Differential pulse-position modulation(DP PM)can achieve a good compromise between power and bandwidth requirements.However,the output sequence has undetectable insertions and deletions.This paper proposes a successiv...Differential pulse-position modulation(DP PM)can achieve a good compromise between power and bandwidth requirements.However,the output sequence has undetectable insertions and deletions.This paper proposes a successive cancellation(SC)decoding scheme based on the weighted levenshtein distance(WLD)of polar codes for correcting insertions/deletions in DPPM systems.In this method,the WLD is used to calculate the transfer probabilities recursively to obtain likelihood ratios,and the low-complexity SC decoding method is built according to the error characteristics to match the DPPM system.Additionally,the proposed SC decoding scheme is extended to list decoding,which can further improve error correction performance.Simulation results show that the proposed scheme can effectively correct insertions/deletions in the DPPM system,which enhances its reliability and performance.展开更多
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
Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically ...Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically investigates recent advancements in sustainable alternatives,including geopolymer concrete,engineered innovacementitious composites(ECC),bio-concrete,fiber-reinforced polymers(FRPs),and bamboo,stainless steel,and steel-CFRP hybrid bars.Each material is evaluated based on marine durability,mechanical performance,environmental impact,and cost feasibility using life cycle assessment,durability modelling,and a multi-criteria decisionsupport framework.The results reveal that geopolymer concrete and FRP reinforcement’s exhibit superior corrosion resistance and environmental benefits,while ECC and steel-CFRP composites offer structural resilience with moderate environmental trade-offs.However,challenges remain in long-term performance validation,standardization,and market integration.The review concludes that a combined approach involving innovative materials,computational tools,and sustainability assessment is essential for advancing marine infrastructure.Outlook recommendations include focused field studies,development of regulatory guidelines,and interdisciplinary collaboration to drive the practical adoption of eco-efficient materials in coastal and offshore construction.展开更多
Copper nanoclusters(CuNCs)have gained prominence due to their remarkable color-tunable light emission and cost-effective,versatile solution-based synthesis.The use of various functional ligands in the synthesis of CuN...Copper nanoclusters(CuNCs)have gained prominence due to their remarkable color-tunable light emission and cost-effective,versatile solution-based synthesis.The use of various functional ligands in the synthesis of CuNCs enables the modulation of their emission wavelengths and enhances their environmental stability.These nanoclusters have found applications across diverse fields,including catalysis,sensing,bioimaging,and optoelectronics.This review offers a focused and up-to-date perspective by covering literature from the past decade(2015―2025)with an explicit emphasis on practical environmental matrices,including heavy metal ions,organic pollutants,pharmaceuticals,and other environmental contaminants.It systematically compares sensing mechanisms(e.g.,fluorescence quenching,turn-on responses,ratiometric and inner-filter effects)and provides tabulated limits of detection for key heavy metals,organic pollutants,and pharmaceuticals to facilitate direct benchmarking.Finally,the review highlights translational gaps for in-field deployment,such as matrix interferences,long-term stability of ligand-stabilized CuNCs,sample pre-treatment needs,and the absence of standardized validation protocols and proposes targeted research directions to bridge laboratory advances with real-world environmental monitoring.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
Deep learning methods have been widely applied in motor imagery(MI)-based brain-computer interfaces(BCI)for decoding electroencephalogram(EEG)signals.High temporal resolution and asymmetric spatial activation are fund...Deep learning methods have been widely applied in motor imagery(MI)-based brain-computer interfaces(BCI)for decoding electroencephalogram(EEG)signals.High temporal resolution and asymmetric spatial activation are fundamental properties of EEG during MI processes.However,due to the limited receptive field of convolutional kernels,traditional convolutional neural networks(CNNs)often focus only on local features,and are insufficient to cover neural processes across different frequency bands and duration scales.This limitation hinders the effective characterization of rhythmic activity changes in MI-EEG signals over time.Additionally,MI-EEG signals exhibit significant asymmetric activation between the left and right hemispheres.Traditional spatial feature extraction methods overlook the interaction between global and local regions at the spatial scale of EEG signals,resulting in inadequate spatial representation and ultimately limiting decoding accuracy.To address these limitations,in this study,a novel deep learning network that integrates multi-modal temporal features with spatially asymmetric feature modeling was proposed.The network first extracts multi-modal temporal information from EEG data channels,and then captures global and hemispheric spatial features in the spatial dimension and fuses them through an advanced fusion layer.Global dependencies are captured using a self-attention module,and a multi-scale convolutional fusion module is introduced to explore the relationships between the two types of temporal features.The fused features are classified through a classification layer to accomplish motor imagery task classification.To mitigate the issue of limited sample size,a data augmentation strategy based on signal segmentation and recombination is designed.Experimental results on the BCI Competition IV-2a(bbic-IV-2a)and BCI Competition IV-2b(bbic-IV-2a)datasets demonstrated that the proposed method achieved superior accuracy in multi-class motor imagery classification compared with existing models.On the BCI-IV-2a dataset,it attained an average classification accuracy of 84.36%,while also showing strong performance on the binary classification BCI-IV-2b dataset.These outcomes validate the capability of the proposed network to enhance MI-EEG classification accuracy.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
Plant health is increasingly threatened by environmental stressors,improper irrigation practices,and animal interference,leading to decreased growth and vitality.Current solutions often fail to integrate autonomous ir...Plant health is increasingly threatened by environmental stressors,improper irrigation practices,and animal interference,leading to decreased growth and vitality.Current solutions often fail to integrate autonomous irrigation with effective deterrent mechanisms in a single system.This paper presents the Intelligent Sapling Shield,an innovative device designed to enhance plant protection and optimize growth conditions.The system features an autonomous soil moisture regulation mechanism to optimize water usage,reducing wastage and irrigation costs,while a vibrational deterrent system mitigates animal interference,preventing crop damage.Constructed from plastic mesh,the device ensures proper sunlight exposure,airflow,and shade,with an integrated waterproof LED strip for night-time illumination.Results demonstrate that the system maintains optimal soil moisture levels,reducing water consumption compared to traditional irrigation methods.Additionally,automated plant care minimizes labour requirements,ensuring consistent hydration and protection while enhancing crop resilience and yield.The design emphasizes affordability,portability,and ease of installation,making it suitable for both small-scale urban gardening and large-scale agricultural deployment.Its modular structure allows for customization depending on plant type and environmental conditions,further extending its applicability.By integrating irrigation efficiency,protective deterrence,and energy-efficient illumination,the Intelligent Sapling Shield creates a holistic solution that addresses multiple challenges faced in plant cultivation.By promoting cost-effective,resource-efficient,and sustainable agricultural practices,the Intelligent Sapling Shield contributes to urban greening initiatives and biodiversity conservation,supporting long-term ecological sustainability and offering significant potential for future smart farming innovations.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
A phase-aware cross-modal framework is presented that synthesizes UWF_FA from non-invasive UWF_RI for diabetic retinopathy(DR)stratification.A curated cohort of 1198 patients(2915 UWF_RI and 17,854 UWF_FA images)with ...A phase-aware cross-modal framework is presented that synthesizes UWF_FA from non-invasive UWF_RI for diabetic retinopathy(DR)stratification.A curated cohort of 1198 patients(2915 UWF_RI and 17,854 UWF_FA images)with strict registration quality supports training across three angiographic phases(initial,mid,final).The generator is based on a modified pix2pixHD with an added Gradient Variance Loss to better preserve microvasculature,and is evaluated using MAE,PSNR,SSIM,and MS-SSIM on held-out pairs.Quantitatively,the mid phase achieves the lowestMAE(98.76±42.67),while SSIM remains high across phases.Expert reviewshows substantial agreement(Cohen's κ=0.78–0.82)and Turing-stylemisclassification of 50%–70%of synthetic images as real,indicating strong perceptual realism.For downstream DR stratification,fusing multi-phase synthetic UWF_FA with UWF_RI in a Swin Transformer classifier yields significant gains over a UWF_RI-only baseline,with the full-phase setting(Set D)reaching AUC=0.910 and accuracy=0.829.These results support synthetic UWF_FA as a scalable,non-invasive complement to dye-based angiography that enhances screening accuracy while avoiding injection-related risks.展开更多
基金supported by National Natural Science Foundation of China(No.61801327).
文摘Differential pulse-position modulation(DP PM)can achieve a good compromise between power and bandwidth requirements.However,the output sequence has undetectable insertions and deletions.This paper proposes a successive cancellation(SC)decoding scheme based on the weighted levenshtein distance(WLD)of polar codes for correcting insertions/deletions in DPPM systems.In this method,the WLD is used to calculate the transfer probabilities recursively to obtain likelihood ratios,and the low-complexity SC decoding method is built according to the error characteristics to match the DPPM system.Additionally,the proposed SC decoding scheme is extended to list decoding,which can further improve error correction performance.Simulation results show that the proposed scheme can effectively correct insertions/deletions in the DPPM system,which enhances its reliability and performance.
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.
文摘Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically investigates recent advancements in sustainable alternatives,including geopolymer concrete,engineered innovacementitious composites(ECC),bio-concrete,fiber-reinforced polymers(FRPs),and bamboo,stainless steel,and steel-CFRP hybrid bars.Each material is evaluated based on marine durability,mechanical performance,environmental impact,and cost feasibility using life cycle assessment,durability modelling,and a multi-criteria decisionsupport framework.The results reveal that geopolymer concrete and FRP reinforcement’s exhibit superior corrosion resistance and environmental benefits,while ECC and steel-CFRP composites offer structural resilience with moderate environmental trade-offs.However,challenges remain in long-term performance validation,standardization,and market integration.The review concludes that a combined approach involving innovative materials,computational tools,and sustainability assessment is essential for advancing marine infrastructure.Outlook recommendations include focused field studies,development of regulatory guidelines,and interdisciplinary collaboration to drive the practical adoption of eco-efficient materials in coastal and offshore construction.
文摘Copper nanoclusters(CuNCs)have gained prominence due to their remarkable color-tunable light emission and cost-effective,versatile solution-based synthesis.The use of various functional ligands in the synthesis of CuNCs enables the modulation of their emission wavelengths and enhances their environmental stability.These nanoclusters have found applications across diverse fields,including catalysis,sensing,bioimaging,and optoelectronics.This review offers a focused and up-to-date perspective by covering literature from the past decade(2015―2025)with an explicit emphasis on practical environmental matrices,including heavy metal ions,organic pollutants,pharmaceuticals,and other environmental contaminants.It systematically compares sensing mechanisms(e.g.,fluorescence quenching,turn-on responses,ratiometric and inner-filter effects)and provides tabulated limits of detection for key heavy metals,organic pollutants,and pharmaceuticals to facilitate direct benchmarking.Finally,the review highlights translational gaps for in-field deployment,such as matrix interferences,long-term stability of ligand-stabilized CuNCs,sample pre-treatment needs,and the absence of standardized validation protocols and proposes targeted research directions to bridge laboratory advances with real-world environmental monitoring.
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.
文摘Deep learning methods have been widely applied in motor imagery(MI)-based brain-computer interfaces(BCI)for decoding electroencephalogram(EEG)signals.High temporal resolution and asymmetric spatial activation are fundamental properties of EEG during MI processes.However,due to the limited receptive field of convolutional kernels,traditional convolutional neural networks(CNNs)often focus only on local features,and are insufficient to cover neural processes across different frequency bands and duration scales.This limitation hinders the effective characterization of rhythmic activity changes in MI-EEG signals over time.Additionally,MI-EEG signals exhibit significant asymmetric activation between the left and right hemispheres.Traditional spatial feature extraction methods overlook the interaction between global and local regions at the spatial scale of EEG signals,resulting in inadequate spatial representation and ultimately limiting decoding accuracy.To address these limitations,in this study,a novel deep learning network that integrates multi-modal temporal features with spatially asymmetric feature modeling was proposed.The network first extracts multi-modal temporal information from EEG data channels,and then captures global and hemispheric spatial features in the spatial dimension and fuses them through an advanced fusion layer.Global dependencies are captured using a self-attention module,and a multi-scale convolutional fusion module is introduced to explore the relationships between the two types of temporal features.The fused features are classified through a classification layer to accomplish motor imagery task classification.To mitigate the issue of limited sample size,a data augmentation strategy based on signal segmentation and recombination is designed.Experimental results on the BCI Competition IV-2a(bbic-IV-2a)and BCI Competition IV-2b(bbic-IV-2a)datasets demonstrated that the proposed method achieved superior accuracy in multi-class motor imagery classification compared with existing models.On the BCI-IV-2a dataset,it attained an average classification accuracy of 84.36%,while also showing strong performance on the binary classification BCI-IV-2b dataset.These outcomes validate the capability of the proposed network to enhance MI-EEG classification accuracy.
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.
文摘Plant health is increasingly threatened by environmental stressors,improper irrigation practices,and animal interference,leading to decreased growth and vitality.Current solutions often fail to integrate autonomous irrigation with effective deterrent mechanisms in a single system.This paper presents the Intelligent Sapling Shield,an innovative device designed to enhance plant protection and optimize growth conditions.The system features an autonomous soil moisture regulation mechanism to optimize water usage,reducing wastage and irrigation costs,while a vibrational deterrent system mitigates animal interference,preventing crop damage.Constructed from plastic mesh,the device ensures proper sunlight exposure,airflow,and shade,with an integrated waterproof LED strip for night-time illumination.Results demonstrate that the system maintains optimal soil moisture levels,reducing water consumption compared to traditional irrigation methods.Additionally,automated plant care minimizes labour requirements,ensuring consistent hydration and protection while enhancing crop resilience and yield.The design emphasizes affordability,portability,and ease of installation,making it suitable for both small-scale urban gardening and large-scale agricultural deployment.Its modular structure allows for customization depending on plant type and environmental conditions,further extending its applicability.By integrating irrigation efficiency,protective deterrence,and energy-efficient illumination,the Intelligent Sapling Shield creates a holistic solution that addresses multiple challenges faced in plant cultivation.By promoting cost-effective,resource-efficient,and sustainable agricultural practices,the Intelligent Sapling Shield contributes to urban greening initiatives and biodiversity conservation,supporting long-term ecological sustainability and offering significant potential for future smart farming innovations.
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.
基金funded by theDeanship of Research andGraduate Studies at King Khalid University through Large Research Project under grant number RGP2/417/46.
文摘A phase-aware cross-modal framework is presented that synthesizes UWF_FA from non-invasive UWF_RI for diabetic retinopathy(DR)stratification.A curated cohort of 1198 patients(2915 UWF_RI and 17,854 UWF_FA images)with strict registration quality supports training across three angiographic phases(initial,mid,final).The generator is based on a modified pix2pixHD with an added Gradient Variance Loss to better preserve microvasculature,and is evaluated using MAE,PSNR,SSIM,and MS-SSIM on held-out pairs.Quantitatively,the mid phase achieves the lowestMAE(98.76±42.67),while SSIM remains high across phases.Expert reviewshows substantial agreement(Cohen's κ=0.78–0.82)and Turing-stylemisclassification of 50%–70%of synthetic images as real,indicating strong perceptual realism.For downstream DR stratification,fusing multi-phase synthetic UWF_FA with UWF_RI in a Swin Transformer classifier yields significant gains over a UWF_RI-only baseline,with the full-phase setting(Set D)reaching AUC=0.910 and accuracy=0.829.These results support synthetic UWF_FA as a scalable,non-invasive complement to dye-based angiography that enhances screening accuracy while avoiding injection-related risks.
