Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford...Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.展开更多
As organic thin film transistors(OTFTs)are set to play a crucial role in flexible and cost-effective electronic applica-tions,this paper investigates a high-mobility 6,13-bis(triisopropylsilylethynyl)pentacene(TIPS-pe...As organic thin film transistors(OTFTs)are set to play a crucial role in flexible and cost-effective electronic applica-tions,this paper investigates a high-mobility 6,13-bis(triisopropylsilylethynyl)pentacene(TIPS-pentacene)OTFT for use in flexi-ble electronics.The development of such high-mobility devices necessitates precise device modeling to support technology opti-misation and circuit design.The details of numerical simulation technique is discussed,in which,the electrical behavior of the device is well captured by fine tuning basic semiconductor equations.This technology computer-aided design(TCAD)has been validated with exprimental data.In addition,we have discussed about compact model fitting of the devices as well as parameter extraction procedure employed.This includes verification of Silvaco ATLAS finite element method(FEM)based results against experimental data gained from fabricated OTFT devices.Simulations for p-type TFT-based inverter are also per-formed to assess the performance of compact model in simple circuit simulation.展开更多
Digital content such as games,extended reality(XR),and movies has been widely and easily distributed over wireless networks.As a result,unauthorized access,copyright infringement by third parties or eavesdroppers,and ...Digital content such as games,extended reality(XR),and movies has been widely and easily distributed over wireless networks.As a result,unauthorized access,copyright infringement by third parties or eavesdroppers,and cyberattacks over these networks have become pressing concerns.Therefore,protecting copyrighted content and preventing illegal distribution in wireless communications has garnered significant attention.The Intelligent Reflecting Surface(IRS)is regarded as a promising technology for future wireless and mobile networks due to its ability to reconfigure the radio propagation environment.This study investigates the security performance of an uplink Non-Orthogonal Multiple Access(NOMA)system integrated with an IRS and employing Fountain Codes(FCs).Specifically,two users send signals to the base station at separate distances.A relay receives the signal from the nearby user first and then relays it to the base station.The IRS receives the signal from the distant user and reflects it to the relay,which then sends the reflected signal to the base station.Furthermore,a malevolent eavesdropper intercepts both user and relay communications.We construct mathematical equations for Outage Probability(OP),throughput,diversity evaluation,and Interception Probability(IP),offering quantitative insights to assess system security and performance.Additionally,OP and IP are analyzed using a Deep Neural Network(DNN)model.A deeper comprehension of the security performance of the IRS-assisted NOMA systemin signal transmission is provided by Monte Carlo simulations,which are also carried out to confirm the theoretical conclusions.展开更多
The Tourism Industry plays a critical role in economic growth on the international scene but is equally responsible for contributing to greenhouse gas emissions and energy demand.The research analyzed the global trend...The Tourism Industry plays a critical role in economic growth on the international scene but is equally responsible for contributing to greenhouse gas emissions and energy demand.The research analyzed the global trends of energy consumption(EC)within this industry concerning environmental performance,limits,and prospects of sustained expan-sion.It includes 300 tourism-related businesses across different global economic regions.Key tourism factors include EC,greenhouse gas emissions,renewable energy(RE)use,tourism’s Gross Domestic Product(GDP)contribution,and energy efficiency.Statistical methods such as regression and panel data analysis assess the impact of tourism GDP,carbon emissions and RE.The regression analysis,including linear regression and panel data regression,to assess the influence of factors such as tourism GDP,carbon emissions,RE share,and energy efficiency improvements,providing a data-driven approach to understanding EC in tourism.The findings reveal regional differences,with developed regions consuming more energy per capita,while developing markets show progress in energy-efficient practices.The findings of the linear regression analysis show tourism GDP contribution(β=4,200).The outcomes of the panel data regression analysis show the t-statistic values of carbon emissions(t=5.64).The Difference-in-Differences analysis indicates that tourist GDP is greater in developed regions(β=4,100)compared to developing regions(β=3,500).Carbon emissions(β=4,800)are greater,although RE(β=4,200)and energy efficiency(β=2,500)increase more in developing nations.The research emphasizes expanding use of RE in tourism infrastructure,especially in ecotourism and green hotels.展开更多
In this study,ten wind turbines and fourteen solar photovoltaic(SPV)modules were employed to compare the potential of hydrogen production from wind and solar energy resources in the six geopolitical zones of Nigeria.T...In this study,ten wind turbines and fourteen solar photovoltaic(SPV)modules were employed to compare the potential of hydrogen production from wind and solar energy resources in the six geopolitical zones of Nigeria.The amount of hydrogen produced was considered as a technical parameter,cost of hydrogen production was considered as an economic index,and the amount of carbon(IV)oxide saved from the use of diesel fuel was considered as an environmental index.The results reveal that ENERCON E-40 turbine yields the highest capacity factor in Lagos,Jos,Sokoto,Bauchi and Enugu sites while FUHRLAENDER,GMBH yields the highest capacity factor in Delta.The mean annual hydrogen production from wind ranged from 2.05 tons/annum at site S6(Delta)to 17.33 tons/annum at site S3(Sokoto),and the mean annual hydrogen production from SPV ranged from 64.33 tons/annum at sites S1(Lagos)to 140.28 tons/annum at site S6(Delta).The cost of hydrogen production from wind was 6.3679 and 25.9007$/kg for sites S3 and S6,respectively,and the cost of hydrogen production from SPV was 5.6659 and 6.1206$/kg for sites S3 and S1,respectively.The amount of CO_(2) saved annually from wind-based hydrogen generation was 137,267 kg/year in site S6 and 504,180 kg/year in site S3,and was used to produce electricity via fuel cells.The amount of CO_(2) saved using hydrogen produced from SPV was 615,400 kg/year and 1,341,899 kg/year in sites S1 and S6,respectively.The results also revealed that 75.55%,88.93%,80.28%,80.54%,85.65%,98.53%more hydrogen could be produced from SPV for sites S1–S6,respectively,compared to the wind resources.This study serves as a source of reliable technical information to relevant government agencies,policy makers and investors in making informed decisions on optimal investment in the hydrogen economy of Nigeria.展开更多
Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quali...Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.展开更多
The Dhofar region of Oman,renowned for its unique monsoon-influenced climate and substantial agricultural potential,faces significant challenges in achieving sustainable agricultural practices that balance productivit...The Dhofar region of Oman,renowned for its unique monsoon-influenced climate and substantial agricultural potential,faces significant challenges in achieving sustainable agricultural practices that balance productivity with environmental conservation.This review critically explores a range of sustainable agricultural methods currently im-plemented in the region,including organic farming,water conservation techniques such as drip irrigation and rainwater harvesting,agroforestry systems,crop rotation,and soil conservation measures like terracing and composting.These strategies aim to mitigate pressing environmental concerns such as water scarcity,soil erosion,and land degradation while enhancing crop yield and farm profitability.The review further examines the economic implications of these practices, evaluating their cost-effectiveness, potential for long-term returns, and influence on the growing market demandfor organic and eco-friendly products. Despite their benefits, the broader adoption of these sustainable approaches ishindered by several challenges, including limited access to advanced technologies, inadequate financial resources, lackof technical knowledge, and minimal awareness among local farmers. The article also assesses the role of governmentalpolicies, subsidies, and extension services in promoting the adoption of sustainable agriculture in Dhofar. Finally, it offersstrategic recommendations for future research, policy development, and capacity-building initiatives. This reviewemphasizes the urgent need for continued investment in sustainable solutions to ensure long-term agricultural resilienceand environmental sustainability in the region.展开更多
The results of mass appraisal in many countries are used as a basis for calculating the amount of real estate tax,therefore,regardless of the methods used to calculate it,the resulting value should be as close as poss...The results of mass appraisal in many countries are used as a basis for calculating the amount of real estate tax,therefore,regardless of the methods used to calculate it,the resulting value should be as close as possible to the market value of the real estate to maintain a balance of interests between the state and the rights holders.In practice,this condition is not always met,since,firstly,the quality of market data is often very low,and secondly,some markets are characterized by low activity,which is expressed in a deficit of information on asking prices.The aim of the work is ecological valuation of land use:how regression-based mass appraisal can inform ecological conservation,land degradation,and sustainable land management.Four multiple regression models were constructed for AI generated map of land plots for recreational use in St.Petersburg(Russia)with different volumes of market information(32,30,20 and 15 units of market information with four price-forming factors).During the analysis of the quality of the models,it was revealed that the best result is shown by the model built on the maximum sample size,then the model based on 15 analogs,which proves that a larger number of analog objects does not always allow us to achieve better results,since the more analog objects there are.展开更多
Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effecti...Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effective energy storage systems.Ad-vances in materials science have led to the develop-ment of hybrid nanomaterials,such as combining fil-amentous carbon forms with inorganic nanoparticles,to create new charge and energy transfer processes.Notable materials for electrochemical energy-stor-age applications include MXenes,2D transition met-al carbides,and nitrides,carbon black,carbon aerogels,activated carbon,carbon nanotubes,conducting polymers,carbon fibers,and nanofibers,and graphene,because of their thermal,electrical,and mechanical properties.Carbon materials mixed with conducting polymers,ceramics,metal oxides,transition metal oxides,metal hydroxides,transition metal sulfides,trans-ition metal dichalcogenide,metal sulfides,carbides,nitrides,and biomass materials have received widespread attention due to their remarkable performance,eco-friendliness,cost-effectiveness,and renewability.This article explores the development of carbon-based hybrid materials for future supercapacitors,including electric double-layer capacitors,pseudocapacitors,and hy-brid supercapacitors.It investigates the difficulties that influence structural design,manufacturing(electrospinning,hydro-thermal/solvothermal,template-assisted synthesis,electrodeposition,electrospray,3D printing)techniques and the latest car-bon-based hybrid materials research offer practical solutions for producing high-performance,next-generation supercapacitors.展开更多
In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lie...In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lies inintegrating global and local search methodologies to update the algorithm population within the problem-solvingspace based on moving each member to the farthest and nearest member to itself.The paper delineates the theoryof FNO,presenting a mathematical model in two phases:(i)exploration based on the simulation of the movementof a population member towards the farthest member from itself and(ii)exploitation based on simulating themovement of a population member towards the nearest member from itself.FNO’s efficacy in tackling optimizationchallenges is assessed through its handling of the CEC 2017 test suite across problem dimensions of 10,30,50,and 100,as well as to address CEC 2020.The optimization results underscore FNO’s adeptness in exploration,exploitation,and maintaining a balance between them throughout the search process to yield viable solutions.Comparative analysis against twelve established metaheuristic algorithms reveals FNO’s superior performance.Simulation findings indicate FNO’s outperformance of competitor algorithms,securing the top rank as the mosteffective optimizer across a majority of benchmark functions.Moreover,the outcomes derived by employing FNOon twenty-two constrained optimization challenges from the CEC 2011 test suite,alongside four engineering designdilemmas,showcase the effectiveness of the suggested method in tackling real-world scenarios.展开更多
In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals i...In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals in Density Functional Theory (DFT) with the CASTEP code. The optimized lattice parameters are quite similar for all the functionals. The electronic properties have shown that RbSrBr3 perovskite is a wide direct band gap compound with a band gap energy ranging from 4.296 eV to 4.494 eV for all the functionals. The mechanical parameters like elastic constants, Young’s modulus, Shear modulus, Poisson’s ratio, Pugh’s ratio, and an anisotropic factor reveal that the RbSrBr3 perovskite has ductile behavior and an anisotropic nature which signifies the mechanical stability of the compound. The Debye temperature might withstand lattice vibration heat. High absorption coefficient (>104 cm−1), high optical conductivity, and very low reflectivity have been found in the RbSrBr3 perovskite for all functions. The computed findings on the RbSrBr3 perovskite suggested that the presented studied material is potentially applicable for photodetector and optoelectronic devices.展开更多
In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transfo...In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.展开更多
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 r...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 research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major 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 diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.展开更多
Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce o...Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce operating costs. The battery storage system has to be monitored and managed to prevent serious problems such as battery overcharging, over-discharging, overheating, battery unbalancing, thermal runaway, and fire dangers. For voltage balancing between batteries in the pack throughout the charging period and the SOC estimate, a modified lossless switching mechanism is used in this research’s suggested battery management system. The OCV state of charge calculation, in the beginning, was used in conjunction with the coulomb counting approach to estimate the SOC. The results reveal that correlation factor K has an average value of 0.3 volts when VM ≥ 12 V and an average value of 0.825 when VM ≤ 12 V. The battery monitoring system revealed that voltage balancing was accomplished during the charging process in park one after 80 seconds with a SOC difference of 1.4% between Batteries 1 and 2. On the other hand, the system estimates the state of charge during the discharging process in two packs, with a maximum DOD of 10.8 V for all batteries. The project’s objectives were met since the BMS estimated SOC and achieved voltage balance.展开更多
Heating,ventilation,and air conditioning(HVAC)systems contribute substantially to global energy consumption,while rejecting significant amounts of low-grade heat into the environment.This paper presents a nonintrusive...Heating,ventilation,and air conditioning(HVAC)systems contribute substantially to global energy consumption,while rejecting significant amounts of low-grade heat into the environment.This paper presents a nonintrusive spiral-coil heat exchanger designed to recover waste heat from the outdoor condenser of a split-type air conditioner.The system operates externally without altering the existing HVAC configuration,thereby rendering it suitable for retrofitting.Water was circulated as the working fluid at flow rates of 0.028–0.052 kg/s to assess thermal performance.Performance indicators,including the outlet water temperature,heat transfer rate,convective coefficient,and efficiency,were systematically evaluated.The system achieved a maximum outlet water temperature of 67℃and a peak thermal efficiency of 91.07%at the highest flow rate.The uncertainty analysis confirmed reliable measurements within±3.45%.The monthly energy savings were estimated at 178.35 kWh,accompanied by a reduction in CO_(2)emissions of up to 187.26 kg,yielding a short payback period of 1.06 years.These results demonstrate the feasibility of spiral-coil heat exchangers as cost-effective and eco-friendly alternatives to conventional electric water heaters.The proposed approach not only enhances the overall energy utilization but also contributes to energy conservation and climate mitigation objectives.展开更多
Unmanned aerial vehicles(UAVs)technology is rapidly advancing,offering innovative solutions for various industries,including the critical task of oil and gas pipeline surveillance.However,the limited flight time of co...Unmanned aerial vehicles(UAVs)technology is rapidly advancing,offering innovative solutions for various industries,including the critical task of oil and gas pipeline surveillance.However,the limited flight time of conventional UAVs presents a significant challenge to comprehensive and continuous monitoring,which is crucial for maintaining the integrity of pipeline infrastructure.This review paper evaluates methods for extending UAV flight endurance,focusing on their potential application in pipeline inspection.Through an extensive literature review,this study identifies the latest advancements in UAV technology,evaluates their effectiveness,and highlights the existing gaps in achieving prolonged flight operations.Advanced techniques,including artificial intelligence(AI),machine learning(ML),and deep learning(DL),are reviewed for their roles in pipeline monitoring.Notably,DL algorithms like You Only Look Once(YOLO)are explored for autonomous flight in UAV-based inspections,real-time defect detection,such as cracks,corrosion,and leaks,enhancing reliability and accuracy.A vital aspect of this research is the proposed deployment of a hybrid drone design combining lighter-than-air(LTA)and heavier-than-air(HTA)principles,achieving a balance of endurance and maneuverability.LTA vehicles utilize buoyancy to reduce energy consumption,thereby extending flight durations.The paper details the methodology for designing LTA vehicles,presenting an analysis of design parameters that align with the requirements for effective pipeline surveillance.The ongoing work is currently at Technology Readiness Level(TRL)4,where key components have been validated in laboratory conditions,with fabrication and flight testing planned for the next phase.Initial design analysis indicates that LTA configurations could offer significant advantages in flight endurance compared to traditional UAV designs.These findings lay the groundwork for future fabrication and testing phases,which will be critical in validating and assessing the proposed approach’s real-world applicability.By outlining the technical complexities and proposing specialized techniques tailored for pipeline monitoring,this paper provides a foundational framework for advancing UAV capabilities in the oil and gas sector.Researchers and industry practitioners can use this roadmap to further develop UAV-enabled surveillance solutions,aiming to improve the reliability,efficiency,and safety of pipeline monitoring.展开更多
The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the c...The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the current 5G networks have not achieved the promised 5G goals, including the projected 2000 times EE improvement over the legacy 4G Long Term Evolution (LTE) networks. This paper provides a comprehensive survey of Artificial Intelligence (AI)-enabled MA techniques, emphasizing their roles in Spectrum Sensing (SS), Dynamic Resource Allocation (DRA), user scheduling, interference mitigation, and protocol adaptation. In particular, we systematically analyze the progression of traditional and modern MA schemes, from Orthogonal Multiple Access (OMA)-based approaches like Time Division Multiple Access (TDMA) and Frequency Division Multiple Access (FDMA) to advanced Non-Orthogonal Multiple Access (NOMA) methods, including power domain-NOMA, Sparse Code Multiple Access (SCMA), and Rate Splitting Multiple Access (RSMA). The study further categorizes AI techniques—such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Federated Learning (FL), and Explainable AI (XAI)—and maps them to practical challenges in Dynamic Spectrum Management (DSM), protocol optimization, and real-time distributed decision-making. Optimization strategies, including metaheuristics and multi-agent learning frameworks, are reviewed to illustrate the potential of AI in enhancing energy efficiency, system responsiveness, and cross-layer RA. Additionally, the review addresses security, privacy, and trust concerns, highlighting solutions like privacy-preserving ML, FL, and XAI in 6G and beyond. By identifying research gaps, challenges, and future directions, this work offers a structured resource for researchers and practitioners aiming to integrate AI into 6G MA systems for intelligent, scalable, and secure wireless communications.展开更多
The ascent of the metaverse signfies a profound transformation in our digital landscape,ushering in a complex network of interlinked virtual domains and digital spaces.In this burgeoning metaverse,a paradigm shift is ...The ascent of the metaverse signfies a profound transformation in our digital landscape,ushering in a complex network of interlinked virtual domains and digital spaces.In this burgeoning metaverse,a paradigm shift is seen in how people engage,collaborate,and become immersed in digital environments.An especially intriguing concept taking root within this metaverse landscape is that of digital twins.Initially rooted in industrial and Internet of Things(IoT)contexts,digital twins are now making their mark in the metaverse,presenting opportunities to elevate user experiences,introduce novel dimensions of interaction,and seamlessly bridge the divide between the virtual and physical realms.Digital twins,conceived initially to replicate physical entities in real-time,have transcended their industrial origins in this new metaverse context.They no longer solely replicate physical objects but extend their domain to encompass digital entities,avatars,virtual environments,and users.Despite the vital contributions of digital twins in the metaverse,there has been no research that has explored the applications and scope of digital twins in the metaverse comprehensively.However,there are a few papers focusing on some particular applications.Addressing this research gap,we present an in-depth review of the pivotal role of application digital twins in the metaverse.We present 15 digital twin applications in the metaverse,ranging from simulation and training to emergency preparedness.This study outlines the critical limitations of integrating digital twins and metaverse and several future research directions.展开更多
The Discrete Walsh Hadamard Transform(DWHT)has emerged as an efficient alternative to the Discrete Fourier Transform(DFT)for Orthogonal Frequency Division Multiplexing(OFDM)implementations,particularly in handling cha...The Discrete Walsh Hadamard Transform(DWHT)has emerged as an efficient alternative to the Discrete Fourier Transform(DFT)for Orthogonal Frequency Division Multiplexing(OFDM)implementations,particularly in handling channel impairments.In this article,we proposed an efficient Joint Low Complexity Regularized Zero Forcing-Wavelet Domain Equalizer(JLCRLZF-WDE)to replace the traditional Frequency Domain Equalizer(FDE)in DWHT-OFDM systems.Unlike FDE,which requires additional DFT and Inverse DFT(IDFT)computations,the proposed JLCRLZF-WDE directly operates in the Walsh domain,effectively mitigating the computational overhead.The derivation of the proposed JLCRLZF-WDE equations take the effect of the channel,Co-Carrier Frequency Offset(Co-CFO),as well as the noise into account.During the derivation of the system model equations,we assume a MultipleInput-Multiple-Output(MIMO)-OFDM communication system through a Rayleigh fading channel.The Bit Error Rate(BER)performance and computational complexity of the proposed and the conventional algorithms are compared,indicating the significance of the proposed algorithm.Simulation results confirm the superiority of the proposed equalizer,demonstrating a 23.68%±28.4%reduction in computational complexity compared to Minimum Mean Square Error(LMMSE)-FDE based on DFT,while maintaining comparable BER performance at various MIMO configuration.Furthermore,at a BER of 10^(-4),the JLCRLZF-WDE achieves performance parity with conventional Walsh domain LMMSE equalizers,whereas other equalizers require an additional Signal-to-Noise Ratio(SNR)of 3.06 d B to achieve the same performance.展开更多
The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on e...The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on electric vehicles,the infrastructure of charging points,production of electric vehicles,and network modelling,this paper provides a comprehensive overview of electric vehicles,and hybrid vehicles,including an analysis of their market growth,as well as different types of optimization used in the current scenario.In developing countries like India,the biggest barrier is their unfulfilled facility over the charging.Without renewable energy sources,vehicle-to-grid technology facilitates the enhancement of additional power requirements.The mobility factor has been considered an important and special characteristic of electric vehicles.展开更多
基金supported in part by the Universitat Politècnica de València under grant PAID-10-21supported through AMRITA Seed Grant(Proposal ID:ASG2022188)。
文摘Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.
基金The DST government of India is appreciated by the researchers for giving them the early career research grant under the project ECR/2017/000179。
文摘As organic thin film transistors(OTFTs)are set to play a crucial role in flexible and cost-effective electronic applica-tions,this paper investigates a high-mobility 6,13-bis(triisopropylsilylethynyl)pentacene(TIPS-pentacene)OTFT for use in flexi-ble electronics.The development of such high-mobility devices necessitates precise device modeling to support technology opti-misation and circuit design.The details of numerical simulation technique is discussed,in which,the electrical behavior of the device is well captured by fine tuning basic semiconductor equations.This technology computer-aided design(TCAD)has been validated with exprimental data.In addition,we have discussed about compact model fitting of the devices as well as parameter extraction procedure employed.This includes verification of Silvaco ATLAS finite element method(FEM)based results against experimental data gained from fabricated OTFT devices.Simulations for p-type TFT-based inverter are also per-formed to assess the performance of compact model in simple circuit simulation.
基金supported in part by Vietnam National Foundation for Science and Technology Development(NAFOSTED)under Grant 102.04-2021.57in part by Culture,Sports and Tourism R&D Program through the Korea Creative Content Agency grant funded by the Ministry of Culture,Sports and Tourism in 2024(Project Name:Global Talent Training Program for Copyright Management Technology in Game Contents,Project Number:RS-2024-00396709,Contribution Rate:100%).
文摘Digital content such as games,extended reality(XR),and movies has been widely and easily distributed over wireless networks.As a result,unauthorized access,copyright infringement by third parties or eavesdroppers,and cyberattacks over these networks have become pressing concerns.Therefore,protecting copyrighted content and preventing illegal distribution in wireless communications has garnered significant attention.The Intelligent Reflecting Surface(IRS)is regarded as a promising technology for future wireless and mobile networks due to its ability to reconfigure the radio propagation environment.This study investigates the security performance of an uplink Non-Orthogonal Multiple Access(NOMA)system integrated with an IRS and employing Fountain Codes(FCs).Specifically,two users send signals to the base station at separate distances.A relay receives the signal from the nearby user first and then relays it to the base station.The IRS receives the signal from the distant user and reflects it to the relay,which then sends the reflected signal to the base station.Furthermore,a malevolent eavesdropper intercepts both user and relay communications.We construct mathematical equations for Outage Probability(OP),throughput,diversity evaluation,and Interception Probability(IP),offering quantitative insights to assess system security and performance.Additionally,OP and IP are analyzed using a Deep Neural Network(DNN)model.A deeper comprehension of the security performance of the IRS-assisted NOMA systemin signal transmission is provided by Monte Carlo simulations,which are also carried out to confirm the theoretical conclusions.
文摘The Tourism Industry plays a critical role in economic growth on the international scene but is equally responsible for contributing to greenhouse gas emissions and energy demand.The research analyzed the global trends of energy consumption(EC)within this industry concerning environmental performance,limits,and prospects of sustained expan-sion.It includes 300 tourism-related businesses across different global economic regions.Key tourism factors include EC,greenhouse gas emissions,renewable energy(RE)use,tourism’s Gross Domestic Product(GDP)contribution,and energy efficiency.Statistical methods such as regression and panel data analysis assess the impact of tourism GDP,carbon emissions and RE.The regression analysis,including linear regression and panel data regression,to assess the influence of factors such as tourism GDP,carbon emissions,RE share,and energy efficiency improvements,providing a data-driven approach to understanding EC in tourism.The findings reveal regional differences,with developed regions consuming more energy per capita,while developing markets show progress in energy-efficient practices.The findings of the linear regression analysis show tourism GDP contribution(β=4,200).The outcomes of the panel data regression analysis show the t-statistic values of carbon emissions(t=5.64).The Difference-in-Differences analysis indicates that tourist GDP is greater in developed regions(β=4,100)compared to developing regions(β=3,500).Carbon emissions(β=4,800)are greater,although RE(β=4,200)and energy efficiency(β=2,500)increase more in developing nations.The research emphasizes expanding use of RE in tourism infrastructure,especially in ecotourism and green hotels.
基金supported by Abiola Ajimobi Technical UniversityUniversity of Ibadan
文摘In this study,ten wind turbines and fourteen solar photovoltaic(SPV)modules were employed to compare the potential of hydrogen production from wind and solar energy resources in the six geopolitical zones of Nigeria.The amount of hydrogen produced was considered as a technical parameter,cost of hydrogen production was considered as an economic index,and the amount of carbon(IV)oxide saved from the use of diesel fuel was considered as an environmental index.The results reveal that ENERCON E-40 turbine yields the highest capacity factor in Lagos,Jos,Sokoto,Bauchi and Enugu sites while FUHRLAENDER,GMBH yields the highest capacity factor in Delta.The mean annual hydrogen production from wind ranged from 2.05 tons/annum at site S6(Delta)to 17.33 tons/annum at site S3(Sokoto),and the mean annual hydrogen production from SPV ranged from 64.33 tons/annum at sites S1(Lagos)to 140.28 tons/annum at site S6(Delta).The cost of hydrogen production from wind was 6.3679 and 25.9007$/kg for sites S3 and S6,respectively,and the cost of hydrogen production from SPV was 5.6659 and 6.1206$/kg for sites S3 and S1,respectively.The amount of CO_(2) saved annually from wind-based hydrogen generation was 137,267 kg/year in site S6 and 504,180 kg/year in site S3,and was used to produce electricity via fuel cells.The amount of CO_(2) saved using hydrogen produced from SPV was 615,400 kg/year and 1,341,899 kg/year in sites S1 and S6,respectively.The results also revealed that 75.55%,88.93%,80.28%,80.54%,85.65%,98.53%more hydrogen could be produced from SPV for sites S1–S6,respectively,compared to the wind resources.This study serves as a source of reliable technical information to relevant government agencies,policy makers and investors in making informed decisions on optimal investment in the hydrogen economy of Nigeria.
文摘Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.
文摘The Dhofar region of Oman,renowned for its unique monsoon-influenced climate and substantial agricultural potential,faces significant challenges in achieving sustainable agricultural practices that balance productivity with environmental conservation.This review critically explores a range of sustainable agricultural methods currently im-plemented in the region,including organic farming,water conservation techniques such as drip irrigation and rainwater harvesting,agroforestry systems,crop rotation,and soil conservation measures like terracing and composting.These strategies aim to mitigate pressing environmental concerns such as water scarcity,soil erosion,and land degradation while enhancing crop yield and farm profitability.The review further examines the economic implications of these practices, evaluating their cost-effectiveness, potential for long-term returns, and influence on the growing market demandfor organic and eco-friendly products. Despite their benefits, the broader adoption of these sustainable approaches ishindered by several challenges, including limited access to advanced technologies, inadequate financial resources, lackof technical knowledge, and minimal awareness among local farmers. The article also assesses the role of governmentalpolicies, subsidies, and extension services in promoting the adoption of sustainable agriculture in Dhofar. Finally, it offersstrategic recommendations for future research, policy development, and capacity-building initiatives. This reviewemphasizes the urgent need for continued investment in sustainable solutions to ensure long-term agricultural resilienceand environmental sustainability in the region.
基金financed as part of the project“Development of a methodology for instrumental base formation for analysis and modeling of the spatial socio-economic development of systems based on internal reserves in the context of digitalization”(FSEG-2023-0008)funded by the Russian Science Foundation(Agreement 23-41-10001,https://doi.org/https://rscf.ru/project/23-41-10001/).
文摘The results of mass appraisal in many countries are used as a basis for calculating the amount of real estate tax,therefore,regardless of the methods used to calculate it,the resulting value should be as close as possible to the market value of the real estate to maintain a balance of interests between the state and the rights holders.In practice,this condition is not always met,since,firstly,the quality of market data is often very low,and secondly,some markets are characterized by low activity,which is expressed in a deficit of information on asking prices.The aim of the work is ecological valuation of land use:how regression-based mass appraisal can inform ecological conservation,land degradation,and sustainable land management.Four multiple regression models were constructed for AI generated map of land plots for recreational use in St.Petersburg(Russia)with different volumes of market information(32,30,20 and 15 units of market information with four price-forming factors).During the analysis of the quality of the models,it was revealed that the best result is shown by the model built on the maximum sample size,then the model based on 15 analogs,which proves that a larger number of analog objects does not always allow us to achieve better results,since the more analog objects there are.
文摘Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effective energy storage systems.Ad-vances in materials science have led to the develop-ment of hybrid nanomaterials,such as combining fil-amentous carbon forms with inorganic nanoparticles,to create new charge and energy transfer processes.Notable materials for electrochemical energy-stor-age applications include MXenes,2D transition met-al carbides,and nitrides,carbon black,carbon aerogels,activated carbon,carbon nanotubes,conducting polymers,carbon fibers,and nanofibers,and graphene,because of their thermal,electrical,and mechanical properties.Carbon materials mixed with conducting polymers,ceramics,metal oxides,transition metal oxides,metal hydroxides,transition metal sulfides,trans-ition metal dichalcogenide,metal sulfides,carbides,nitrides,and biomass materials have received widespread attention due to their remarkable performance,eco-friendliness,cost-effectiveness,and renewability.This article explores the development of carbon-based hybrid materials for future supercapacitors,including electric double-layer capacitors,pseudocapacitors,and hy-brid supercapacitors.It investigates the difficulties that influence structural design,manufacturing(electrospinning,hydro-thermal/solvothermal,template-assisted synthesis,electrodeposition,electrospray,3D printing)techniques and the latest car-bon-based hybrid materials research offer practical solutions for producing high-performance,next-generation supercapacitors.
文摘In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lies inintegrating global and local search methodologies to update the algorithm population within the problem-solvingspace based on moving each member to the farthest and nearest member to itself.The paper delineates the theoryof FNO,presenting a mathematical model in two phases:(i)exploration based on the simulation of the movementof a population member towards the farthest member from itself and(ii)exploitation based on simulating themovement of a population member towards the nearest member from itself.FNO’s efficacy in tackling optimizationchallenges is assessed through its handling of the CEC 2017 test suite across problem dimensions of 10,30,50,and 100,as well as to address CEC 2020.The optimization results underscore FNO’s adeptness in exploration,exploitation,and maintaining a balance between them throughout the search process to yield viable solutions.Comparative analysis against twelve established metaheuristic algorithms reveals FNO’s superior performance.Simulation findings indicate FNO’s outperformance of competitor algorithms,securing the top rank as the mosteffective optimizer across a majority of benchmark functions.Moreover,the outcomes derived by employing FNOon twenty-two constrained optimization challenges from the CEC 2011 test suite,alongside four engineering designdilemmas,showcase the effectiveness of the suggested method in tackling real-world scenarios.
文摘In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals in Density Functional Theory (DFT) with the CASTEP code. The optimized lattice parameters are quite similar for all the functionals. The electronic properties have shown that RbSrBr3 perovskite is a wide direct band gap compound with a band gap energy ranging from 4.296 eV to 4.494 eV for all the functionals. The mechanical parameters like elastic constants, Young’s modulus, Shear modulus, Poisson’s ratio, Pugh’s ratio, and an anisotropic factor reveal that the RbSrBr3 perovskite has ductile behavior and an anisotropic nature which signifies the mechanical stability of the compound. The Debye temperature might withstand lattice vibration heat. High absorption coefficient (>104 cm−1), high optical conductivity, and very low reflectivity have been found in the RbSrBr3 perovskite for all functions. The computed findings on the RbSrBr3 perovskite suggested that the presented studied material is potentially applicable for photodetector and optoelectronic devices.
文摘In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.
文摘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 research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major 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 diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.
文摘Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce operating costs. The battery storage system has to be monitored and managed to prevent serious problems such as battery overcharging, over-discharging, overheating, battery unbalancing, thermal runaway, and fire dangers. For voltage balancing between batteries in the pack throughout the charging period and the SOC estimate, a modified lossless switching mechanism is used in this research’s suggested battery management system. The OCV state of charge calculation, in the beginning, was used in conjunction with the coulomb counting approach to estimate the SOC. The results reveal that correlation factor K has an average value of 0.3 volts when VM ≥ 12 V and an average value of 0.825 when VM ≤ 12 V. The battery monitoring system revealed that voltage balancing was accomplished during the charging process in park one after 80 seconds with a SOC difference of 1.4% between Batteries 1 and 2. On the other hand, the system estimates the state of charge during the discharging process in two packs, with a maximum DOD of 10.8 V for all batteries. The project’s objectives were met since the BMS estimated SOC and achieved voltage balance.
文摘Heating,ventilation,and air conditioning(HVAC)systems contribute substantially to global energy consumption,while rejecting significant amounts of low-grade heat into the environment.This paper presents a nonintrusive spiral-coil heat exchanger designed to recover waste heat from the outdoor condenser of a split-type air conditioner.The system operates externally without altering the existing HVAC configuration,thereby rendering it suitable for retrofitting.Water was circulated as the working fluid at flow rates of 0.028–0.052 kg/s to assess thermal performance.Performance indicators,including the outlet water temperature,heat transfer rate,convective coefficient,and efficiency,were systematically evaluated.The system achieved a maximum outlet water temperature of 67℃and a peak thermal efficiency of 91.07%at the highest flow rate.The uncertainty analysis confirmed reliable measurements within±3.45%.The monthly energy savings were estimated at 178.35 kWh,accompanied by a reduction in CO_(2)emissions of up to 187.26 kg,yielding a short payback period of 1.06 years.These results demonstrate the feasibility of spiral-coil heat exchangers as cost-effective and eco-friendly alternatives to conventional electric water heaters.The proposed approach not only enhances the overall energy utilization but also contributes to energy conservation and climate mitigation objectives.
基金supported by the Yayasan Universiti Teknologi PETRONAS(YUTP)under Cost Center 015LC0-485.
文摘Unmanned aerial vehicles(UAVs)technology is rapidly advancing,offering innovative solutions for various industries,including the critical task of oil and gas pipeline surveillance.However,the limited flight time of conventional UAVs presents a significant challenge to comprehensive and continuous monitoring,which is crucial for maintaining the integrity of pipeline infrastructure.This review paper evaluates methods for extending UAV flight endurance,focusing on their potential application in pipeline inspection.Through an extensive literature review,this study identifies the latest advancements in UAV technology,evaluates their effectiveness,and highlights the existing gaps in achieving prolonged flight operations.Advanced techniques,including artificial intelligence(AI),machine learning(ML),and deep learning(DL),are reviewed for their roles in pipeline monitoring.Notably,DL algorithms like You Only Look Once(YOLO)are explored for autonomous flight in UAV-based inspections,real-time defect detection,such as cracks,corrosion,and leaks,enhancing reliability and accuracy.A vital aspect of this research is the proposed deployment of a hybrid drone design combining lighter-than-air(LTA)and heavier-than-air(HTA)principles,achieving a balance of endurance and maneuverability.LTA vehicles utilize buoyancy to reduce energy consumption,thereby extending flight durations.The paper details the methodology for designing LTA vehicles,presenting an analysis of design parameters that align with the requirements for effective pipeline surveillance.The ongoing work is currently at Technology Readiness Level(TRL)4,where key components have been validated in laboratory conditions,with fabrication and flight testing planned for the next phase.Initial design analysis indicates that LTA configurations could offer significant advantages in flight endurance compared to traditional UAV designs.These findings lay the groundwork for future fabrication and testing phases,which will be critical in validating and assessing the proposed approach’s real-world applicability.By outlining the technical complexities and proposing specialized techniques tailored for pipeline monitoring,this paper provides a foundational framework for advancing UAV capabilities in the oil and gas sector.Researchers and industry practitioners can use this roadmap to further develop UAV-enabled surveillance solutions,aiming to improve the reliability,efficiency,and safety of pipeline monitoring.
文摘The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the current 5G networks have not achieved the promised 5G goals, including the projected 2000 times EE improvement over the legacy 4G Long Term Evolution (LTE) networks. This paper provides a comprehensive survey of Artificial Intelligence (AI)-enabled MA techniques, emphasizing their roles in Spectrum Sensing (SS), Dynamic Resource Allocation (DRA), user scheduling, interference mitigation, and protocol adaptation. In particular, we systematically analyze the progression of traditional and modern MA schemes, from Orthogonal Multiple Access (OMA)-based approaches like Time Division Multiple Access (TDMA) and Frequency Division Multiple Access (FDMA) to advanced Non-Orthogonal Multiple Access (NOMA) methods, including power domain-NOMA, Sparse Code Multiple Access (SCMA), and Rate Splitting Multiple Access (RSMA). The study further categorizes AI techniques—such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Federated Learning (FL), and Explainable AI (XAI)—and maps them to practical challenges in Dynamic Spectrum Management (DSM), protocol optimization, and real-time distributed decision-making. Optimization strategies, including metaheuristics and multi-agent learning frameworks, are reviewed to illustrate the potential of AI in enhancing energy efficiency, system responsiveness, and cross-layer RA. Additionally, the review addresses security, privacy, and trust concerns, highlighting solutions like privacy-preserving ML, FL, and XAI in 6G and beyond. By identifying research gaps, challenges, and future directions, this work offers a structured resource for researchers and practitioners aiming to integrate AI into 6G MA systems for intelligent, scalable, and secure wireless communications.
文摘The ascent of the metaverse signfies a profound transformation in our digital landscape,ushering in a complex network of interlinked virtual domains and digital spaces.In this burgeoning metaverse,a paradigm shift is seen in how people engage,collaborate,and become immersed in digital environments.An especially intriguing concept taking root within this metaverse landscape is that of digital twins.Initially rooted in industrial and Internet of Things(IoT)contexts,digital twins are now making their mark in the metaverse,presenting opportunities to elevate user experiences,introduce novel dimensions of interaction,and seamlessly bridge the divide between the virtual and physical realms.Digital twins,conceived initially to replicate physical entities in real-time,have transcended their industrial origins in this new metaverse context.They no longer solely replicate physical objects but extend their domain to encompass digital entities,avatars,virtual environments,and users.Despite the vital contributions of digital twins in the metaverse,there has been no research that has explored the applications and scope of digital twins in the metaverse comprehensively.However,there are a few papers focusing on some particular applications.Addressing this research gap,we present an in-depth review of the pivotal role of application digital twins in the metaverse.We present 15 digital twin applications in the metaverse,ranging from simulation and training to emergency preparedness.This study outlines the critical limitations of integrating digital twins and metaverse and several future research directions.
文摘The Discrete Walsh Hadamard Transform(DWHT)has emerged as an efficient alternative to the Discrete Fourier Transform(DFT)for Orthogonal Frequency Division Multiplexing(OFDM)implementations,particularly in handling channel impairments.In this article,we proposed an efficient Joint Low Complexity Regularized Zero Forcing-Wavelet Domain Equalizer(JLCRLZF-WDE)to replace the traditional Frequency Domain Equalizer(FDE)in DWHT-OFDM systems.Unlike FDE,which requires additional DFT and Inverse DFT(IDFT)computations,the proposed JLCRLZF-WDE directly operates in the Walsh domain,effectively mitigating the computational overhead.The derivation of the proposed JLCRLZF-WDE equations take the effect of the channel,Co-Carrier Frequency Offset(Co-CFO),as well as the noise into account.During the derivation of the system model equations,we assume a MultipleInput-Multiple-Output(MIMO)-OFDM communication system through a Rayleigh fading channel.The Bit Error Rate(BER)performance and computational complexity of the proposed and the conventional algorithms are compared,indicating the significance of the proposed algorithm.Simulation results confirm the superiority of the proposed equalizer,demonstrating a 23.68%±28.4%reduction in computational complexity compared to Minimum Mean Square Error(LMMSE)-FDE based on DFT,while maintaining comparable BER performance at various MIMO configuration.Furthermore,at a BER of 10^(-4),the JLCRLZF-WDE achieves performance parity with conventional Walsh domain LMMSE equalizers,whereas other equalizers require an additional Signal-to-Noise Ratio(SNR)of 3.06 d B to achieve the same performance.
文摘The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on electric vehicles,the infrastructure of charging points,production of electric vehicles,and network modelling,this paper provides a comprehensive overview of electric vehicles,and hybrid vehicles,including an analysis of their market growth,as well as different types of optimization used in the current scenario.In developing countries like India,the biggest barrier is their unfulfilled facility over the charging.Without renewable energy sources,vehicle-to-grid technology facilitates the enhancement of additional power requirements.The mobility factor has been considered an important and special characteristic of electric vehicles.
