New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage ...New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage integration remains challenging owing to the structural complexity,limited functionality,and low flexibility observed in most skyrmion-based devices.In this study,we designed a novel device architecture that integrates seven basic logic gates into a unified physical structure.Their operation can be enabled by physical mechanisms,such as spin-orbit torque,spin-transfer torque,skyrmion-edge repulsions,and skyrmion-skyrmion interactions.Furthermore,by incorporating voltage-controlled magnetic anisotropy,the device achieved multi-input capability and reconfigurability functionality.Ultralow power consumption(<1 fJ/bit per logic function)and extremely high logic density were achieved.Significantly,the compatibility of this nanotrack design with existing skyrmion racetrack memory paves the way for advanced in-memory computing in spintronic architectures.展开更多
Regulation of apoptosis represents a key parameter in all living organisms.In this paper,an input-induced logic-gated modular nanocalculator is designed to regulate cancer cell apoptosis by programmatically combining ...Regulation of apoptosis represents a key parameter in all living organisms.In this paper,an input-induced logic-gated modular nanocalculator is designed to regulate cancer cell apoptosis by programmatically combining and connecting logic gate modules with different functions.Via rational design of the various logic gate modules of the nanocalculator,different apoptosis related operations including cancer cell targeting,apoptosis induction,and apoptosis monitoring could be performed.Importantly,each of these logic gate modules could independently perform apoptosis related YES logic operations when ran separately.After combining each YES logic gate module into a logic circuit and connecting it to the GO scaffold to construct a logic-gated nanocalculator,the input-induced logic-gated modular nanocalculator could selectively enter cancer cells and control the drug release to logically apoptosis(output),by performing AND logic gate operations when inputs(nucleolin and H^(+)) were included at the same time.Moreover,evidence suggests that these efficient logical calculations proceed in cancer cell apoptosis regulation without the general limiations of lithography in nanotechnology.As such,this work provides a new vision for the construction of a logic-gated modular nanocalculator with logical calculation proficiency potentially useful in cancer therapy and the regulation of life.展开更多
Efficient torque allocation in over-actuated vehicles poses a central challenge in the domain of advanced vehicle control.These vehicles,featuring redundant actuators,provide an exceptional avenue for enhancing perfor...Efficient torque allocation in over-actuated vehicles poses a central challenge in the domain of advanced vehicle control.These vehicles,featuring redundant actuators,provide an exceptional avenue for enhancing performance,stability,and efficiency.This paper presents a pioneering tendency for torque allocation in the context of over-actuated vehicles,particularly inwheel motor(IWM)driven electric vehicles.We introduce a systematic methodology grounded in analytical modeling,allowing for the efficient reconciliation of multiple,often conflicting objectives.The explicit functions are analytically modeled to enhance stability and energy economy.Additionally,a fuzzy logic-based torque allocation strategy is developed and compared,along with other literature methods,with the analytical models.Simulations are conducted in a joint simulation between Simulink/MATLAB and SCANeR Studio vehicle dynamics simulator,followed by validation on a real-world dataset.Our findings elucidate the proficiency of the analytical models on vehicle performance,stability,computational efficiency,and energy consumption.展开更多
Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern co...Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern complex systems,while existing demarcation criteria like replicability and Popper’s falsificationism have practical limitations.Analyzing incompatibilities in complex systems,this paper proposes a revised framework:modified Hilbert axiomatic standards(clearly defined concepts,logical consistency,unrefuted axioms)and dynamic demarcation criteria.Abandoning unattainable traditional requirements of completeness and independence,it emphasizes conceptual clarity,openness,and progressiveness,offering an operational,self-consistent basis for judging scientificity.展开更多
Artificial intelligence(AI)based models have been used to predict the structural,optical,mechanical,and electrochemical properties of zinc oxide/graphene oxide nanocomposites.Machine learning(ML)models such as Artific...Artificial intelligence(AI)based models have been used to predict the structural,optical,mechanical,and electrochemical properties of zinc oxide/graphene oxide nanocomposites.Machine learning(ML)models such as Artificial Neural Networks(ANN),Support Vector Regression(SVR),Multilayer Perceptron(MLP),and hybrid,along with fuzzy logic tools,were applied to predict the different properties like wavelength at maximum intensity(444 nm),crystallite size(17.50 nm),and optical bandgap(2.85 eV).While some other properties,such as energy density,power density,and charge transfer resistance,were also predicted with the help of datasets of 1000(80:20).In general,the energy parameters were predicted more accurately by hybrid models.The hydrothermal method was used to synthesize graphene oxide(GO)and zinc oxide(ZnO)nanocomposites.The increased surface area,conductivity,and stability of graphene oxide in zinc oxide nanoparticles make the composite an ideal option for energy storage.X-ray diffraction(XRD)confirmed the crystallite size of 17.41 nm for the nanocomposite and the presence of GO(12.8○)peaks.The scanning electron microscope(SEM)showed anchored wrinkled GO sheets on zinc oxide with an average particle size of 2.93μm.Energy-dispersive X-ray spectroscopy(EDX)confirmed the elemental composition,and Fouriertransform infrared spectroscopy(FTIR)revealed the impact of GO on functional groups and electrochemical behavior.Photoluminescence(PL)wavelength of(439 nm)and band gap of(2.81 eV)show that the material is suitable for energy applications in nanocomposites.Smart nanocomposite materials with improved performance in energy storage and related applications were fabricated by combining synthesis,characterization,fuzzy logic,and machine learning in this work.展开更多
In this paper,we propose a fuzzy logic-based coded event-triggered control with self-adjustable prescribed performance(FL-CEC-SPP)to address the trade-off between control performance and communication efficiency in re...In this paper,we propose a fuzzy logic-based coded event-triggered control with self-adjustable prescribed performance(FL-CEC-SPP)to address the trade-off between control performance and communication efficiency in resource-constrained networked control systems.The method integrates a fuzzy-coded event-triggered controller into a coded control framework to dynamically adjust the triggering threshold,thereby reducing unnecessary transmissions while maintaining system stability.A self-adjustable prescribed performance constraint is also incorporated to ensure that the tracking error remains within predefined bounds under arbitrary initial conditions.Theoretical analyses and simulation comparisons show that the method proposed in this paper maintains good tracking performance and stability while reducing the communication burden,and has wide applications in resource-constrained network control systems.展开更多
This paper introduces a fuzzy C-means-based pooling layer for convolutional neural networks that explicitly models local uncertainty and ambiguity.Conventional pooling operations,such as max and average,apply rigid ag...This paper introduces a fuzzy C-means-based pooling layer for convolutional neural networks that explicitly models local uncertainty and ambiguity.Conventional pooling operations,such as max and average,apply rigid aggregation and often discard fine-grained boundary information.In contrast,our method computes soft membershipswithin each receptive field and aggregates cluster-wise responses throughmembership-weighted pooling,thereby preserving informative structure while reducing dimensionality.Being differentiable,the proposed layer operates as standard two-dimensional pooling.We evaluate our approach across various CNN backbones and open datasets,including CIFAR-10/100,STL-10,LFW,and ImageNette,and further probe small training set restrictions on MNIST and Fashion-MNIST.In these settings,the proposed pooling consistently improves accuracy and weighted F1 over conventional baselines,with particularly strong gains when training data are scarce.Even with less than 1%of the training set,ourmethodmaintains reliable performance,indicating improved sample efficiency and robustness to noisy or ambiguous local patterns.Overall,integrating soft memberships into the pooling operator provides a practical and generalizable inductive bias that enhances robustness and generalization in modern CNN pipelines.展开更多
In recent years,terbium radioisotopes have been investigated for their potential therapeutic and diagnostic applications in nuclear medicine.This study aimed to investigate the production of ^(152) Tb and ^(155) Tb by...In recent years,terbium radioisotopes have been investigated for their potential therapeutic and diagnostic applications in nuclear medicine.This study aimed to investigate the production of ^(152) Tb and ^(155) Tb by alpha-induced reactions in detail,with a specific focus on determining the optimum production parameters and testing existing nuclear models.Given the limited number of experiments conducted on reactions related to terbium isotope production,it is necessary to perform theoretical calculations of cross sections over a wide energy range to gain a detailed understanding of terbium isotope production.To achieve this objective,the cross sections of the ^(151)Eu(α,n)^(154) Tb reactions were calculated up to 60 MeV using the TALYS computer code with 432 different combinations of optical model parameters,level density,and strength function models.The theoretical reaction cross-section results were compared with the experimental results in the literature.The best input parameters were determined using the Threshold Logic Unit method,and these parameters were used in all isotope production calculations.Once the optimal model combination was determined,the total activity production and isotopic fraction of ^(152) Tb and ^(155) Tb isotopes were calculated in detail for beam energies of 17–50 MeV,different irradiation times,and varying ^(151) Eu and ^(153) Eu target thicknesses.展开更多
In recent years,acoustic logic gates has attracted growing interest in acoustics due to their promising applications in acoustic communication and signal processing.For practical implementation,these logic gates must ...In recent years,acoustic logic gates has attracted growing interest in acoustics due to their promising applications in acoustic communication and signal processing.For practical implementation,these logic gates must operate over a certain bandwidth to ensure reliable performance.However,current experimental realizations have predominantly been confined to single-frequency or narrowband operation,leaving their broadband capabilities largely unverified.To address this gap,we present both numerical and experimental demonstrations of three basic acoustic logic gates(OR,NOT,and AND)using a phased unit cell composed of a central channel flanked by two arrays of semicircular cavities.By leveraging phase modulation of the unit cells and linear interference of sound,we achieve these logic operations with a uniform threshold of I_(t)=0.25.Remarkably,the measured fractional bandwidths(bandwidth relative to center frequency)reach approximately 111.5%(OR),37.2%(NOT),and 48.5%(AND),demonstrating ultra-broadband functionality.The proposed logic gates combine exceptional bandwidth with structural simplicity,offering significant potential for applications in acoustic computing,information processing,and integrated acoustic systems.展开更多
This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing th...This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.展开更多
Multi-valued quantum adder circuits,based on multi-valued logic,are significant components in numerous quantum algorithms.Their low-cost implementations can enhance the efficiency of these algorithms.In this paper,inn...Multi-valued quantum adder circuits,based on multi-valued logic,are significant components in numerous quantum algorithms.Their low-cost implementations can enhance the efficiency of these algorithms.In this paper,innovative universal architectures for d(d>3)-level quantum half-adder,full-adder,parallel adder,and parallel adder/subtractor circuits are designed using d-level 1-qudit(quantum digit)and M-S gates.To demonstrate the effectiveness of these architectures,quaternary adder circuits derived from them are displayed and compared with several existing counterparts.Judging by the results,these circuits exhibit reductions in quantum cost(QC),hardware complexity(HC),number of constant inputs(NCIs),and number of garbage outputs(NGOs).展开更多
This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA f...This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA framework integrates security by design principles, micro-segmentation, and Island Mode Operation (IMO) to enhance cyber resilience and ensure continuous, secure operations. The methodology deploys a Forward-Thinking Architecture Strategy (FTAS) algorithm, which utilises an industrial Intrusion Detection System (IDS) implemented with Python’s Network Intrusion Detection System (NIDS) library. The FTAS algorithm successfully identified and responded to cyber-attacks, ensuring minimal system disruption. ISERA has been validated through comprehensive testing scenarios simulating Denial of Service (DoS) attacks and malware intrusions, at both the IT and OT layers where it successfully mitigates the impact of malicious activity. Results demonstrate ISERA’s efficacy in real-time threat detection, containment, and incident response, thus ensuring the integrity and reliability of critical infrastructure systems. ISERA’s decentralised approach contributes to global net zero goals by optimising resource use and minimising environmental impact. By adopting a decentralised control architecture and leveraging virtualisation, ISERA significantly enhances the cyber resilience and sustainability of critical infrastructure systems. This approach not only strengthens defences against evolving cyber threats but also optimises resource allocation, reducing the system’s carbon footprint. As a result, ISERA ensures the uninterrupted operation of essential services while contributing to broader net zero goals.展开更多
In industrial control systems,such as power transmission facilities and water treatment plants,Programmable Logic Controllers(PLCs)can work consistently and stably over long periods if there are no faults.Black-box id...In industrial control systems,such as power transmission facilities and water treatment plants,Programmable Logic Controllers(PLCs)can work consistently and stably over long periods if there are no faults.Black-box identification aims to automatically construct Petri net models with the help of I/O signals from PLC devices only.The main challenge is how to convert the infinitely long PLC signals into an event sequence,which is the foundation for subsequent modeling.The current algorithms are confronted with a number of challenges,including an exponential increase in the number of transitions,high time complexity,and susceptibility to noisy signals.To solve these problems,this paper proposes a new method for converting PLC signals into a transition sequence.The method is based on the principles of Boolean absorption law,which filters out noise information in the I/O signals.Then firing functions representing input–output causality are constructed from the filtered signals.Finally,the original signal sequence is traversed to generate a transition sequence.The experimental results show that these methods can rapidly identify a transition sequence.Compared to traditional methods,the proposed algorithms have polynomial time complexity.展开更多
Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are fac...Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).展开更多
This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Ham...This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.展开更多
This paper investigates control synthesis for motion planning under conditions of uncertainty,specifically in robot motion and environmental properties,which are modeled using a probabilistic labeled Markov decision p...This paper investigates control synthesis for motion planning under conditions of uncertainty,specifically in robot motion and environmental properties,which are modeled using a probabilistic labeled Markov decision process(PL-MDP).To address this,a model-free reinforcement learning(RL)approach is designed to produce a finite-memory control policy that meets complex tasks specified by linear temporal logic(LTL)formulas.Recognizing the presence of uncertainties and potentially conflicting objectives,this study centers on addressing infeasible LTL specifications.A relaxed LTL constraint enables the agent to adapt its motion plan,allowing for partial satisfaction by accounting for necessary task violations.Additionally,a new automaton structure is introduced to increase the density of accepting rewards,facilitating deterministic policy outcomes.The proposed RL framework is rigorously analyzed and prioritizes two key objectives:(1)satisfying the acceptance condition of the relaxed product MDP,and(2)minimizing long-term violation costs.Simulation and experimental results are presented to demonstrate the framework’s effectiveness and robustness.展开更多
With the increasing integration of emerging source-load types such as distributed photovoltaics,electric vehicles,and energy storage into distribution networks,the operational characteristics of these networks have ev...With the increasing integration of emerging source-load types such as distributed photovoltaics,electric vehicles,and energy storage into distribution networks,the operational characteristics of these networks have evolved from traditional single-load centers to complex multi-source,multi-load systems.This transition not only increases the difficulty of effectively classifying distribution networks due to their heightened complexity but also renders traditional energy management approaches-primarily focused on economic objectives-insufficient to meet the growing demands for flexible scheduling and dynamic response.To address these challenges,this paper proposes an adaptive multi-objective energy management strategy that accounts for the distinct operational requirements of distribution networks with a high penetration of new-type source-loads.The goal is to establish a comprehensive energy management framework that optimally balances energy efficiency,carbon reduction,and economic performance in modern distribution networks.To enhance classification accuracy,the strategy constructs amulti-dimensional scenario classification model that integrates environmental and climatic factors by analyzing the operational characteristics of new-type distribution networks and incorporating expert knowledge.An improved split-coupling K-means preclustering algorithm is employed to classify distribution networks effectively.Based on the classification results,fuzzy logic control is then utilized to dynamically optimize the weighting of each objective,allowing for an adaptive adjustment of priorities to achieve a flexible and responsivemulti-objective energy management strategy.The effectiveness of the proposed approach is validated through practical case studies.Simulation results indicate that the proposed method improves classification accuracy by 18.18%compared to traditional classification methods and enhances energy savings and carbon reduction by 4.34%and 20.94%,respectively,compared to the fixed-weight strategy.展开更多
Mining-induced surface subsidence often causes buried oil–gas pipelines deform,and the potential leakage risk can pose a safety hazard.In this work,a novel model for predicting the influence range of potential leakag...Mining-induced surface subsidence often causes buried oil–gas pipelines deform,and the potential leakage risk can pose a safety hazard.In this work,a novel model for predicting the influence range of potential leakage risk from deformed pipelines was developed.First,the pipe instability deformation limit was corrected by the multi-indicator optimized screening method proposed in this paper.Then,the leakage risk influence radius of the pipe segment was defined by the failure probability.Next,the pipe segment'deformation and strength were assessed sequentially using the ratio and point methods.Combining the fuzzy logic inference method with the assessment results as input variable,and the failure probabilities as output variable,a quantitative assessment model for the pipeline leakage risk was established.Accordingly,the risk range and level of adjacent coal mines and surfaces were divided,and the verification method and forward countermeasures were proposed.Finally,an engineering case was used for analysis and verification.The results show that the gas pipeline with 650 m length was divided into seven regions and four risk levels.The influence radius of the risk levels from low to high were 12.75 m,25.5 m,38.25 m,and 51 m,and the influence widths on the surface were 25.28 m,49.84 m,76.34 m,and 101.84 m,correspondingly.The nearest distances from the risk area to the mine and village were 212.65 m and 329.08 m.The assessment of potentially threatened areas is significantly simplified by the assessment model combined with pipeline deformation,which has great practical importance for risk management and disaster prevention in adjacent space.展开更多
基金support from the National Natural Science Foundation of China (Grant No.12474101)support from the National Natural Science Foundation of China (Grant Nos.52272202 and W2421027)support from the National Natural Science Foundation of China (Grant No.52501307)。
文摘New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage integration remains challenging owing to the structural complexity,limited functionality,and low flexibility observed in most skyrmion-based devices.In this study,we designed a novel device architecture that integrates seven basic logic gates into a unified physical structure.Their operation can be enabled by physical mechanisms,such as spin-orbit torque,spin-transfer torque,skyrmion-edge repulsions,and skyrmion-skyrmion interactions.Furthermore,by incorporating voltage-controlled magnetic anisotropy,the device achieved multi-input capability and reconfigurability functionality.Ultralow power consumption(<1 fJ/bit per logic function)and extremely high logic density were achieved.Significantly,the compatibility of this nanotrack design with existing skyrmion racetrack memory paves the way for advanced in-memory computing in spintronic architectures.
基金financially supported by the National Natural Science Foundation of China (NSFC,Nos.22134005 and 22074124)Chongqing Talents Program for Outstanding Scientists (No.cstc2021ycjh-bgzxm0178)+1 种基金Natural Science Foundation of Chongqing (No.CSTB2022NSCQ-MSX0521)the Chongqing Graduate Student Scientific Research Innovation Project (No.CYB21119)。
文摘Regulation of apoptosis represents a key parameter in all living organisms.In this paper,an input-induced logic-gated modular nanocalculator is designed to regulate cancer cell apoptosis by programmatically combining and connecting logic gate modules with different functions.Via rational design of the various logic gate modules of the nanocalculator,different apoptosis related operations including cancer cell targeting,apoptosis induction,and apoptosis monitoring could be performed.Importantly,each of these logic gate modules could independently perform apoptosis related YES logic operations when ran separately.After combining each YES logic gate module into a logic circuit and connecting it to the GO scaffold to construct a logic-gated nanocalculator,the input-induced logic-gated modular nanocalculator could selectively enter cancer cells and control the drug release to logically apoptosis(output),by performing AND logic gate operations when inputs(nucleolin and H^(+)) were included at the same time.Moreover,evidence suggests that these efficient logical calculations proceed in cancer cell apoptosis regulation without the general limiations of lithography in nanotechnology.As such,this work provides a new vision for the construction of a logic-gated modular nanocalculator with logical calculation proficiency potentially useful in cancer therapy and the regulation of life.
基金carried out within the framework of the V3EA Project“Electric,Energy Efficient,and Autonomous Vehicle”(2021-2025)supported by the Research National Agency(ANR)of the French Government。
文摘Efficient torque allocation in over-actuated vehicles poses a central challenge in the domain of advanced vehicle control.These vehicles,featuring redundant actuators,provide an exceptional avenue for enhancing performance,stability,and efficiency.This paper presents a pioneering tendency for torque allocation in the context of over-actuated vehicles,particularly inwheel motor(IWM)driven electric vehicles.We introduce a systematic methodology grounded in analytical modeling,allowing for the efficient reconciliation of multiple,often conflicting objectives.The explicit functions are analytically modeled to enhance stability and energy economy.Additionally,a fuzzy logic-based torque allocation strategy is developed and compared,along with other literature methods,with the analytical models.Simulations are conducted in a joint simulation between Simulink/MATLAB and SCANeR Studio vehicle dynamics simulator,followed by validation on a real-world dataset.Our findings elucidate the proficiency of the analytical models on vehicle performance,stability,computational efficiency,and energy consumption.
基金supported by the start-up funding from Westlake University under Grant Number 041030150118 and the scientific research project of Westlake University“Theoretical Research and Demonstration Application of Complex Systems and Deep-Sea Technology(Phase I)”under Grant Number WU2025A006.
文摘Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern complex systems,while existing demarcation criteria like replicability and Popper’s falsificationism have practical limitations.Analyzing incompatibilities in complex systems,this paper proposes a revised framework:modified Hilbert axiomatic standards(clearly defined concepts,logical consistency,unrefuted axioms)and dynamic demarcation criteria.Abandoning unattainable traditional requirements of completeness and independence,it emphasizes conceptual clarity,openness,and progressiveness,offering an operational,self-consistent basis for judging scientificity.
基金extend their gratitude to the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia,for funding the publication of this work under the Ambitious Researcher program(Project No.KFU253806).
文摘Artificial intelligence(AI)based models have been used to predict the structural,optical,mechanical,and electrochemical properties of zinc oxide/graphene oxide nanocomposites.Machine learning(ML)models such as Artificial Neural Networks(ANN),Support Vector Regression(SVR),Multilayer Perceptron(MLP),and hybrid,along with fuzzy logic tools,were applied to predict the different properties like wavelength at maximum intensity(444 nm),crystallite size(17.50 nm),and optical bandgap(2.85 eV).While some other properties,such as energy density,power density,and charge transfer resistance,were also predicted with the help of datasets of 1000(80:20).In general,the energy parameters were predicted more accurately by hybrid models.The hydrothermal method was used to synthesize graphene oxide(GO)and zinc oxide(ZnO)nanocomposites.The increased surface area,conductivity,and stability of graphene oxide in zinc oxide nanoparticles make the composite an ideal option for energy storage.X-ray diffraction(XRD)confirmed the crystallite size of 17.41 nm for the nanocomposite and the presence of GO(12.8○)peaks.The scanning electron microscope(SEM)showed anchored wrinkled GO sheets on zinc oxide with an average particle size of 2.93μm.Energy-dispersive X-ray spectroscopy(EDX)confirmed the elemental composition,and Fouriertransform infrared spectroscopy(FTIR)revealed the impact of GO on functional groups and electrochemical behavior.Photoluminescence(PL)wavelength of(439 nm)and band gap of(2.81 eV)show that the material is suitable for energy applications in nanocomposites.Smart nanocomposite materials with improved performance in energy storage and related applications were fabricated by combining synthesis,characterization,fuzzy logic,and machine learning in this work.
基金supported by Singapore RIE2025 Manufacturing,Trade and Connectivity Industry Alignment Fund-Pre-Positioning(IAF-PP)under Grant M24N2a0039 through WP2-Intelligent Switching Controlthe National Research Foundation Singapore under its AI Singapore Programme under Grant AISG4-GC-2023-007-1B.
文摘In this paper,we propose a fuzzy logic-based coded event-triggered control with self-adjustable prescribed performance(FL-CEC-SPP)to address the trade-off between control performance and communication efficiency in resource-constrained networked control systems.The method integrates a fuzzy-coded event-triggered controller into a coded control framework to dynamically adjust the triggering threshold,thereby reducing unnecessary transmissions while maintaining system stability.A self-adjustable prescribed performance constraint is also incorporated to ensure that the tracking error remains within predefined bounds under arbitrary initial conditions.Theoretical analyses and simulation comparisons show that the method proposed in this paper maintains good tracking performance and stability while reducing the communication burden,and has wide applications in resource-constrained network control systems.
文摘This paper introduces a fuzzy C-means-based pooling layer for convolutional neural networks that explicitly models local uncertainty and ambiguity.Conventional pooling operations,such as max and average,apply rigid aggregation and often discard fine-grained boundary information.In contrast,our method computes soft membershipswithin each receptive field and aggregates cluster-wise responses throughmembership-weighted pooling,thereby preserving informative structure while reducing dimensionality.Being differentiable,the proposed layer operates as standard two-dimensional pooling.We evaluate our approach across various CNN backbones and open datasets,including CIFAR-10/100,STL-10,LFW,and ImageNette,and further probe small training set restrictions on MNIST and Fashion-MNIST.In these settings,the proposed pooling consistently improves accuracy and weighted F1 over conventional baselines,with particularly strong gains when training data are scarce.Even with less than 1%of the training set,ourmethodmaintains reliable performance,indicating improved sample efficiency and robustness to noisy or ambiguous local patterns.Overall,integrating soft memberships into the pooling operator provides a practical and generalizable inductive bias that enhances robustness and generalization in modern CNN pipelines.
文摘In recent years,terbium radioisotopes have been investigated for their potential therapeutic and diagnostic applications in nuclear medicine.This study aimed to investigate the production of ^(152) Tb and ^(155) Tb by alpha-induced reactions in detail,with a specific focus on determining the optimum production parameters and testing existing nuclear models.Given the limited number of experiments conducted on reactions related to terbium isotope production,it is necessary to perform theoretical calculations of cross sections over a wide energy range to gain a detailed understanding of terbium isotope production.To achieve this objective,the cross sections of the ^(151)Eu(α,n)^(154) Tb reactions were calculated up to 60 MeV using the TALYS computer code with 432 different combinations of optical model parameters,level density,and strength function models.The theoretical reaction cross-section results were compared with the experimental results in the literature.The best input parameters were determined using the Threshold Logic Unit method,and these parameters were used in all isotope production calculations.Once the optimal model combination was determined,the total activity production and isotopic fraction of ^(152) Tb and ^(155) Tb isotopes were calculated in detail for beam energies of 17–50 MeV,different irradiation times,and varying ^(151) Eu and ^(153) Eu target thicknesses.
基金Project supported by the National Natural Science Foundation of China(Grant No.12174159)。
文摘In recent years,acoustic logic gates has attracted growing interest in acoustics due to their promising applications in acoustic communication and signal processing.For practical implementation,these logic gates must operate over a certain bandwidth to ensure reliable performance.However,current experimental realizations have predominantly been confined to single-frequency or narrowband operation,leaving their broadband capabilities largely unverified.To address this gap,we present both numerical and experimental demonstrations of three basic acoustic logic gates(OR,NOT,and AND)using a phased unit cell composed of a central channel flanked by two arrays of semicircular cavities.By leveraging phase modulation of the unit cells and linear interference of sound,we achieve these logic operations with a uniform threshold of I_(t)=0.25.Remarkably,the measured fractional bandwidths(bandwidth relative to center frequency)reach approximately 111.5%(OR),37.2%(NOT),and 48.5%(AND),demonstrating ultra-broadband functionality.The proposed logic gates combine exceptional bandwidth with structural simplicity,offering significant potential for applications in acoustic computing,information processing,and integrated acoustic systems.
基金supported in part by the National Natural Science Foundation of China under Grants 62073124 and U1804150.
文摘This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.
基金supported by the Natural Science Foundation of Sichuan Province(No.25QNJJ4066)Academic Degree and Post graduate Education Reform Project of Sichuan Province(Grants:YJGXM24-C017)。
文摘Multi-valued quantum adder circuits,based on multi-valued logic,are significant components in numerous quantum algorithms.Their low-cost implementations can enhance the efficiency of these algorithms.In this paper,innovative universal architectures for d(d>3)-level quantum half-adder,full-adder,parallel adder,and parallel adder/subtractor circuits are designed using d-level 1-qudit(quantum digit)and M-S gates.To demonstrate the effectiveness of these architectures,quaternary adder circuits derived from them are displayed and compared with several existing counterparts.Judging by the results,these circuits exhibit reductions in quantum cost(QC),hardware complexity(HC),number of constant inputs(NCIs),and number of garbage outputs(NGOs).
基金funded by the Office of Gas and Electricity Markets(Ofgem)and supported by De Montfort University(DMU)and Nottingham Trent University(NTU),UK.
文摘This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA framework integrates security by design principles, micro-segmentation, and Island Mode Operation (IMO) to enhance cyber resilience and ensure continuous, secure operations. The methodology deploys a Forward-Thinking Architecture Strategy (FTAS) algorithm, which utilises an industrial Intrusion Detection System (IDS) implemented with Python’s Network Intrusion Detection System (NIDS) library. The FTAS algorithm successfully identified and responded to cyber-attacks, ensuring minimal system disruption. ISERA has been validated through comprehensive testing scenarios simulating Denial of Service (DoS) attacks and malware intrusions, at both the IT and OT layers where it successfully mitigates the impact of malicious activity. Results demonstrate ISERA’s efficacy in real-time threat detection, containment, and incident response, thus ensuring the integrity and reliability of critical infrastructure systems. ISERA’s decentralised approach contributes to global net zero goals by optimising resource use and minimising environmental impact. By adopting a decentralised control architecture and leveraging virtualisation, ISERA significantly enhances the cyber resilience and sustainability of critical infrastructure systems. This approach not only strengthens defences against evolving cyber threats but also optimises resource allocation, reducing the system’s carbon footprint. As a result, ISERA ensures the uninterrupted operation of essential services while contributing to broader net zero goals.
基金supported by the Science and Technology Planning Project of Fujian Province,China,under Grant No.2024H0014(2024H01010100).
文摘In industrial control systems,such as power transmission facilities and water treatment plants,Programmable Logic Controllers(PLCs)can work consistently and stably over long periods if there are no faults.Black-box identification aims to automatically construct Petri net models with the help of I/O signals from PLC devices only.The main challenge is how to convert the infinitely long PLC signals into an event sequence,which is the foundation for subsequent modeling.The current algorithms are confronted with a number of challenges,including an exponential increase in the number of transitions,high time complexity,and susceptibility to noisy signals.To solve these problems,this paper proposes a new method for converting PLC signals into a transition sequence.The method is based on the principles of Boolean absorption law,which filters out noise information in the I/O signals.Then firing functions representing input–output causality are constructed from the filtered signals.Finally,the original signal sequence is traversed to generate a transition sequence.The experimental results show that these methods can rapidly identify a transition sequence.Compared to traditional methods,the proposed algorithms have polynomial time complexity.
文摘Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).
基金financially supported by Sichuan Science and Technology Program(Grant No.2023NSFSC1980).
文摘This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.
基金supported by the National Natural Science Foundation of China under Grant 62173314.
文摘This paper investigates control synthesis for motion planning under conditions of uncertainty,specifically in robot motion and environmental properties,which are modeled using a probabilistic labeled Markov decision process(PL-MDP).To address this,a model-free reinforcement learning(RL)approach is designed to produce a finite-memory control policy that meets complex tasks specified by linear temporal logic(LTL)formulas.Recognizing the presence of uncertainties and potentially conflicting objectives,this study centers on addressing infeasible LTL specifications.A relaxed LTL constraint enables the agent to adapt its motion plan,allowing for partial satisfaction by accounting for necessary task violations.Additionally,a new automaton structure is introduced to increase the density of accepting rewards,facilitating deterministic policy outcomes.The proposed RL framework is rigorously analyzed and prioritizes two key objectives:(1)satisfying the acceptance condition of the relaxed product MDP,and(2)minimizing long-term violation costs.Simulation and experimental results are presented to demonstrate the framework’s effectiveness and robustness.
基金supported by the Science and Technology Project of the Headquarters of the State Grid Corporation(project code:5400-202323233A-1-1-ZN).
文摘With the increasing integration of emerging source-load types such as distributed photovoltaics,electric vehicles,and energy storage into distribution networks,the operational characteristics of these networks have evolved from traditional single-load centers to complex multi-source,multi-load systems.This transition not only increases the difficulty of effectively classifying distribution networks due to their heightened complexity but also renders traditional energy management approaches-primarily focused on economic objectives-insufficient to meet the growing demands for flexible scheduling and dynamic response.To address these challenges,this paper proposes an adaptive multi-objective energy management strategy that accounts for the distinct operational requirements of distribution networks with a high penetration of new-type source-loads.The goal is to establish a comprehensive energy management framework that optimally balances energy efficiency,carbon reduction,and economic performance in modern distribution networks.To enhance classification accuracy,the strategy constructs amulti-dimensional scenario classification model that integrates environmental and climatic factors by analyzing the operational characteristics of new-type distribution networks and incorporating expert knowledge.An improved split-coupling K-means preclustering algorithm is employed to classify distribution networks effectively.Based on the classification results,fuzzy logic control is then utilized to dynamically optimize the weighting of each objective,allowing for an adaptive adjustment of priorities to achieve a flexible and responsivemulti-objective energy management strategy.The effectiveness of the proposed approach is validated through practical case studies.Simulation results indicate that the proposed method improves classification accuracy by 18.18%compared to traditional classification methods and enhances energy savings and carbon reduction by 4.34%and 20.94%,respectively,compared to the fixed-weight strategy.
基金funded by the National Natural Science Foundation of China(52225402 and 51874312)the Major scientific and technological innovation project of Shandong Province(2019SDZY01 and 2019SDZY02).
文摘Mining-induced surface subsidence often causes buried oil–gas pipelines deform,and the potential leakage risk can pose a safety hazard.In this work,a novel model for predicting the influence range of potential leakage risk from deformed pipelines was developed.First,the pipe instability deformation limit was corrected by the multi-indicator optimized screening method proposed in this paper.Then,the leakage risk influence radius of the pipe segment was defined by the failure probability.Next,the pipe segment'deformation and strength were assessed sequentially using the ratio and point methods.Combining the fuzzy logic inference method with the assessment results as input variable,and the failure probabilities as output variable,a quantitative assessment model for the pipeline leakage risk was established.Accordingly,the risk range and level of adjacent coal mines and surfaces were divided,and the verification method and forward countermeasures were proposed.Finally,an engineering case was used for analysis and verification.The results show that the gas pipeline with 650 m length was divided into seven regions and four risk levels.The influence radius of the risk levels from low to high were 12.75 m,25.5 m,38.25 m,and 51 m,and the influence widths on the surface were 25.28 m,49.84 m,76.34 m,and 101.84 m,correspondingly.The nearest distances from the risk area to the mine and village were 212.65 m and 329.08 m.The assessment of potentially threatened areas is significantly simplified by the assessment model combined with pipeline deformation,which has great practical importance for risk management and disaster prevention in adjacent space.
