A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the robot.The kinematics controller...A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the robot.The kinematics controller generates desired linear and angular velocities for follower robots,which make the configuration of follower robots coverage to the desired.The fuzzy logic controller takes dynamics of the leader and followers into consideration,which is built upon Mamdani fuzzy model.The force and torque acting on robots are described as linguistic variables and also 25 if-then rules are designed.In addition,the fuzzy logic controller adopts the Centroid of Area method as defuzzification strategy and makes robots’actual velocities converge to the expected which is generated by the kinematics controller.The innovation of the kinematics and fuzzy logic combined formation controller presented in the paper is that the perfect velocity tracking assumption is removed and realtime performance of the system is improved.Compared with traditional torque-computed controller,the velocity error convergence time in case of the proposed method is shorter than traditional torque-computed controller.The simulation results validate that the proposed controller can drive robot members to form the desired formation and formation tracking errors which can coverage to a neighborhood of the origin.Additionally,the simulations also show that the proposed method has better velocity convergence performance than traditional torque-computed method.展开更多
The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method...To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method for a class of parallel platforms with 3-RE structure after locking the actuated joints is proposed in this paper.Given that the angle between specific joint axes of limbs remains constant,a set of geometric constraints for the forward kinematics of parallel mechanisms(PM)are determined.After translating unit direction vectors of these joint axes to the common starting point,the geometric constraints of the angle between the vectors are transformed into the distances between the endpoints of the vectors,making them easier to handle.Under the framework of CGA,the positions of key points that determine the position and orientation of the moving platform can be intuitively determined by the intersection,division,and duality of basic geometric entities.By employing the tangent half-angle substitution,the forward kinematic analysis of the parallel mechanisms leads to a high-order univariate polynomial equation without the need for any complex algebraic elimination operations.After solving this equation and back substitution,the position and pose of the MP can be obtained indirectly.A numerical case is utilized to confirm the effectiveness of the proposed method.展开更多
Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfor...Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfortunately their inverse kinematics have not yet been resolved.This paper discovers that the unknown kinematic parameters of middle platform are responsible for the unresolvable of inverse kinematics,meanwhile the unknown kinematic parameters of middle platform also have huge coupling relationships.Therefore,to break through this challenges,the huge coupling relationships are decoupled layer by layer,the kinematic parameters of middle platform are solved by combining Sylvester's elimination method,and the inverse displacements of 2(3RPS)and 2(3SPR)S-PMs are obtained subsequently.This paper not only solves the inverse kinematics of classical 2(3RPS)and 2(3SPR)S-PMs,but also reveals the essence of the inverse kinematics of general(3-DOF)+(3-DOF)6-DOF S-PMs and proposes a corresponding solution.展开更多
Presents a fast and effective method proposed by combining the fuzzy C means (FCM) and the fuzzy neural network for solving robot inverse kinematics, and its successful application to the robot inverse kinematics and ...Presents a fast and effective method proposed by combining the fuzzy C means (FCM) and the fuzzy neural network for solving robot inverse kinematics, and its successful application to the robot inverse kinematics and concludes from simulation results that this new method not only has high efficiency and accuracy, but also good generalization, and it also overcomes the "dimension disaster" of fuzzy set in a fuzzy neural network fairly well.展开更多
Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to ...Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to avoid collision and improve the flexibility of the robots,this study proposes a reconfigurable cable-driven parallel robot(RCDPR)having characteristics of large load-to-weight ratio,easy modularity and variable stiffness.Adjustable brackets are connected to the moving platform to adjust the position of the pull-out point with the movement of the end-effector.In addition,a variable stiffness actuator(VSA)accompanied by finite element analysis is designed to optimize the cable tension to adapt different task requirements.Firstly,a new idea of reconfiguration is given,and an inverse kinematic model is established using the vector closure principle to derive its inverse kinematic expressions focusing on one of the configurations.Second,the VSA is attached to each cable to achieve stiffness adjustment,and the system stiffness is derived in detail.Finally,the rationality and accuracy of the robot are verified through numerical analysis,providing a reference for subsequent trajectory planning with implications.展开更多
Rockfall kinematic characteristics exhibit significant randomness and are influenced by factors such as rock mass properties,slope morphology,impact angle,and slope materials.Accurately determining the key parameters ...Rockfall kinematic characteristics exhibit significant randomness and are influenced by factors such as rock mass properties,slope morphology,impact angle,and slope materials.Accurately determining the key parameters of rockfall movement is critical for understanding motion patterns and effectively preventing and controlling rockfall hazards.In this study,a monitoring system consisting of selfdeveloped inertial navigation equipment,high-speed cameras,and an unmanned aerial vehicle was used to conduct onsite motion tests involving four differently shaped rock specimens on three types of slopes(bedrock,detritus,and clast bedding).The selfdeveloped inertial navigation system integrated a highdynamic-range accelerometer(±400 g)and a shockresistant gyroscope(±4000°/s),capable of robustly collecting data during the test.The data collected from these tests were processed to extract key kinematic parameters such as velocity,trajectory,restitution coefficients,and friction coefficients.The test results demonstrated that the inertial navigation system accurately recorded the acceleration and angular velocity of the rocks during motion,with these measurements closely aligning with the field data.The normal and tangential restitution coefficients were found to be influenced primarily by the slope material and impact angle,with higher normal restitution coefficients observed for low-angle impacts.The normal restitution coefficients ranged from 0.35 to 0.86,whereas the tangential restitution coefficients ranged from 0.46 to 0.91,depending on the slope materials.Additionally,the sliding friction coefficient was calculated to be between 0.66 and 0.78,whereas the rolling friction coefficient for the slab-shaped specimen was determined to be 0.53.These findings provide valuable data for improving the accuracy of rockfall trajectory predictions and the design of protective structures.展开更多
The human thumb plays a crucial role in performing coordinated hand movements for precise tool use.However,quantifying and interpreting the kinematics and couplings of the six degrees of freedom(6DOF)between the inter...The human thumb plays a crucial role in performing coordinated hand movements for precise tool use.However,quantifying and interpreting the kinematics and couplings of the six degrees of freedom(6DOF)between the interphalangeal(IP)and metacarpophalangeal(MCP)joints during hand functional tasks remains challenging.To address this issue,advanced dynamic biplane radiography combined with a model-based 2D–3D tracking technique was employed to decode the inherent kinematics of the thumb IP and MCP joints during key pinch,tip pinch,palmar pinch and wide grasp.The results indicate that the functional tasks of the thumb are intricately modulated by the 3D rotational and translational motions of the IP and MCP joints.The IP joint exhibited the greatest flexion/extension range of motion during the tip pinch task(67.2°±8.4°),compared to smaller ranges in key pinch(27.6°±3.8°)and wide grasp(16.2°±7.1°)tasks.In the wide grasp task,the IP joint showed more movement in the radius/ulna direction(3.4±1.2 mm)compared to tip pinch(3.1±0.8 mm).Furthermore,the kinematic data of the IP joint challenge the traditional notion that the IP joint normally acts as a hinge mechanism.The results of this study help to elucidate the kinematics of human thumb IP and MCP joints and may provide new inspiration for the design of high-performance bionic hands or thumb prosthetics as well as for evaluating the outcomes of thumb therapeutic interventions and surgical procedures.展开更多
Parallel mechanisms with fewer degrees of freedom that incorporate two or more SPR limbs have been widely adopted in industrial applications in recent years.However,notable theoretical gaps persist,particularly in the...Parallel mechanisms with fewer degrees of freedom that incorporate two or more SPR limbs have been widely adopted in industrial applications in recent years.However,notable theoretical gaps persist,particularly in the field of analytical solutions for forward kinematics.To address this,this paper proposes an innovative forward kinematics analysis method based on Conformal Geometric Algebra(CGA)for complex hybrid mechanisms formed by serial concatenation of such parallel mechanisms.The method efficiently represents geometric elements and their operational relationships by defining appropriate unknown parameters.It constructs fundamental geometric objects such as spheres and planes,derives vertex expressions through intersection and dual operations,and establishes univariate high-order equations via inner product operations,ultimately obtaining complete analytical solutions for the forward kinematics of hybrid mechanisms.Using the(2-SPR+RPS)+(3-SPR)serial-parallel hybrid mechanism as a validation case,three configuration tests implemented in Mathematica demonstrate that:for each configuration,the upper 3-SPR mechanism yields 15 mathematical solutions,while the lower 2-SPR+RPS mechanism yields 4 mathematical solutions.After geometric constraint filtering,a unique physically valid solution is obtained for each mechanism.SolidWorks simulations further verify the correctness and reliability of the model.This research provides a reliable analytical method for forward kinematics of hybrid mechanisms,holding significant implications for advancing their applications in high-precision scenarios.展开更多
The Ross Sea basins,shaped by Late Cretaceous and Cenozoic extension within the crust of the Ross Sea,represent key regions for understanding continental rifting processes.However,the dynamic mechanisms driving the tr...The Ross Sea basins,shaped by Late Cretaceous and Cenozoic extension within the crust of the Ross Sea,represent key regions for understanding continental rifting processes.However,the dynamic mechanisms driving the transition from diffuse extension to focused extension in these basins remain poorly understood.Here,we provide a comprehensive model of crustal extension in the Ross Sea basins,detailing the kinematic and dynamic evolution from 100 Ma to the present on the basis of published finite rotation poles.Our model illuminates the complex relative motions between the West Antarctic and East Antarctic Plates and quantifies the crustal strain rates associated with their relative movements.We show that West Antarctica began to move away slowly from the East Antarctic and rotated clockwise at approximately 53 Ma,and the motion progressively decreased until it ceased at approximately 11 Ma.This kinematic shift temporally coincided with the onset of focused rifting,indicating a transition from broadly distributed extension in the eastern Ross Sea to localized deformation in the western basin.Time-resolved strain rate fields further reveal several hundred kilometers of total crustal extension,suggesting a primary influence of evolving plate motions over passive lithospheric weakening.These findings refine the tectonic history of the Ross Sea and provide a reproducible framework linking rift basin evolution to global plate motion.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
The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir upli...The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir uplift.Seismic imaging revealed that the upper slab was scraped and that the lower slab had subducted to a depth of>150 km.These features constitute the tectonic complexity of the Pamirs,as well as the thermal subduction mechanism involved,which remains poorly understood.Hence,in this study,high-resolution three-dimensional(3D)kinematic modeling is applied to investigate the thermal structure and geometry of the subducting slab beneath the Pamirs.The modeled slab configuration reveals distinct along-strike variations,with a steeply dipping slab beneath the southern Pamirs,a more gently inclined slab beneath the northern Pamirs,and apparent upper slab termination at shallow depths beneath the Pamirs.The thermal field reveals a cold slab core after delamination,with temperatures ranging from 400℃to 800℃,enveloped by a hotter mantle reaching~1400℃.The occurrence of intermediate-depth earthquakes aligns primarily with colder slab regions,particularly near the slab tear-off below the southwestern Pamirs,indicating a strong correlation between slab temperature and seismicity.In contrast,the northern Pamirs exhibit reduced seismicity at depth,which is likely associated with thermal weakening and delamination.The central Pamirs show a significant thermal anomaly caused by a concave slab,where the coldest crust does not descend deeply,further suggesting crustal detachment or mechanical failure.The lateral asymmetry in slab temperature possibly explains the mechanism of lateral tearing and differential slab-mantle coupling.展开更多
BACKGROUND Medial dished(MD)liner designs for cruciate-retaining(CR)total knee arthroplasty(TKA)are a relatively novel development.MD tibial inserts have a more constraining medial side,which allows for more similar k...BACKGROUND Medial dished(MD)liner designs for cruciate-retaining(CR)total knee arthroplasty(TKA)are a relatively novel development.MD tibial inserts have a more constraining medial side,which allows for more similar kinematics and function to a native knee.AIM To evaluate the clinical results and patient-reported outcomes after CR TKA procedures utilizing a kinematically designed medial dish system.METHODS A multicenter,retrospective cohort review of 139 primary elective TKAs utilizing a kinematically designed CR Knee System(JOURNEY™II CR MD;Smith and Nephew,Memphis,TN,United States)at three different institutions with a minimum of two years of follow-up.Demographic information,clinical outcomes,and patient-reported outcome measures were collected and analyzed.RESULTS With up to 3.7 years from surgery,overall implant survivorship was 98.6%.There were significant postoperative increases in the average Knee Injury and Osteoarthritis Outcome Score for Joint Replacement scores(17.4 at 6 months,26.1 points at two years or more,P<0.001).CONCLUSION The combination of high implant survivorship and substantial improvements in patient-reported outcome measures suggests that the medial dish tibial insert represents a safe and effective option within TKA.Additional investigation is necessary to evaluate the long-term survivorship of this design.展开更多
A shaking table test was performed to investigate the different responses of piles with and without cement-soil reinforcement,considering both inertial and kinematic interactions.A comparison of the dynamic shear stre...A shaking table test was performed to investigate the different responses of piles with and without cement-soil reinforcement,considering both inertial and kinematic interactions.A comparison of the dynamic shear stress−strain hysteresis curves of soil profiles on the pile side with and without cement-soil reinforced piles indicates that cement-soil reinforced piles not only bear more tremendous shear stress but also have smaller strains under the action of cyclic shear stress.Furthermore,the cement-soil on the pile side not only shares part of the shear stress and modifies the bending moment distribution but also significantly enhances the resistance of the pile-side soil,reducing the lateral displacement of the superstructure.Cement-soil reinforcement reduced shear strains,inhibited sand liquefaction,and reduced superstructure displacements by 27%−47%(instantaneous)and 40%−65%(permanent).The proportion of horizontal load sharing between cement-soil reinforcement and saturated sand is considered,along with the change pattern of the subgrade reaction after sand liquefaction.An equivalent subgrade reaction calculation method is proposed,which accounts for the horizontal load-sharing ratios of soils with two different strengths.The test results indicate that the pile stress and displacement,estimated using the equivalent subgrade reaction,are in good agreement with the observed results.展开更多
Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional atten...Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional attention modules such as SE-Net,CBAM,ECA-Net,and CA adopt a deterministic paradigm,assigning fixed scalar weights to features without modeling ambiguity or confidence.To overcome these limitations,this paper proposes the Fuzzy Attention Network Layer(FANL),which integrates intuitionistic fuzzy set theory with convolutional neural networks to explicitly represent feature uncertainty through membership(μ),non-membership(ν),and hesitation(π)degrees.FANLconsists of four coremodules:(1)feature dimensionality reduction via global pooling,(2)fuzzymodeling using learnable clustering centers,(3)adaptive attention generation through weighted fusion of fuzzy components,and(4)feature refinement through residual connections.A cross-layer guidance mechanism is further introduced to enhance hierarchical feature propagation,allowing high-level semantic features to incorporate fine-grained texture information from shallow layers.Comprehensive experiments on three benchmark datasets—PathMNIST-30000,full PathMNIST,and Blood MNIST—demonstrate the effectiveness and generalizability of FANL.The model achieves 84.41±0.56%accuracy and a 1.69%improvement over the baseline CNN while maintaining lightweight computational complexity.Ablation studies show that removing any component causes a 1.7%–2.0%performance drop,validating the synergistic contribution of each module.Furthermore,FANL provides superior uncertainty calibration(ECE=0.0452)and interpretable selective prediction under uncertainty.Overall,FANL presents an efficient and uncertaintyaware attention framework that improves both accuracy and reliability,offering a promising direction for robust visual recognition under ambiguous or noisy conditions.展开更多
Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score ...Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score the quality of pull-up movement scientifically and objectively,and provide guidance to help athletes better complete the pull-up movement.In this method,the OpenPose algorithm is used to identify the coordinates of skeleton points,and then the coordinate data are processed by a Kalman filter to obtain coordinates closer to the true values.Finally,the filtered data are input into the scoring algorithm designed based on the fuzzy comprehensive evaluation algorithm,and the results of the pull-up quality score and the corresponding guidance are obtained.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
Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudass...Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudassisted architecture faces two critical challenges:the untrusted cloud services and the separation of data ownership from control.Although Attribute-based Searchable Encryption(ABSE)provides fine-grained access control and keyword search over encrypted data,existing schemes lack of error tolerance in exact multi-keyword matching.In this paper,we proposed an attribute-based multi-keyword fuzzy searchable encryption with forward ciphertext search(FCS-ABMSE)scheme that avoids computationally expensive bilinear pairing operations on the IoT device side.The scheme supportsmulti-keyword fuzzy search without requiring explicit keyword fields,thereby significantly enhancing error tolerance in search operations.It further incorporates forward-secure ciphertext search to mitigate trapdoor abuse,as well as offline encryption and verifiable outsourced decryption to minimize user-side computational costs.Formal security analysis proved that the FCS-ABMSE scheme meets both indistinguishability of ciphertext under the chosen keyword attacks(IND-CKA)and the indistinguishability of ciphertext under the chosen plaintext attacks(IND-CPA).In addition,we constructed an enhanced variant based on type-3 pairings.Results demonstrated that the proposed scheme outperforms existing ABSE approaches in terms of functionalities,computational cost,and communication cost.展开更多
Satellite image segmentation plays a crucial role in remote sensing,supporting applications such as environmental monitoring,land use analysis,and disaster management.However,traditional segmentation methods often rel...Satellite image segmentation plays a crucial role in remote sensing,supporting applications such as environmental monitoring,land use analysis,and disaster management.However,traditional segmentation methods often rely on large amounts of labeled data,which are costly and time-consuming to obtain,especially in largescale or dynamic environments.To address this challenge,we propose the Semi-Supervised Multi-View Picture Fuzzy Clustering(SS-MPFC)algorithm,which improves segmentation accuracy and robustness,particularly in complex and uncertain remote sensing scenarios.SS-MPFC unifies three paradigms:semi-supervised learning,multi-view clustering,and picture fuzzy set theory.This integration allows the model to effectively utilize a small number of labeled samples,fuse complementary information from multiple data views,and handle the ambiguity and uncertainty inherent in satellite imagery.We design a novel objective function that jointly incorporates picture fuzzy membership functions across multiple views of the data,and embeds pairwise semi-supervised constraints(must-link and cannot-link)directly into the clustering process to enhance segmentation accuracy.Experiments conducted on several benchmark satellite datasets demonstrate that SS-MPFC significantly outperforms existing state-of-the-art methods in segmentation accuracy,noise robustness,and semantic interpretability.On the Augsburg dataset,SS-MPFC achieves a Purity of 0.8158 and an Accuracy of 0.6860,highlighting its outstanding robustness and efficiency.These results demonstrate that SSMPFC offers a scalable and effective solution for real-world satellite-based monitoring systems,particularly in scenarios where rapid annotation is infeasible,such as wildfire tracking,agricultural monitoring,and dynamic urban mapping.展开更多
Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary freque...Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary frequency regulation(PFR),this paper proposes a novel hybrid energy storage system(HESS)control strategy based on Newton-Raphson optimization algorithm(NRBO)-VMD and a fuzzy neural network(FNN)for PFR.In the primary power allocation stage,the high inertia and slow response of thermal power units prevent them from promptly responding to the high-frequency components of PFR signals,leading to increased mechanical stress.To address the distinct response characteristics of thermal units and HESS,an NRBO-VMD based decomposition method for PFR signals is proposed,enabling a flexible system response to grid frequency deviations.Within the HESS,an adaptive coordinated control strategy and a State of Charge(SOC)self-recovery strategy are introduced.These strategies autonomously adjust the virtual inertia and droop coefficients based on the depth of frequency regulation and the real-time SOC.Furthermore,a FNN is constructed to perform secondary refinement of the internal power distribution within the HESS.Finally,simulations under various operational conditions demonstrate that the proposed strategy effectively mitigates frequent power adjustments of the thermal unit during PFR,adaptively achieves optimal power decomposition and distribution,maintains the flywheel energy storage’s SOC within an optimal range,and ensures the long-term stable operation of the HESS.展开更多
基金Sponsored by the National Nature Science Foundation of China(Grant No.61105088)
文摘A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the robot.The kinematics controller generates desired linear and angular velocities for follower robots,which make the configuration of follower robots coverage to the desired.The fuzzy logic controller takes dynamics of the leader and followers into consideration,which is built upon Mamdani fuzzy model.The force and torque acting on robots are described as linguistic variables and also 25 if-then rules are designed.In addition,the fuzzy logic controller adopts the Centroid of Area method as defuzzification strategy and makes robots’actual velocities converge to the expected which is generated by the kinematics controller.The innovation of the kinematics and fuzzy logic combined formation controller presented in the paper is that the perfect velocity tracking assumption is removed and realtime performance of the system is improved.Compared with traditional torque-computed controller,the velocity error convergence time in case of the proposed method is shorter than traditional torque-computed controller.The simulation results validate that the proposed controller can drive robot members to form the desired formation and formation tracking errors which can coverage to a neighborhood of the origin.Additionally,the simulations also show that the proposed method has better velocity convergence performance than traditional torque-computed method.
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
基金Supported by National Natural Science Foundation of China (Grant No. 52175019)Beijing Municipal Natural Science Foundation of China (Grant No. L222038)+3 种基金Beijing Nova Programme Interdisciplinary Cooperation Project of China (Grant No. 20240484699)Joint Funds of Industry-University-Research of Shanghai Academy of Spaceflight Technology of China (Grant No. SAST2022-017)Beijing Municipal Key Laboratory of Space-ground Interconnection and Convergence of ChinaKey Laboratory of IoT Monitoring and Early Warning,Ministry of Emergency Management of China
文摘To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method for a class of parallel platforms with 3-RE structure after locking the actuated joints is proposed in this paper.Given that the angle between specific joint axes of limbs remains constant,a set of geometric constraints for the forward kinematics of parallel mechanisms(PM)are determined.After translating unit direction vectors of these joint axes to the common starting point,the geometric constraints of the angle between the vectors are transformed into the distances between the endpoints of the vectors,making them easier to handle.Under the framework of CGA,the positions of key points that determine the position and orientation of the moving platform can be intuitively determined by the intersection,division,and duality of basic geometric entities.By employing the tangent half-angle substitution,the forward kinematic analysis of the parallel mechanisms leads to a high-order univariate polynomial equation without the need for any complex algebraic elimination operations.After solving this equation and back substitution,the position and pose of the MP can be obtained indirectly.A numerical case is utilized to confirm the effectiveness of the proposed method.
基金Supported by National Natural Science Foundation of China(Grant No.52275033)National Natural Science Youth Foundation of China(Grant No.52205033)Hebei Provincial Natural Science Foundation of China(Grant No.E2021203019)。
文摘Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfortunately their inverse kinematics have not yet been resolved.This paper discovers that the unknown kinematic parameters of middle platform are responsible for the unresolvable of inverse kinematics,meanwhile the unknown kinematic parameters of middle platform also have huge coupling relationships.Therefore,to break through this challenges,the huge coupling relationships are decoupled layer by layer,the kinematic parameters of middle platform are solved by combining Sylvester's elimination method,and the inverse displacements of 2(3RPS)and 2(3SPR)S-PMs are obtained subsequently.This paper not only solves the inverse kinematics of classical 2(3RPS)and 2(3SPR)S-PMs,but also reveals the essence of the inverse kinematics of general(3-DOF)+(3-DOF)6-DOF S-PMs and proposes a corresponding solution.
文摘Presents a fast and effective method proposed by combining the fuzzy C means (FCM) and the fuzzy neural network for solving robot inverse kinematics, and its successful application to the robot inverse kinematics and concludes from simulation results that this new method not only has high efficiency and accuracy, but also good generalization, and it also overcomes the "dimension disaster" of fuzzy set in a fuzzy neural network fairly well.
基金Supported by National Natural Science Foundation of China(Grant Nos.52335002,52205014,52275033)the Fundamental Research Funds for the Central Universities(Grant No.JZ2024HGTB0245).
文摘Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to avoid collision and improve the flexibility of the robots,this study proposes a reconfigurable cable-driven parallel robot(RCDPR)having characteristics of large load-to-weight ratio,easy modularity and variable stiffness.Adjustable brackets are connected to the moving platform to adjust the position of the pull-out point with the movement of the end-effector.In addition,a variable stiffness actuator(VSA)accompanied by finite element analysis is designed to optimize the cable tension to adapt different task requirements.Firstly,a new idea of reconfiguration is given,and an inverse kinematic model is established using the vector closure principle to derive its inverse kinematic expressions focusing on one of the configurations.Second,the VSA is attached to each cable to achieve stiffness adjustment,and the system stiffness is derived in detail.Finally,the rationality and accuracy of the robot are verified through numerical analysis,providing a reference for subsequent trajectory planning with implications.
基金supported by Guizhou Provincial Basic Research Program(Natural Science,Grant No.QKHJC-ZK[2022]YB075)the National Natural Science Foundation of China(Grant No.42067046)+2 种基金the Guizhou Provincial Program on Commercialization of Scientific and Technological Achievements(N0.QKHCG-LH2024-ZD025)the Science and Technology Planning Project of Guiyang City(Grant No.ZKHT[2023]13-10)Undergraduate Training Program for Innovation and Entrepreneurship of Guizhou Province(Project No.S202110657053)。
文摘Rockfall kinematic characteristics exhibit significant randomness and are influenced by factors such as rock mass properties,slope morphology,impact angle,and slope materials.Accurately determining the key parameters of rockfall movement is critical for understanding motion patterns and effectively preventing and controlling rockfall hazards.In this study,a monitoring system consisting of selfdeveloped inertial navigation equipment,high-speed cameras,and an unmanned aerial vehicle was used to conduct onsite motion tests involving four differently shaped rock specimens on three types of slopes(bedrock,detritus,and clast bedding).The selfdeveloped inertial navigation system integrated a highdynamic-range accelerometer(±400 g)and a shockresistant gyroscope(±4000°/s),capable of robustly collecting data during the test.The data collected from these tests were processed to extract key kinematic parameters such as velocity,trajectory,restitution coefficients,and friction coefficients.The test results demonstrated that the inertial navigation system accurately recorded the acceleration and angular velocity of the rocks during motion,with these measurements closely aligning with the field data.The normal and tangential restitution coefficients were found to be influenced primarily by the slope material and impact angle,with higher normal restitution coefficients observed for low-angle impacts.The normal restitution coefficients ranged from 0.35 to 0.86,whereas the tangential restitution coefficients ranged from 0.46 to 0.91,depending on the slope materials.Additionally,the sliding friction coefficient was calculated to be between 0.66 and 0.78,whereas the rolling friction coefficient for the slab-shaped specimen was determined to be 0.53.These findings provide valuable data for improving the accuracy of rockfall trajectory predictions and the design of protective structures.
基金supported by the National Natural Science Foundation of China(No.52175270)the Project of Scientific and Technological Development Plan of Jilin Province(No.20220508130RC).
文摘The human thumb plays a crucial role in performing coordinated hand movements for precise tool use.However,quantifying and interpreting the kinematics and couplings of the six degrees of freedom(6DOF)between the interphalangeal(IP)and metacarpophalangeal(MCP)joints during hand functional tasks remains challenging.To address this issue,advanced dynamic biplane radiography combined with a model-based 2D–3D tracking technique was employed to decode the inherent kinematics of the thumb IP and MCP joints during key pinch,tip pinch,palmar pinch and wide grasp.The results indicate that the functional tasks of the thumb are intricately modulated by the 3D rotational and translational motions of the IP and MCP joints.The IP joint exhibited the greatest flexion/extension range of motion during the tip pinch task(67.2°±8.4°),compared to smaller ranges in key pinch(27.6°±3.8°)and wide grasp(16.2°±7.1°)tasks.In the wide grasp task,the IP joint showed more movement in the radius/ulna direction(3.4±1.2 mm)compared to tip pinch(3.1±0.8 mm).Furthermore,the kinematic data of the IP joint challenge the traditional notion that the IP joint normally acts as a hinge mechanism.The results of this study help to elucidate the kinematics of human thumb IP and MCP joints and may provide new inspiration for the design of high-performance bionic hands or thumb prosthetics as well as for evaluating the outcomes of thumb therapeutic interventions and surgical procedures.
基金Supported by Hebei Provincial Natural Science Foundation(Grant No.F2024202052)National Natural Science Foundation of China(Grant No.52175019)+3 种基金Beijing Municipal Natural Science Foundation(Grant No.L222038)Beijing Nova Programme Interdisciplinary Cooperation Project(Grant No.20240484699)Joint Funds of Industry-University-Research of Shanghai Academy of Spaceflight Technology(Grant No.SAST2022-017)Beijing Municipal Key Laboratory of Space-ground Interconnection and Convergence of China and Key Laboratory of IoT Monitoring and Early Warning,Ministry of Emergency Management。
文摘Parallel mechanisms with fewer degrees of freedom that incorporate two or more SPR limbs have been widely adopted in industrial applications in recent years.However,notable theoretical gaps persist,particularly in the field of analytical solutions for forward kinematics.To address this,this paper proposes an innovative forward kinematics analysis method based on Conformal Geometric Algebra(CGA)for complex hybrid mechanisms formed by serial concatenation of such parallel mechanisms.The method efficiently represents geometric elements and their operational relationships by defining appropriate unknown parameters.It constructs fundamental geometric objects such as spheres and planes,derives vertex expressions through intersection and dual operations,and establishes univariate high-order equations via inner product operations,ultimately obtaining complete analytical solutions for the forward kinematics of hybrid mechanisms.Using the(2-SPR+RPS)+(3-SPR)serial-parallel hybrid mechanism as a validation case,three configuration tests implemented in Mathematica demonstrate that:for each configuration,the upper 3-SPR mechanism yields 15 mathematical solutions,while the lower 2-SPR+RPS mechanism yields 4 mathematical solutions.After geometric constraint filtering,a unique physically valid solution is obtained for each mechanism.SolidWorks simulations further verify the correctness and reliability of the model.This research provides a reliable analytical method for forward kinematics of hybrid mechanisms,holding significant implications for advancing their applications in high-precision scenarios.
基金The National Natural Science Foundation of China under contract Nos 42176067,41576069,47906197 and 42206066the National Key R&D Program of China under contract No.2024YFF0506701the Project of Impact and Response of Antarctic Seas to Climate Change under contract No.IRASCC01-03-01.
文摘The Ross Sea basins,shaped by Late Cretaceous and Cenozoic extension within the crust of the Ross Sea,represent key regions for understanding continental rifting processes.However,the dynamic mechanisms driving the transition from diffuse extension to focused extension in these basins remain poorly understood.Here,we provide a comprehensive model of crustal extension in the Ross Sea basins,detailing the kinematic and dynamic evolution from 100 Ma to the present on the basis of published finite rotation poles.Our model illuminates the complex relative motions between the West Antarctic and East Antarctic Plates and quantifies the crustal strain rates associated with their relative movements.We show that West Antarctica began to move away slowly from the East Antarctic and rotated clockwise at approximately 53 Ma,and the motion progressively decreased until it ceased at approximately 11 Ma.This kinematic shift temporally coincided with the onset of focused rifting,indicating a transition from broadly distributed extension in the eastern Ross Sea to localized deformation in the western basin.Time-resolved strain rate fields further reveal several hundred kilometers of total crustal extension,suggesting a primary influence of evolving plate motions over passive lithospheric weakening.These findings refine the tectonic history of the Ross Sea and provide a reproducible framework linking rift basin evolution to global plate motion.
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.
基金the Chinese Academy of Sciences Pioneer Hundred Talents Program and the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0708)supported by a MEXT(Ministry of Education,Culture,Sports,Science and Technology)KAKENHI(Grants-in-Aid for Scientific Research)grant(Grant No.21H05203)Kobe University Strategic International Collaborative Research Grant(Type B Fostering Joint Research).
文摘The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir uplift.Seismic imaging revealed that the upper slab was scraped and that the lower slab had subducted to a depth of>150 km.These features constitute the tectonic complexity of the Pamirs,as well as the thermal subduction mechanism involved,which remains poorly understood.Hence,in this study,high-resolution three-dimensional(3D)kinematic modeling is applied to investigate the thermal structure and geometry of the subducting slab beneath the Pamirs.The modeled slab configuration reveals distinct along-strike variations,with a steeply dipping slab beneath the southern Pamirs,a more gently inclined slab beneath the northern Pamirs,and apparent upper slab termination at shallow depths beneath the Pamirs.The thermal field reveals a cold slab core after delamination,with temperatures ranging from 400℃to 800℃,enveloped by a hotter mantle reaching~1400℃.The occurrence of intermediate-depth earthquakes aligns primarily with colder slab regions,particularly near the slab tear-off below the southwestern Pamirs,indicating a strong correlation between slab temperature and seismicity.In contrast,the northern Pamirs exhibit reduced seismicity at depth,which is likely associated with thermal weakening and delamination.The central Pamirs show a significant thermal anomaly caused by a concave slab,where the coldest crust does not descend deeply,further suggesting crustal detachment or mechanical failure.The lateral asymmetry in slab temperature possibly explains the mechanism of lateral tearing and differential slab-mantle coupling.
文摘BACKGROUND Medial dished(MD)liner designs for cruciate-retaining(CR)total knee arthroplasty(TKA)are a relatively novel development.MD tibial inserts have a more constraining medial side,which allows for more similar kinematics and function to a native knee.AIM To evaluate the clinical results and patient-reported outcomes after CR TKA procedures utilizing a kinematically designed medial dish system.METHODS A multicenter,retrospective cohort review of 139 primary elective TKAs utilizing a kinematically designed CR Knee System(JOURNEY™II CR MD;Smith and Nephew,Memphis,TN,United States)at three different institutions with a minimum of two years of follow-up.Demographic information,clinical outcomes,and patient-reported outcome measures were collected and analyzed.RESULTS With up to 3.7 years from surgery,overall implant survivorship was 98.6%.There were significant postoperative increases in the average Knee Injury and Osteoarthritis Outcome Score for Joint Replacement scores(17.4 at 6 months,26.1 points at two years or more,P<0.001).CONCLUSION The combination of high implant survivorship and substantial improvements in patient-reported outcome measures suggests that the medial dish tibial insert represents a safe and effective option within TKA.Additional investigation is necessary to evaluate the long-term survivorship of this design.
基金Project(52078129)supported by the National Natural Science Foundation of ChinaProject(MTF2023009)supported by the Open Project of Key Laboratory of Transport Industry of Comprehensive Transportation Theory(Nanjing Modern Multimodal Transportation Laboratory),ChinaProject(2242024K40037)supported by the Fundamental Research Funds for the Central Universities,China。
文摘A shaking table test was performed to investigate the different responses of piles with and without cement-soil reinforcement,considering both inertial and kinematic interactions.A comparison of the dynamic shear stress−strain hysteresis curves of soil profiles on the pile side with and without cement-soil reinforced piles indicates that cement-soil reinforced piles not only bear more tremendous shear stress but also have smaller strains under the action of cyclic shear stress.Furthermore,the cement-soil on the pile side not only shares part of the shear stress and modifies the bending moment distribution but also significantly enhances the resistance of the pile-side soil,reducing the lateral displacement of the superstructure.Cement-soil reinforcement reduced shear strains,inhibited sand liquefaction,and reduced superstructure displacements by 27%−47%(instantaneous)and 40%−65%(permanent).The proportion of horizontal load sharing between cement-soil reinforcement and saturated sand is considered,along with the change pattern of the subgrade reaction after sand liquefaction.An equivalent subgrade reaction calculation method is proposed,which accounts for the horizontal load-sharing ratios of soils with two different strengths.The test results indicate that the pile stress and displacement,estimated using the equivalent subgrade reaction,are in good agreement with the observed results.
文摘Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional attention modules such as SE-Net,CBAM,ECA-Net,and CA adopt a deterministic paradigm,assigning fixed scalar weights to features without modeling ambiguity or confidence.To overcome these limitations,this paper proposes the Fuzzy Attention Network Layer(FANL),which integrates intuitionistic fuzzy set theory with convolutional neural networks to explicitly represent feature uncertainty through membership(μ),non-membership(ν),and hesitation(π)degrees.FANLconsists of four coremodules:(1)feature dimensionality reduction via global pooling,(2)fuzzymodeling using learnable clustering centers,(3)adaptive attention generation through weighted fusion of fuzzy components,and(4)feature refinement through residual connections.A cross-layer guidance mechanism is further introduced to enhance hierarchical feature propagation,allowing high-level semantic features to incorporate fine-grained texture information from shallow layers.Comprehensive experiments on three benchmark datasets—PathMNIST-30000,full PathMNIST,and Blood MNIST—demonstrate the effectiveness and generalizability of FANL.The model achieves 84.41±0.56%accuracy and a 1.69%improvement over the baseline CNN while maintaining lightweight computational complexity.Ablation studies show that removing any component causes a 1.7%–2.0%performance drop,validating the synergistic contribution of each module.Furthermore,FANL provides superior uncertainty calibration(ECE=0.0452)and interpretable selective prediction under uncertainty.Overall,FANL presents an efficient and uncertaintyaware attention framework that improves both accuracy and reliability,offering a promising direction for robust visual recognition under ambiguous or noisy conditions.
文摘Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score the quality of pull-up movement scientifically and objectively,and provide guidance to help athletes better complete the pull-up movement.In this method,the OpenPose algorithm is used to identify the coordinates of skeleton points,and then the coordinate data are processed by a Kalman filter to obtain coordinates closer to the true values.Finally,the filtered data are input into the scoring algorithm designed based on the fuzzy comprehensive evaluation algorithm,and the results of the pull-up quality score and the corresponding guidance are obtained.
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Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudassisted architecture faces two critical challenges:the untrusted cloud services and the separation of data ownership from control.Although Attribute-based Searchable Encryption(ABSE)provides fine-grained access control and keyword search over encrypted data,existing schemes lack of error tolerance in exact multi-keyword matching.In this paper,we proposed an attribute-based multi-keyword fuzzy searchable encryption with forward ciphertext search(FCS-ABMSE)scheme that avoids computationally expensive bilinear pairing operations on the IoT device side.The scheme supportsmulti-keyword fuzzy search without requiring explicit keyword fields,thereby significantly enhancing error tolerance in search operations.It further incorporates forward-secure ciphertext search to mitigate trapdoor abuse,as well as offline encryption and verifiable outsourced decryption to minimize user-side computational costs.Formal security analysis proved that the FCS-ABMSE scheme meets both indistinguishability of ciphertext under the chosen keyword attacks(IND-CKA)and the indistinguishability of ciphertext under the chosen plaintext attacks(IND-CPA).In addition,we constructed an enhanced variant based on type-3 pairings.Results demonstrated that the proposed scheme outperforms existing ABSE approaches in terms of functionalities,computational cost,and communication cost.
基金funded by the Research Project:THTETN.05/24-25,VietnamAcademy of Science and Technology.
文摘Satellite image segmentation plays a crucial role in remote sensing,supporting applications such as environmental monitoring,land use analysis,and disaster management.However,traditional segmentation methods often rely on large amounts of labeled data,which are costly and time-consuming to obtain,especially in largescale or dynamic environments.To address this challenge,we propose the Semi-Supervised Multi-View Picture Fuzzy Clustering(SS-MPFC)algorithm,which improves segmentation accuracy and robustness,particularly in complex and uncertain remote sensing scenarios.SS-MPFC unifies three paradigms:semi-supervised learning,multi-view clustering,and picture fuzzy set theory.This integration allows the model to effectively utilize a small number of labeled samples,fuse complementary information from multiple data views,and handle the ambiguity and uncertainty inherent in satellite imagery.We design a novel objective function that jointly incorporates picture fuzzy membership functions across multiple views of the data,and embeds pairwise semi-supervised constraints(must-link and cannot-link)directly into the clustering process to enhance segmentation accuracy.Experiments conducted on several benchmark satellite datasets demonstrate that SS-MPFC significantly outperforms existing state-of-the-art methods in segmentation accuracy,noise robustness,and semantic interpretability.On the Augsburg dataset,SS-MPFC achieves a Purity of 0.8158 and an Accuracy of 0.6860,highlighting its outstanding robustness and efficiency.These results demonstrate that SSMPFC offers a scalable and effective solution for real-world satellite-based monitoring systems,particularly in scenarios where rapid annotation is infeasible,such as wildfire tracking,agricultural monitoring,and dynamic urban mapping.
基金supported by the Lanzhou Science and Technology Plan Project(XM1753694781389).
文摘Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary frequency regulation(PFR),this paper proposes a novel hybrid energy storage system(HESS)control strategy based on Newton-Raphson optimization algorithm(NRBO)-VMD and a fuzzy neural network(FNN)for PFR.In the primary power allocation stage,the high inertia and slow response of thermal power units prevent them from promptly responding to the high-frequency components of PFR signals,leading to increased mechanical stress.To address the distinct response characteristics of thermal units and HESS,an NRBO-VMD based decomposition method for PFR signals is proposed,enabling a flexible system response to grid frequency deviations.Within the HESS,an adaptive coordinated control strategy and a State of Charge(SOC)self-recovery strategy are introduced.These strategies autonomously adjust the virtual inertia and droop coefficients based on the depth of frequency regulation and the real-time SOC.Furthermore,a FNN is constructed to perform secondary refinement of the internal power distribution within the HESS.Finally,simulations under various operational conditions demonstrate that the proposed strategy effectively mitigates frequent power adjustments of the thermal unit during PFR,adaptively achieves optimal power decomposition and distribution,maintains the flywheel energy storage’s SOC within an optimal range,and ensures the long-term stable operation of the HESS.
