer SystemsNational Technical University of AthensAthensGreece department of computer engineering and Informatics University of PatrasRio-PatrasGreece department of Electrical and computer systems engineering Monash UniversityMelbourneAustralia

Liberalized electricity markets,smart grids and high penetration of renewable energy sources(RESs)led to the development of novel markets,whose objective is the harmonization between production and demand,usually noted as real time of flexibility *** necessitates the development of novel pricing schemes able to allow energy service providers(ESPs)to maximize their aggregated profits from the traditional markets(trading between wholesale/day-ahead and retail markets)and the innovative flexibility *** the same time,ESPs have to offer their end users(consumers)competitive(low cost)energy *** this context,novel pricing schemes must act,among others,as automated demand side management(DSM)techniques that are able to trigger the desired behavioral changes according to the flexibility market prices in energy consumption curves(ECCs)of the *** pricing schemes proposed so far,*** pricing,interact in an efficient way with wholesale *** they do not provide consumers with strong enough financial incentives to modify their energy consumption habits towards energy cost ***,they do not interact efficiently with flexibility ***,we develop a flexibility real-time pricing(FRTP)scheme,which offers a dynamically adjustable level of financial incentives to participating users by fairly rewarding the ones that make desirable behavioral changes in their *** evaluation results demonstrate that the proposed FRTP is able to offer a 15%–30%more attractive trade-off between the stacked profits of ESPs,*** sum of the profits from retail and flexibility markets,and the satisfaction of consumers.

关键词： Demand response Flexibility markets Realtime pricing(RTP) Behavioral change Energy efficiency

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Distribution Management systems for Smart Grid:Architecture,Work Flows,and Interoperability

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Journal of Modern Power systems and Clean Energy 2022年第2期10卷 300-308页

作者： Rabih A.Jabr Izudin Dzafic the department of Electrical and computer engineering American University of BeirutBeirut 11072020Lebanon the Faculty of Electrical engineering University of SarajevoSarajevo 71000Bosnia and Herzegovina

The smart grid integrates advanced sensors,a two-way communication infrastructure,and high-performance computation-based *** distribution management systems for smart grid include several functions for manipulating legacy voltage control devices and distributed energy resources through closed-loop volt/var control,leading to wide-area regulation of voltages in the presence of fluctuating *** other primary distribution network analysis application is concerned with automatic fault location and service restoration following fault events,aiming to provide the grid with autonomous intelligence for *** technologies are vital to enable the computing applications of distribution networks,whether they work in centralized or distributed *** paper presents the state of the art in distribution management system architectures and modern workflows showing data exchange,practical parallel implementations designed to handle large amounts of data,in addition to communication standards that serve as interoperability *** demystifies the relationship between different functions developed independently by power system researchers and shows their operation as a complete system,thus placing them in a better context for future research and development.

关键词： Cyber security data communication power distribution networks self-healing software architecture voltage control.

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Multi-Step Clustering of Smart Meters Time Series:Application to Demand Flexibility Characterization of SME Customers

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computer Modeling in engineering & Sciences 2025年第1期142卷 869-907页

作者： Santiago Bañales Raquel Dormido Natividad Duro department of computer Sciences and Automatic Control Universidad Nacional de Educación a Distancia(UNED)Madrid28040Spain Iberdrola Innovation Middle East Doha210177Qatar

Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy *** study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time *** meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns *** dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series *** intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire *** the first time,a step function approach is applied to reduce time series *** attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy *** addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined *** application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the *** research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditio

关键词： Electric load clustering load profiling smart meters machine learning data mining demand flexibility demand response

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Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

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computer Modeling in engineering & Sciences 2025年第1期142卷 531-553页

作者： Tmader Alballa Muhammad Ihsan Atiqe Ur Rahman Noorah Ayed Alsorayea Hamiden Abd El-Wahed Khalifa department of Mathematics College of SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia 2 department of Mathematics University of Management and TechnologyLahore54000Pakistan department of Mathematics College of ScienceQassim UniversityBuraydah51452Saudi Arabia

The dramatic rise in the number of people living in cities has made many environmental and social problems *** search for a productive method for disposing of solid waste is the most notable of these *** scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated *** goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site *** characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these *** tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s *** this,an intelligent algorithm is *** steps of the suggested algorithm are explained with an example that explains *** compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their *** study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,*** uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior *** is simpler for the decisionmakers to look at each option separately because the decision is *** the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

关键词： Hypersoft expert set Sanchez’s method decision making optimization solid waste management possibility grade fuzzy parameterization

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