Despite the dazzling theoretical capacity,the devasting electrochemical activity of Li_(2)MnO_(3)(LMO)caused by the difficult oxidation of Mn4+impedes its practical application as the lithium-ion battery(LIB)cathode.T...Despite the dazzling theoretical capacity,the devasting electrochemical activity of Li_(2)MnO_(3)(LMO)caused by the difficult oxidation of Mn4+impedes its practical application as the lithium-ion battery(LIB)cathode.The efficacious activation of the Li_(2)MnO_(3) by importing electrochemically active Mn3+ions or morphological engineering is instrumental to its lithium storage activity and structural integrity upon cycling.Herein,we propose a conceptual strategy with metal-organic frameworks(MOFs)as self-sacrificial templates to prepare oxygen-deficient Li_(2)MnO_(3)(O_v-LMO)for exalted lithium storage performance.Attributed to optimized morphological features,LMO materials derived from Mn-BDC(H_(2)BDC=1,4-dicarboxybenzene)delivered superior cycling/rate performances compared with their counterparts derived from Mn-BTC(H_(3)BTC=1,3,5-benzenetricarboxylicacid)and Mn-PTC(H_(4)PTC=pyromellitic acid).Both experimental and theoretical studies elucidate the efficacious activation of primitive LMO materials toward advanced lithium storage by importing oxygen deficiencies.Impressively,O_v-LMO derived from Mn-BDC(O_v-BDC-LMO)delivered intriguing reversible capacities(179.2 mA h g^(-1)at 20 mA g^(-1)after 200 cycles and 100.1 mA h g^(-1)at 80 mA g^(-1)after 300 cycles),which can be attributed to the small particle size that shortens pathways for Li+/electron transport,the enhanced redox activity induced by abundant oxygen vacancies,and the optimized electronic configuration that contributes to the faster lithium diffusivity.This work provides insights into the rational design of LMO by morphological and atomic modulation to direct its activation and practical application as an advanced LIB cathode.展开更多
Defects-rich heterointerfaces integrated with adjustable crystalline phases and atom vacancies,as well as veiled dielectric-responsive character,are instrumental in electromagnetic dissipation.Conventional methods,how...Defects-rich heterointerfaces integrated with adjustable crystalline phases and atom vacancies,as well as veiled dielectric-responsive character,are instrumental in electromagnetic dissipation.Conventional methods,however,constrain their delicate constructions.Herein,an innovative alternative is proposed:carrageenan-assistant cations-regulated(CACR)strategy,which induces a series of sulfides nanoparticles rooted in situ on the surface of carbon matrix.This unique configuration originates from strategic vacancy formation energy of sulfides and strong sulfides-carbon support interaction,benefiting the delicate construction of defects-rich heterostructures in M_(x)S_(y)/carbon composites(M-CAs).Impressively,these generated sulfur vacancies are firstly found to strengthen electron accumulation/consumption ability at heterointerfaces and,simultaneously,induct local asymmetry of electronic structure to evoke large dipole moment,ultimately leading to polarization coupling,i.e.,defect-type interfacial polarization.Such“Janus effect”(Janus effect means versatility,as in the Greek two-headed Janus)of interfacial sulfur vacancies is intuitively confirmed by both theoretical and experimental investigations for the first time.Consequently,the sulfur vacancies-rich heterostructured Co/Ni-CAs displays broad absorption bandwidth of 6.76 GHz at only 1.8 mm,compared to sulfur vacancies-free CAs without any dielectric response.Harnessing defects-rich heterostructures,this one-pot CACR strategy may steer the design and development of advanced nanomaterials,boosting functionality across diverse application domains beyond electromagnetic response.展开更多
Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlo...Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlooked challenge is their demand for considerable run-to-failure data for training.Collection of such training data leads to prohibitive testing efforts as the run-to-failure tests can last for years.Here,we propose a semi-supervised representation learning method to enhance prediction accuracy by learning from data without RUL labels.Our approach builds on a sophisticated deep neural network that comprises an encoder and three decoder heads to extract time-dependent representation features from short-term battery operating data regardless of the existence of RUL labels.The approach is validated using three datasets collected from 34 batteries operating under various conditions,encompassing over 19,900 charge and discharge cycles.Our method achieves a root mean squared error(RMSE)within 25 cycles,even when only 1/50 of the training dataset is labelled,representing a reduction of 48%compared to the conventional approach.We also demonstrate the method's robustness with varying numbers of labelled data and different weights assigned to the three decoder heads.The projection of extracted features in low space reveals that our method effectively learns degradation features from unlabelled data.Our approach highlights the promise of utilising semi-supervised learning to reduce the data demand for reliability monitoring of energy devices.展开更多
To improve the quality of the illumination distribution,one novel indoor visible light communication(VLC)system,which is jointly assisted by the angle-diversity transceivers and simultaneous transmission and reflectio...To improve the quality of the illumination distribution,one novel indoor visible light communication(VLC)system,which is jointly assisted by the angle-diversity transceivers and simultaneous transmission and reflection-intelligent reflecting surface(STAR-IRS),has been proposed in this work.A Harris Hawks optimizer algorithm(HHOA)-based two-stage alternating iteration algorithm(TSAIA)is presented to jointly optimize the magnitude and uniformity of the received optical power.Besides,to demonstrate the superiority of the proposed strategy,several benchmark schemes are simulated and compared.Results showed that compared to other optimization strategies,the TSAIA scheme is more capable of balancing the average value and variance of the received optical power,when the maximal ratio combining(MRC)strategy is adopted at the receiver.Moreover,as the number of the STAR-IRS elements increases,the optical power variance of the system optimized by TSAIA scheme would become smaller while the average optical power would get larger.This study will benefit the design of received optical power distribution for indoor VLC systems.展开更多
A non-orthogonal multiple access(NOMA) power allocation scheme on the basis of the sparrow search algorithm(SSA) is proposed in this work. Specifically, the logarithmic utility function is utilized to address the pote...A non-orthogonal multiple access(NOMA) power allocation scheme on the basis of the sparrow search algorithm(SSA) is proposed in this work. Specifically, the logarithmic utility function is utilized to address the potential fairness issue that may arise from the maximum sum-rate based objective function and the optical power constraints are set considering the non-negativity of the transmit signal, the requirement of the human eyes safety and all users' quality of service(Qo S). Then, the SSA is utilized to solve this optimization problem. Moreover, to demonstrate the superiority of the proposed strategy, it is compared with the fixed power allocation(FPA) and the gain ratio power allocation(GRPA) schemes. Results show that regardless of the number of users considered, the sum-rate achieved by SSA consistently outperforms that of FPA and GRPA schemes. Specifically, compared to FPA and GRPA schemes, the sum-rate obtained by SSA is increased by 40.45% and 53.44% when the number of users is 7, respectively. The proposed SSA also has better performance in terms of user fairness. This work will benefit the design and development of the NOMA-visible light communication(VLC) systems.展开更多
Ensuring the reliability of wind energy as a dependable source requires overcoming challenges posed by the inherent volatility and stochastic nature of wind patterns.Long-term forecasting provides strategic advantages...Ensuring the reliability of wind energy as a dependable source requires overcoming challenges posed by the inherent volatility and stochastic nature of wind patterns.Long-term forecasting provides strategic advantages in managing energy generation projects,enabling the development of effective portfolio management strategies.The primary objective of this study was the development of forecasting methods to support strategic decision-making within the scope of wind energy operations,specifically targeting the PindaíWind Complex and its commercial dispatch.The study integrated Big Data analytics,data engineering,and computational techniques through the application of machine learning algorithms:including eXtreme Gradient Boosting,Multilayer Perceptron,Support Vector Regression,Ridge Regression,and Random Forests,aiming to generate forward-looking projections of the complex’s energy production for the year 2023.To this end,five supervised machine learning techniques were modeled and implemented.These techniques were grounded in their respective mathematical and structural formulations,and the empirical foundation for modeling was provided by historical power generation data from the PindaíWind Complex,combined with high-resolution realized and forecasted meteorological data retrieved via the Open-Meteo API.The models are trained using historical monthly generation data from the PindaíWind Complex,which has an installed capacity of 79.9 MW and is located in the northeastern region of Brazil,along with meteorological data from reanalysis models,such as air temperature,relative humidity,precipitation,surface pressure,wind speed at 10 m,wind speed at 100 m,and wind gusts.These methodologies are applied to forecast monthly wind generation for the year 2023,and the outputs are systematically compared using evaluation metrics to determine the most suitable modeling approach.The results highlight the superiority of the Multilayer Perceptron,Support Vector Regression,and eXtreme Gradient Boosting models,which achieved Kling-Gupta Efficiency(KGE)of 0.89,0.89,and 0.90,mean absolute scaled error(MASE)of 0.29,0.31,and 0.18,root mean square errors(RMSE)of 0.56,0.59,and 0.35,and mean absolute errors(MAE)of 0.48,0.52,and 0.29,respectively.展开更多
In this paper,we study the ρ-meson electromagnetic form factors(EMFFs)within the framework of the light-front quark model.The physical form factors G_(C,M,Q)(Q^(2))of the ρ-meson,as well as the charged square radius...In this paper,we study the ρ-meson electromagnetic form factors(EMFFs)within the framework of the light-front quark model.The physical form factors G_(C,M,Q)(Q^(2))of the ρ-meson,as well as the charged square radius<r^(2)>,the magnetic moment μ,and the quadrupole moment Q,are calculated,which describe the behaviors of EMFFs at zero momentum transfer.Using the type-Ⅱ replacement,we find that the zero-mode does contribute zero to the matrix element S_(00)^(+).It is found that the“M→M_(0)”replacement improves the angular condition remarkably,which permits different prescriptions of ρ-meson EMFFs to give the consistent results.The residual tiny violation of angular condition needs other explanations beyond the zero-mode contributions.Our results indicate that the relativistic effects or interaction internal structure are weaken in the zero-binding limit.This work is also applicable to other spin-1 particles.展开更多
Unmanned Aerial Vehicles(UAVs)have demonstrated significant potential as Aerial Base Stations(A-BSs)for providing data services to Ground Users(GUs),attributed to their flexibility,cost-effectiveness,and high likeliho...Unmanned Aerial Vehicles(UAVs)have demonstrated significant potential as Aerial Base Stations(A-BSs)for providing data services to Ground Users(GUs),attributed to their flexibility,cost-effectiveness,and high likelihood of establishing line-of-sight links.In this article,we formulate the joint power and trajectory optimization problem for a multi-UAV assisted wireless network with no-fly zones constrained,aiming at maximizing the Accumulated Service Data(ASD)of UAVs and minimizing the Average End Age of Information(AEAoI)of GUs.Specifically,this paper proposes the Multi-Agent worst-case Soft Actor Critic(MA-wcSAC)algorithm with a distributional safety-critic.The simulation results demonstrate that,compared to the Multi-Agent Soft Actor Critic(MA-SAC)algorithm,the proposed algorithm exhibits comparable data service performance while reducing security risks by at least 30%at different risk levels.展开更多
Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a locatio...Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.展开更多
The cooperative control of ride comfort and handling stability in automobile suspension systems presents a significant challenge in intelligent chassis system design.This complexity arises from the high degrees of fre...The cooperative control of ride comfort and handling stability in automobile suspension systems presents a significant challenge in intelligent chassis system design.This complexity arises from the high degrees of freedom,diverse operating conditions,and inherent trade-offs between performance metrics in full-car suspension systems.In this paper,a novel switching control strategy is proposed to better balance ride comfort and handling stability for a full-car suspension system.The system integrates a ride comfort controller and an anti-rollover controller,guided by a new rollover risk assessment indicator that requires fewer state variables.First,a vehicle suspension simplification model approach is introduced,reducing the fourteen-degree-of-freedom full-car suspension model to three two-degree-of-freedom models:vertical,pitch and roll.Based on these simplified models,vertical,roll,and pitch controllers are designed,simplifying the controller design process for full-car suspension systems.The ride comfort controller is constructed using the modal energy method in conjunction with the simplified model controllers,while the roll controller functions as the anti-rollover controller.The proposed rollover risk assessment indicator serves as the switching criterion between handling stability and ride comfort control.Experimental results demonstrate that the proposed switching control strategy effectively adapts to various road conditions,enabling the semi-active variable damping suspension system to perform multi-modal switching.Compared to a well-tuned passive suspension,vertical,roll,and pitch accelerations are reduced by 14.13%,13.02%and 13.08%,respectively,significantly improving ride comfort.Additionally,the system effectively mitigates rollover risk,achieving reductions in roll angle,roll speed,and roll acceleration by 19.69%,16.40%,and 29.96%,respectively,thereby greatly enhancing vehicle safety.Overall,the proposed switching control strategy achieves a successful balance between ride comfort and handling stability,enhancing overall driving performance.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
Industrial Control Systems(ICS)in Operational Technology(OT)environments face unique cybersecurity challenges due to legacy systems,critical operational needs,and incompatibility with standard IT security practices.To...Industrial Control Systems(ICS)in Operational Technology(OT)environments face unique cybersecurity challenges due to legacy systems,critical operational needs,and incompatibility with standard IT security practices.To address these challenges,this paper presents the Security Operation and Event Management(SOEM)platform,a software designed to support Security Operations Centers(SOCs)in reaching full visibility of OT environments.SOEM integrates diverse log sources and intrusion detection systems,including logs generated by the control system itself and additional on-the-shelf products,to enhance situational awareness and enable rapid incident response.The pilot project was carried out within the funded project SOC-OT-IGE from the“Centro di Competenza Start 4.0”and is being developed in partnership with Ansaldo Energia and HWG Sababa.The validation has been conducted in a real-world pilot project.Thanks to the mapping to requirements for compliance with IEC 62443,the platform demonstrates its effectiveness through defined key performance indicators(KPIs).This work bridges the gap between IT-centric SOC methodologies and the specialized needs of industrial cybersecurity.展开更多
This paper proposes an extension of the Modified-Plant ADRC(MP-ADRC)strategy to broaden its application to minimum phase dynamical systems.The main features of the MP-ADRC method are the inclusion of a constant gain i...This paper proposes an extension of the Modified-Plant ADRC(MP-ADRC)strategy to broaden its application to minimum phase dynamical systems.The main features of the MP-ADRC method are the inclusion of a constant gain in series with the plant output error and a linear filter in parallel with the overall error system.These structural changes do not influence the input/output dynamics of the original plant,but are intentionally introduced to modify the dynamics to be estimated by the extended state observer(ESO)and,thus,promote an increase in the robustness of the method.Some advantages can also be attributed to the proposed methodology,such as(i)the design procedures of both the controller and the ESO only require knowledge of the sign(±)of the plant input channel coefficient(or control gain);(ii)the plant control input is generated directly by a single ESO state variable.Despite the advantages and the characteristics of MP-ADRC mentioned earlier,closed-loop stability cannot be guaranteed when it is applied to dynamical systems that have finite zeros.To overcome this difficulty,this work introduces an extension in the MP-ADRC method.It basically consists of rewriting the minimum phase plant dynamics according to its relative order,and then follows with the design of the ESO by conveniently increasing the number of ESO state variables.The simulation results are also presented to illustrate the application of the proposed method.展开更多
With the future substantial increase in coverage and network heterogeneity,emerging networks will encounter unprecedented security threats.Covert communication is considered a potential enhanced security and privacy s...With the future substantial increase in coverage and network heterogeneity,emerging networks will encounter unprecedented security threats.Covert communication is considered a potential enhanced security and privacy solution for safeguarding future wireless networks,as it can enable monitors to detect the transmitter's transmission behavior with a low probability,thereby ensuring the secure transmission of private information.Due to its favorable security,it is foreseeable that covert communication will be widely used in various wireless communication settings such as medical,financial,and military scenarios.However,existing covert communication methods still present many challenges toward practical applications.In particular,it is difficult to guarantee the effectiveness of covert schemes based on the randomness of eavesdropping environments,and it is challenging for legitimate users to detect weak covert signals.Considering that emerging artificial-intelligence-aided transmission technologies can open up entirely new opportunities to address the above challenges,we provide a comprehensive review of recent advances and potential research directions in the field of intelligent covert communications in this work.First,the basic concepts and performance metrics of covert communications are introduced.Then,existing effective covert communication techniques in the time,frequency,spatial,power,and modulation domains are reviewed.Finally,this paper discusses potential implementations and challenges for intelligent covert communications in future networks.展开更多
Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate becau...Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.展开更多
Although the image dehazing problem has received considerable attention over recent years,the existing models often prioritise performance at the expense of complexity,making them unsuitable for real-world application...Although the image dehazing problem has received considerable attention over recent years,the existing models often prioritise performance at the expense of complexity,making them unsuitable for real-world applications,which require algorithms to be deployed on resource constrained-devices.To address this challenge,we propose WaveLiteDehaze-Network(WLD-Net),an end-to-end dehazing model that delivers performance comparable to complex models while operating in real time and using significantly fewer parameters.This approach capitalises on the insight that haze predominantly affects low-frequency infor-mation.By exclusively processing the image in the frequency domain using discrete wavelet transform(DWT),we segregate the image into high and low frequencies and process them separately.This allows us to preserve high-frequency details and recover low-frequency components affected by haze,distinguishing our method from existing approaches that use spatial domain processing as the backbone,with DWT serving as an auxiliary component.DWT is applied at multiple levels for better in-formation retention while also accelerating computation by downsampling feature maps.Subsequently,a learning-based fusion mechanism reintegrates the processed frequencies to reconstruct the dehazed image.Experiments show that WLD-Net out-performs other low-parameter models on real-world hazy images and rivals much larger models,achieving the highest PSNR and SSIM scores on the O-Haze dataset.Qualitatively,the proposed method demonstrates its effectiveness in handling a diverse range of haze types,delivering visually pleasing results and robust performance,while also generalising well across different scenarios.With only 0.385 million parameters(more than 100 times smaller than comparable dehazing methods),WLD-Net processes 1024×1024 images in just 0.045 s,highlighting its applicability across various real-world scenarios.The code is available at https://github.com/AliMurtaza29/WLD-Net.展开更多
The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices.This pape...The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices.This paper introduces the Adaptive Blended Marine Predators Algorithm(AB-MPA),a novel optimization technique designed to enhance Quality of Service(QoS)in IoT systems by dynamically optimizing network configurations for improved energy efficiency and stability.Our results represent significant improvements in network performance metrics such as energy consumption,throughput,and operational stability,indicating that AB-MPA effectively addresses the pressing needs ofmodern IoT environments.Nodes are initiated with 100 J of stored energy,and energy is consumed at 0.01 J per square meter in each node to emphasize energy-efficient networks.The algorithm also provides sufficient network lifetime extension to a resourceful 7000 cycles for up to 200 nodes with a maximum Packet Delivery Ratio(PDR)of 99% and a robust network throughput of up to 1800 kbps in more compact node configurations.This study proposes a viable solution to a critical problem and opens avenues for further research into scalable network management for diverse applications.展开更多
Correction to:Nano-Micro Lett.(2025)17:24 https://doi.org/10.1007/s40820-024-01515-0 Following publication of the original article[1],the authors reported the author list needed to be updated because the last three au...Correction to:Nano-Micro Lett.(2025)17:24 https://doi.org/10.1007/s40820-024-01515-0 Following publication of the original article[1],the authors reported the author list needed to be updated because the last three author names were duplicated.The correct author list has been provided in this Correction.The original article[1]has been corrected.展开更多
The Internet of Vehicles(IoV)has been widely researched in recent years,and cloud computing has been one of the key technologies in the IoV.Although cloud computing provides high performance compute,storage and networ...The Internet of Vehicles(IoV)has been widely researched in recent years,and cloud computing has been one of the key technologies in the IoV.Although cloud computing provides high performance compute,storage and networking services,the IoV still suffers with high processing latency,less mobility support and location awareness.In this paper,we integrate fog computing and software defined networking(SDN) to address those problems.Fog computing extends computing and storing to the edge of the network,which could decrease latency remarkably in addition to enable mobility support and location awareness.Meanwhile,SDN provides flexible centralized control and global knowledge to the network.In order to apply the software defined cloud/fog networking(SDCFN) architecture in the IoV effectively,we propose a novel SDN-based modified constrained optimization particle swarm optimization(MPSO-CO) algorithm which uses the reverse of the flight of mutation particles and linear decrease inertia weight to enhance the performance of constrained optimization particle swarm optimization(PSO-CO).The simulation results indicate that the SDN-based MPSO-CO algorithm could effectively decrease the latency and improve the quality of service(QoS) in the SDCFN architecture.展开更多
A shared control of highly automated Steer-by-Wire system is proposed for cooperative driving between the driver and vehicle in the face of driver's abnormal driving. A fault detection scheme is designed to detect...A shared control of highly automated Steer-by-Wire system is proposed for cooperative driving between the driver and vehicle in the face of driver's abnormal driving. A fault detection scheme is designed to detect the abnormal driving behaviour and transfer the control of the car to the automatic system designed based on a fault tolerant model predictive control(MPC) controller driving the vehicle along an optimal safe path.The proposed concept and control algorithm are tested in a number of scenarios representing intersection, lane change and different types of driver's abnormal behaviour. The simulation results show the feasibility and effectiveness of the proposed method.展开更多
基金the financial support from the Special Funds for the Cultivation of Guangdong College Students’Scientific and Technological Innovation(“Climbing Program”Special Funds,pdjh2023b0145)the Research and Development Plan Project in Key Fields of Guangdong Province(2020B0101030005)+1 种基金the Applied special project of Guangdong Provincial Science and Technology Plan(2017B090917002)the Basic and Applied Basic Research Fund of Guangdong Province(2019B1515120027)。
文摘Despite the dazzling theoretical capacity,the devasting electrochemical activity of Li_(2)MnO_(3)(LMO)caused by the difficult oxidation of Mn4+impedes its practical application as the lithium-ion battery(LIB)cathode.The efficacious activation of the Li_(2)MnO_(3) by importing electrochemically active Mn3+ions or morphological engineering is instrumental to its lithium storage activity and structural integrity upon cycling.Herein,we propose a conceptual strategy with metal-organic frameworks(MOFs)as self-sacrificial templates to prepare oxygen-deficient Li_(2)MnO_(3)(O_v-LMO)for exalted lithium storage performance.Attributed to optimized morphological features,LMO materials derived from Mn-BDC(H_(2)BDC=1,4-dicarboxybenzene)delivered superior cycling/rate performances compared with their counterparts derived from Mn-BTC(H_(3)BTC=1,3,5-benzenetricarboxylicacid)and Mn-PTC(H_(4)PTC=pyromellitic acid).Both experimental and theoretical studies elucidate the efficacious activation of primitive LMO materials toward advanced lithium storage by importing oxygen deficiencies.Impressively,O_v-LMO derived from Mn-BDC(O_v-BDC-LMO)delivered intriguing reversible capacities(179.2 mA h g^(-1)at 20 mA g^(-1)after 200 cycles and 100.1 mA h g^(-1)at 80 mA g^(-1)after 300 cycles),which can be attributed to the small particle size that shortens pathways for Li+/electron transport,the enhanced redox activity induced by abundant oxygen vacancies,and the optimized electronic configuration that contributes to the faster lithium diffusivity.This work provides insights into the rational design of LMO by morphological and atomic modulation to direct its activation and practical application as an advanced LIB cathode.
基金financially supported by the National Natural Science Foundation of China(Grants nos.62201411,62371378,22205168,52302150 and 62304171)the China Postdoctoral Science Foundation(2022M722500)+1 种基金the Fundamental Research Funds for the Central Universities(Grants nos.ZYTS2308 and 20103237929)Startup Foundation of Xidian University(10251220001).
文摘Defects-rich heterointerfaces integrated with adjustable crystalline phases and atom vacancies,as well as veiled dielectric-responsive character,are instrumental in electromagnetic dissipation.Conventional methods,however,constrain their delicate constructions.Herein,an innovative alternative is proposed:carrageenan-assistant cations-regulated(CACR)strategy,which induces a series of sulfides nanoparticles rooted in situ on the surface of carbon matrix.This unique configuration originates from strategic vacancy formation energy of sulfides and strong sulfides-carbon support interaction,benefiting the delicate construction of defects-rich heterostructures in M_(x)S_(y)/carbon composites(M-CAs).Impressively,these generated sulfur vacancies are firstly found to strengthen electron accumulation/consumption ability at heterointerfaces and,simultaneously,induct local asymmetry of electronic structure to evoke large dipole moment,ultimately leading to polarization coupling,i.e.,defect-type interfacial polarization.Such“Janus effect”(Janus effect means versatility,as in the Greek two-headed Janus)of interfacial sulfur vacancies is intuitively confirmed by both theoretical and experimental investigations for the first time.Consequently,the sulfur vacancies-rich heterostructured Co/Ni-CAs displays broad absorption bandwidth of 6.76 GHz at only 1.8 mm,compared to sulfur vacancies-free CAs without any dielectric response.Harnessing defects-rich heterostructures,this one-pot CACR strategy may steer the design and development of advanced nanomaterials,boosting functionality across diverse application domains beyond electromagnetic response.
基金supported by the National Natural Science Foundation of China(No.52207229)the Key Research and Development Program of Ningxia Hui Autonomous Region of China(No.2024BEE02003)+1 种基金the financial support from the AEGiS Research Grant 2024,University of Wollongong(No.R6254)the financial support from the China Scholarship Council(No.202207550010).
文摘Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlooked challenge is their demand for considerable run-to-failure data for training.Collection of such training data leads to prohibitive testing efforts as the run-to-failure tests can last for years.Here,we propose a semi-supervised representation learning method to enhance prediction accuracy by learning from data without RUL labels.Our approach builds on a sophisticated deep neural network that comprises an encoder and three decoder heads to extract time-dependent representation features from short-term battery operating data regardless of the existence of RUL labels.The approach is validated using three datasets collected from 34 batteries operating under various conditions,encompassing over 19,900 charge and discharge cycles.Our method achieves a root mean squared error(RMSE)within 25 cycles,even when only 1/50 of the training dataset is labelled,representing a reduction of 48%compared to the conventional approach.We also demonstrate the method's robustness with varying numbers of labelled data and different weights assigned to the three decoder heads.The projection of extracted features in low space reveals that our method effectively learns degradation features from unlabelled data.Our approach highlights the promise of utilising semi-supervised learning to reduce the data demand for reliability monitoring of energy devices.
基金supported by the National Natural Science Foundation of China(No.62071365)the Key Research and Development Program of Shaanxi Province(No.2017ZDCXL-GY-06-02).
文摘To improve the quality of the illumination distribution,one novel indoor visible light communication(VLC)system,which is jointly assisted by the angle-diversity transceivers and simultaneous transmission and reflection-intelligent reflecting surface(STAR-IRS),has been proposed in this work.A Harris Hawks optimizer algorithm(HHOA)-based two-stage alternating iteration algorithm(TSAIA)is presented to jointly optimize the magnitude and uniformity of the received optical power.Besides,to demonstrate the superiority of the proposed strategy,several benchmark schemes are simulated and compared.Results showed that compared to other optimization strategies,the TSAIA scheme is more capable of balancing the average value and variance of the received optical power,when the maximal ratio combining(MRC)strategy is adopted at the receiver.Moreover,as the number of the STAR-IRS elements increases,the optical power variance of the system optimized by TSAIA scheme would become smaller while the average optical power would get larger.This study will benefit the design of received optical power distribution for indoor VLC systems.
基金supported by the Cooperative Research Project between China Coal Energy Research Institute Co.,Ltd. and Xidian University (No.N-KY-HX-1101-202302-00725)the Key Research and Development Program of Shaanxi Province (No.2017ZDCXL-GY-06-02)。
文摘A non-orthogonal multiple access(NOMA) power allocation scheme on the basis of the sparrow search algorithm(SSA) is proposed in this work. Specifically, the logarithmic utility function is utilized to address the potential fairness issue that may arise from the maximum sum-rate based objective function and the optical power constraints are set considering the non-negativity of the transmit signal, the requirement of the human eyes safety and all users' quality of service(Qo S). Then, the SSA is utilized to solve this optimization problem. Moreover, to demonstrate the superiority of the proposed strategy, it is compared with the fixed power allocation(FPA) and the gain ratio power allocation(GRPA) schemes. Results show that regardless of the number of users considered, the sum-rate achieved by SSA consistently outperforms that of FPA and GRPA schemes. Specifically, compared to FPA and GRPA schemes, the sum-rate obtained by SSA is increased by 40.45% and 53.44% when the number of users is 7, respectively. The proposed SSA also has better performance in terms of user fairness. This work will benefit the design and development of the NOMA-visible light communication(VLC) systems.
文摘Ensuring the reliability of wind energy as a dependable source requires overcoming challenges posed by the inherent volatility and stochastic nature of wind patterns.Long-term forecasting provides strategic advantages in managing energy generation projects,enabling the development of effective portfolio management strategies.The primary objective of this study was the development of forecasting methods to support strategic decision-making within the scope of wind energy operations,specifically targeting the PindaíWind Complex and its commercial dispatch.The study integrated Big Data analytics,data engineering,and computational techniques through the application of machine learning algorithms:including eXtreme Gradient Boosting,Multilayer Perceptron,Support Vector Regression,Ridge Regression,and Random Forests,aiming to generate forward-looking projections of the complex’s energy production for the year 2023.To this end,five supervised machine learning techniques were modeled and implemented.These techniques were grounded in their respective mathematical and structural formulations,and the empirical foundation for modeling was provided by historical power generation data from the PindaíWind Complex,combined with high-resolution realized and forecasted meteorological data retrieved via the Open-Meteo API.The models are trained using historical monthly generation data from the PindaíWind Complex,which has an installed capacity of 79.9 MW and is located in the northeastern region of Brazil,along with meteorological data from reanalysis models,such as air temperature,relative humidity,precipitation,surface pressure,wind speed at 10 m,wind speed at 100 m,and wind gusts.These methodologies are applied to forecast monthly wind generation for the year 2023,and the outputs are systematically compared using evaluation metrics to determine the most suitable modeling approach.The results highlight the superiority of the Multilayer Perceptron,Support Vector Regression,and eXtreme Gradient Boosting models,which achieved Kling-Gupta Efficiency(KGE)of 0.89,0.89,and 0.90,mean absolute scaled error(MASE)of 0.29,0.31,and 0.18,root mean square errors(RMSE)of 0.56,0.59,and 0.35,and mean absolute errors(MAE)of 0.48,0.52,and 0.29,respectively.
基金supported by the National Natural Science Foundation of China(Grant Nos.11875122,12175025,and 12147102)Tongling University Talent Program(Grant No.R23100)。
文摘In this paper,we study the ρ-meson electromagnetic form factors(EMFFs)within the framework of the light-front quark model.The physical form factors G_(C,M,Q)(Q^(2))of the ρ-meson,as well as the charged square radius<r^(2)>,the magnetic moment μ,and the quadrupole moment Q,are calculated,which describe the behaviors of EMFFs at zero momentum transfer.Using the type-Ⅱ replacement,we find that the zero-mode does contribute zero to the matrix element S_(00)^(+).It is found that the“M→M_(0)”replacement improves the angular condition remarkably,which permits different prescriptions of ρ-meson EMFFs to give the consistent results.The residual tiny violation of angular condition needs other explanations beyond the zero-mode contributions.Our results indicate that the relativistic effects or interaction internal structure are weaken in the zero-binding limit.This work is also applicable to other spin-1 particles.
基金supported in part by the National Natural Science Foundation of China(Nos.62371369 and 62376204)the National Key R&D Program of China(No.2022YFC3301300).
文摘Unmanned Aerial Vehicles(UAVs)have demonstrated significant potential as Aerial Base Stations(A-BSs)for providing data services to Ground Users(GUs),attributed to their flexibility,cost-effectiveness,and high likelihood of establishing line-of-sight links.In this article,we formulate the joint power and trajectory optimization problem for a multi-UAV assisted wireless network with no-fly zones constrained,aiming at maximizing the Accumulated Service Data(ASD)of UAVs and minimizing the Average End Age of Information(AEAoI)of GUs.Specifically,this paper proposes the Multi-Agent worst-case Soft Actor Critic(MA-wcSAC)algorithm with a distributional safety-critic.The simulation results demonstrate that,compared to the Multi-Agent Soft Actor Critic(MA-SAC)algorithm,the proposed algorithm exhibits comparable data service performance while reducing security risks by at least 30%at different risk levels.
基金supported by the National Natural Science Foundation of China(61901341).
文摘Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.
基金Supported by the Australian Research Council’s Discovery Project(Grant No.DP200100149)Taishan Scholars Program of Shandong Province(Grant No.tsqn202211062)Chinses Scholarship Council(Grant No.202006690005).
文摘The cooperative control of ride comfort and handling stability in automobile suspension systems presents a significant challenge in intelligent chassis system design.This complexity arises from the high degrees of freedom,diverse operating conditions,and inherent trade-offs between performance metrics in full-car suspension systems.In this paper,a novel switching control strategy is proposed to better balance ride comfort and handling stability for a full-car suspension system.The system integrates a ride comfort controller and an anti-rollover controller,guided by a new rollover risk assessment indicator that requires fewer state variables.First,a vehicle suspension simplification model approach is introduced,reducing the fourteen-degree-of-freedom full-car suspension model to three two-degree-of-freedom models:vertical,pitch and roll.Based on these simplified models,vertical,roll,and pitch controllers are designed,simplifying the controller design process for full-car suspension systems.The ride comfort controller is constructed using the modal energy method in conjunction with the simplified model controllers,while the roll controller functions as the anti-rollover controller.The proposed rollover risk assessment indicator serves as the switching criterion between handling stability and ride comfort control.Experimental results demonstrate that the proposed switching control strategy effectively adapts to various road conditions,enabling the semi-active variable damping suspension system to perform multi-modal switching.Compared to a well-tuned passive suspension,vertical,roll,and pitch accelerations are reduced by 14.13%,13.02%and 13.08%,respectively,significantly improving ride comfort.Additionally,the system effectively mitigates rollover risk,achieving reductions in roll angle,roll speed,and roll acceleration by 19.69%,16.40%,and 29.96%,respectively,thereby greatly enhancing vehicle safety.Overall,the proposed switching control strategy achieves a successful balance between ride comfort and handling stability,enhancing overall driving performance.
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.
基金supported by the project“Airfield”under the PoC Launchpad initiative funded by the Fondazione Compagnia di San Paolo.
文摘Industrial Control Systems(ICS)in Operational Technology(OT)environments face unique cybersecurity challenges due to legacy systems,critical operational needs,and incompatibility with standard IT security practices.To address these challenges,this paper presents the Security Operation and Event Management(SOEM)platform,a software designed to support Security Operations Centers(SOCs)in reaching full visibility of OT environments.SOEM integrates diverse log sources and intrusion detection systems,including logs generated by the control system itself and additional on-the-shelf products,to enhance situational awareness and enable rapid incident response.The pilot project was carried out within the funded project SOC-OT-IGE from the“Centro di Competenza Start 4.0”and is being developed in partnership with Ansaldo Energia and HWG Sababa.The validation has been conducted in a real-world pilot project.Thanks to the mapping to requirements for compliance with IEC 62443,the platform demonstrates its effectiveness through defined key performance indicators(KPIs).This work bridges the gap between IT-centric SOC methodologies and the specialized needs of industrial cybersecurity.
基金supported in part by the Brazilian research agencies CNPq and CAPESby the Fundação Carlos Chagas Filho de AmparoàPesquisa do Estado do Rio de Janeiro,FAPERJ-Brasil(Project E-26/210.425/2024).
文摘This paper proposes an extension of the Modified-Plant ADRC(MP-ADRC)strategy to broaden its application to minimum phase dynamical systems.The main features of the MP-ADRC method are the inclusion of a constant gain in series with the plant output error and a linear filter in parallel with the overall error system.These structural changes do not influence the input/output dynamics of the original plant,but are intentionally introduced to modify the dynamics to be estimated by the extended state observer(ESO)and,thus,promote an increase in the robustness of the method.Some advantages can also be attributed to the proposed methodology,such as(i)the design procedures of both the controller and the ESO only require knowledge of the sign(±)of the plant input channel coefficient(or control gain);(ii)the plant control input is generated directly by a single ESO state variable.Despite the advantages and the characteristics of MP-ADRC mentioned earlier,closed-loop stability cannot be guaranteed when it is applied to dynamical systems that have finite zeros.To overcome this difficulty,this work introduces an extension in the MP-ADRC method.It basically consists of rewriting the minimum phase plant dynamics according to its relative order,and then follows with the design of the ESO by conveniently increasing the number of ESO state variables.The simulation results are also presented to illustrate the application of the proposed method.
基金supported by the National Natural Science Foundation of China(62425103)the National Key Research and Development Program of China(2022YFC3301300)。
文摘With the future substantial increase in coverage and network heterogeneity,emerging networks will encounter unprecedented security threats.Covert communication is considered a potential enhanced security and privacy solution for safeguarding future wireless networks,as it can enable monitors to detect the transmitter's transmission behavior with a low probability,thereby ensuring the secure transmission of private information.Due to its favorable security,it is foreseeable that covert communication will be widely used in various wireless communication settings such as medical,financial,and military scenarios.However,existing covert communication methods still present many challenges toward practical applications.In particular,it is difficult to guarantee the effectiveness of covert schemes based on the randomness of eavesdropping environments,and it is challenging for legitimate users to detect weak covert signals.Considering that emerging artificial-intelligence-aided transmission technologies can open up entirely new opportunities to address the above challenges,we provide a comprehensive review of recent advances and potential research directions in the field of intelligent covert communications in this work.First,the basic concepts and performance metrics of covert communications are introduced.Then,existing effective covert communication techniques in the time,frequency,spatial,power,and modulation domains are reviewed.Finally,this paper discusses potential implementations and challenges for intelligent covert communications in future networks.
文摘Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.
基金Japan International Cooperation Agency(JICA)via Malaysia-Japan Linkage Research Grant 2024.
文摘Although the image dehazing problem has received considerable attention over recent years,the existing models often prioritise performance at the expense of complexity,making them unsuitable for real-world applications,which require algorithms to be deployed on resource constrained-devices.To address this challenge,we propose WaveLiteDehaze-Network(WLD-Net),an end-to-end dehazing model that delivers performance comparable to complex models while operating in real time and using significantly fewer parameters.This approach capitalises on the insight that haze predominantly affects low-frequency infor-mation.By exclusively processing the image in the frequency domain using discrete wavelet transform(DWT),we segregate the image into high and low frequencies and process them separately.This allows us to preserve high-frequency details and recover low-frequency components affected by haze,distinguishing our method from existing approaches that use spatial domain processing as the backbone,with DWT serving as an auxiliary component.DWT is applied at multiple levels for better in-formation retention while also accelerating computation by downsampling feature maps.Subsequently,a learning-based fusion mechanism reintegrates the processed frequencies to reconstruct the dehazed image.Experiments show that WLD-Net out-performs other low-parameter models on real-world hazy images and rivals much larger models,achieving the highest PSNR and SSIM scores on the O-Haze dataset.Qualitatively,the proposed method demonstrates its effectiveness in handling a diverse range of haze types,delivering visually pleasing results and robust performance,while also generalising well across different scenarios.With only 0.385 million parameters(more than 100 times smaller than comparable dehazing methods),WLD-Net processes 1024×1024 images in just 0.045 s,highlighting its applicability across various real-world scenarios.The code is available at https://github.com/AliMurtaza29/WLD-Net.
文摘The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices.This paper introduces the Adaptive Blended Marine Predators Algorithm(AB-MPA),a novel optimization technique designed to enhance Quality of Service(QoS)in IoT systems by dynamically optimizing network configurations for improved energy efficiency and stability.Our results represent significant improvements in network performance metrics such as energy consumption,throughput,and operational stability,indicating that AB-MPA effectively addresses the pressing needs ofmodern IoT environments.Nodes are initiated with 100 J of stored energy,and energy is consumed at 0.01 J per square meter in each node to emphasize energy-efficient networks.The algorithm also provides sufficient network lifetime extension to a resourceful 7000 cycles for up to 200 nodes with a maximum Packet Delivery Ratio(PDR)of 99% and a robust network throughput of up to 1800 kbps in more compact node configurations.This study proposes a viable solution to a critical problem and opens avenues for further research into scalable network management for diverse applications.
文摘Correction to:Nano-Micro Lett.(2025)17:24 https://doi.org/10.1007/s40820-024-01515-0 Following publication of the original article[1],the authors reported the author list needed to be updated because the last three author names were duplicated.The correct author list has been provided in this Correction.The original article[1]has been corrected.
基金supported in part by National Natural Science Foundation of China (No.61401331,No.61401328)111 Project in Xidian University of China(B08038)+2 种基金Hong Kong,Macao and Taiwan Science and Technology Cooperation Special Project (2014DFT10320,2015DFT10160)The National Science and Technology Major Project of the Ministry of Science and Technology of China(2015zx03002006-003)FundamentalResearch Funds for the Central Universities (20101155739)
文摘The Internet of Vehicles(IoV)has been widely researched in recent years,and cloud computing has been one of the key technologies in the IoV.Although cloud computing provides high performance compute,storage and networking services,the IoV still suffers with high processing latency,less mobility support and location awareness.In this paper,we integrate fog computing and software defined networking(SDN) to address those problems.Fog computing extends computing and storing to the edge of the network,which could decrease latency remarkably in addition to enable mobility support and location awareness.Meanwhile,SDN provides flexible centralized control and global knowledge to the network.In order to apply the software defined cloud/fog networking(SDCFN) architecture in the IoV effectively,we propose a novel SDN-based modified constrained optimization particle swarm optimization(MPSO-CO) algorithm which uses the reverse of the flight of mutation particles and linear decrease inertia weight to enhance the performance of constrained optimization particle swarm optimization(PSO-CO).The simulation results indicate that the SDN-based MPSO-CO algorithm could effectively decrease the latency and improve the quality of service(QoS) in the SDCFN architecture.
文摘A shared control of highly automated Steer-by-Wire system is proposed for cooperative driving between the driver and vehicle in the face of driver's abnormal driving. A fault detection scheme is designed to detect the abnormal driving behaviour and transfer the control of the car to the automatic system designed based on a fault tolerant model predictive control(MPC) controller driving the vehicle along an optimal safe path.The proposed concept and control algorithm are tested in a number of scenarios representing intersection, lane change and different types of driver's abnormal behaviour. The simulation results show the feasibility and effectiveness of the proposed method.
