This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relativ...This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.展开更多
Hard disk drives(HDDs)serve as the primary storage devices in modern data centers.Once a failure occurs,it often leads to severe data loss,significantly degrading the reliability of storage systems.Numerous studies ha...Hard disk drives(HDDs)serve as the primary storage devices in modern data centers.Once a failure occurs,it often leads to severe data loss,significantly degrading the reliability of storage systems.Numerous studies have proposed machine learning-based HDD failure prediction models.However,the Self-Monitoring,Analysis,and Reporting Technology(SMART)attributes differ across HDD manufacturers.We define hard drives of the same brand and model as homogeneous HDD groups,and those from different brands or models as heterogeneous HDD groups.In practical engineering scenarios,a data center is often composed of a heterogeneous population of HDDs,spanning multiple vendors and models.Existing research predominantly focuses on homogeneous datasets,ignoring the model’s generalization capability across heterogeneous HDDs.As a result,HDD models with limited samples often suffer from poor training effectiveness and prediction performance.To address this issue,we investigate generalizable SMART predictors across heterogeneous HDD groups.By extracting time-series features within a fixed sliding time window,we propose a Heterogeneous Disk Failure Prediction Method based on Time Series Features(HDFPM)framework.This method is adaptable to HDD models with limited sample sizes,thereby enhancing its applicability and robustness across diverse drive populations.Experimental results show that the proposed model achieves an F1-score of 0.9518 when applied to two different Seagate HDD models,while maintaining the False Positive Rate(FPR)below 1%.After incorporating the Complexity-Ratio Dynamic Time Warping(CDTW)based feature enhancement method,the best prediction model achieves a True Positive Rate(TPR)of up to 0.93 between the two models.For next-day failure prediction across various Seagate models,the model achieves an F1-score of up to 0.8792.Moreover,the experimental results also show that within the same brand,the higher the proportion of shared SMART attributes across different models,the better the prediction performance.In addition,HDFPMdemonstrates the best stability andmost significant performance in heterogeneous environments.展开更多
The Shanghai High Repetition Rate XFEL and Extreme Light Facility(SHINE)is currently under construction as one of the world’s most advanced hard X-ray free-electron laser facilities.The timing system,as an essential ...The Shanghai High Repetition Rate XFEL and Extreme Light Facility(SHINE)is currently under construction as one of the world’s most advanced hard X-ray free-electron laser facilities.The timing system,as an essential part of the free-electron laser facility,provides precise timing of trigger pulse signals for a range of devices to ensure that particles are generated and accelerated to the designed energy while enabling the precise measurement of beam parameters.To precisely distribute and synchronize the 1.003086 MHz(1300/1296)timing signals over a distance of approximately 3.1 km based on White Rabbit technology,three technical routes have been proposed.This paper begins with a description of the design and development process of the timing system for the SHINE project,which culminates with the determination of the design scheme.During the installation and commissioning of the timing system,the jitter accuracy of the timing signal was tested and found to be less than 10 ps,which meets the requirements of the project.Furthermore,the precise clock synchronization signal provided by the timing system supported the joint debugging of various related systems and realization of beam acquisition.展开更多
This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality...This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality classification were determined based on wave theory of Kelvin medium.Then,a calculation model was obtained for the millisecond-delay cut blast vibration in Kelvin media using the Starfield charge superposition principle.Further,the influence of the delay time on the cut blast vibration was quantitatively analyzed and a method for calculating the reasonable cut blasting millisecond delay time is proposed according to the principle of dimensional analysis.Finally,field tests were used to verify the applicability of the method.The results show that 5 ms to 20 ms is a better detonator delay time range and cut blasting vibration can be effectively controlled using the delay time calculated by the calculation model described in this paper.展开更多
Chilo suppressalis(Walker)is one of the most important rice pests worldwide,posing a significant challenge to effective control.To develop a precision-timed,eco-friendly management strategy,overwintering population in...Chilo suppressalis(Walker)is one of the most important rice pests worldwide,posing a significant challenge to effective control.To develop a precision-timed,eco-friendly management strategy,overwintering population investigation and dynamic monitoring of C.suppressalis populations were conducted in the Meishan region of Sichuan,China,from 2023 to 2024.The optimal timing for insecticide application was estimated,followed by field trials evaluating the efficacy of different insecticides.Results demonstrated that the peak emergence of first-generation adults typically occurred in early July(under the environmental conditions of the Meishan region),with the ambient humidity below 75%and temperature around 29◦C.Pesticide efficacy trials show that insecticide combinations exhibited superior control.Notably,a combined treatment of emamectin benzoate⋅methoxyfenozide+chlorantraniliprole achieved the highest control efficacy(90.05%)and a corresponding yield of 12,491.55 kg/ha.All tested treatments were determined to be safe for rice growth.Furthermore,this optimized strategy resulted in notable economic benefits,including a 50%reduction in pesticide usage and cost savings of 4796.15 CNY compared to conventional practices.This study provides valuable insights into sustainable rice production and pest management and,for the first time,proposes a precision application time window based on intelligent monitoring.展开更多
Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative con...Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.展开更多
To study the influence of support timing and support strength on the mechanical properties and deformation damage characteristics of a single-sided unloaded rock mass,a true triaxial perturbation unloaded rock testing...To study the influence of support timing and support strength on the mechanical properties and deformation damage characteristics of a single-sided unloaded rock mass,a true triaxial perturbation unloaded rock testing system was used to conduct rock damage tests on sandstone with different support timing and strength paths.Based on the acoustic emission monitoring system,the spatial and temporal evolution characteristics of the whole process of rock body loaded instability under two stress paths were studied,and the mechanism of the reinforcing effect of stress support on the unloaded rock mass was analyzed.The results show that,within the scope of this study,both earlier applications of shoring and an increase in shoring strength can effectively improve the ultimate bearing capacity of the unloaded rock,which increases the ultimate bearing capacity of the unloaded rock mass by 60.31% and 54.96%,respectively;There is a phenomenon of rebound deformation of the rock mass during sudden changes in stress(single-sided unloading,stress support),which shows opposite expansion and compression platforms on the stress−strain curve;The crack evolution of unloaded rock under different stress support conditions shows the state law of"initial crack activation→middle steady state expansion→late main crack penetration",and the lagging support significantly accelerates the crack evolution from local activation to main penetration;The single-sided unloading and stress-supporting stages have less influence on the unloading deformationsσ_(1u),σ_(2u) and support deformationsσ_(1) t,σ_(2t) in theσ_(1) andσ_(2)directions,while they show significant response characteristics toσ_(3u),σ_(vu) and σ_(3) t,σ_(vt),and with the increase of the support strength,the stress-supporting stagesσ_(3) t,σ_(vt) gradually increase and exceed the deformations generated by the unloading stagesσ_(3u),σ_(vu);The increase of support strength can effectively compensate for the rock stress loss caused by unloading,which makes the maximum,minimum,and volumetric strain support coefficients during the loading and unloading of the rock body increase gradually while the effect on the intermediate principal strain support coefficient is small;During loading,the support strength of rock masses seeks a new bearing area by regulating stress equilibrium states.This process primarily manifests as a shift in the locations of the crushing zone and the main bearing area,accompanied by a corresponding transformation in failure patterns.Consequently,the rock mass transitions from asymmetric three-zone damage under no or weak support to approximate symmetric three-zone damage under strong support.Simultaneously,the main load-bearing area of the rock mass shifts from deep bearing in the unsupported to middle bearing under strong support as the support strength increases.展开更多
Severe trauma often involves complex injuries,leading to high disability and fatality rates.Effective treatment requires prompt and coordinated efforts across multiple disciplines to enhance success rates.Time-based c...Severe trauma often involves complex injuries,leading to high disability and fatality rates.Effective treatment requires prompt and coordinated efforts across multiple disciplines to enhance success rates.Time-based chain rescue is crucial in managing severe trauma.A patient with chest and abdominal injuries and hemorrhagic shock was transferred from an ambulance to our hospital.Our trauma team-initiated pre-hospital first aid,utilized an emergency green channel,and conducted rapid ultrasound,collaborating across disciplines.The patient eventually recovered and was discharged.展开更多
UAV-mounted intelligent reflecting surface(IRS)helps address the line-of-sight(LoS)blockage between sensor nodes(SNs)and the fusion center(FC)in Internet of Things(IoT).This paper considers an IoT assisted by multiple...UAV-mounted intelligent reflecting surface(IRS)helps address the line-of-sight(LoS)blockage between sensor nodes(SNs)and the fusion center(FC)in Internet of Things(IoT).This paper considers an IoT assisted by multiple UAVs-mounted IRS(U-IRS),where the data from ground SNs are transmitted to the FC.In practice,energy efficiency(EE)and mission completion time are crucial metrics for evaluating system performance and operational costs.Recognizing their importance during data collection,we formulate a multi-objective optimization problem to maximize EE and minimize total mission completion time simultaneously.To characterize this tradeoff while considering optimization objective consistency,we construct an optimization problem that minimizes the weighted sum of the total mission completion time and the reciprocal of EE.Due to the non-convex nature of the formulated problem,obtaining optimal solutions is generally challenging.To tackle this issue,we decompose it into three subproblems:UAV-SN association,number of reflecting elements allocation,andUAVtrajectory optimization.An iterative algorithmcombining genetic algorithm,CS-BJ algorithm,and successive convex approximation technique is proposed to solve these sub-problems.Simulation results demonstrate that when the transmitted data amount is 10 and 30Mbits,compared to the static collection benchmark(the UAV hovers directly above each SN),the EE of the proposed method improves by more than 10.4% and 5.2%,while the total mission completion time is reduced by more than 5.4% and 3.3%,respectively.展开更多
Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,transl...Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.展开更多
This study compares the relative efficacy of the continuation task and the model-as-feedbackwriting (MAFW) task in EFL writing development. Ninety intermediate-level Chinese EFL learnerswere randomly assigned to a con...This study compares the relative efficacy of the continuation task and the model-as-feedbackwriting (MAFW) task in EFL writing development. Ninety intermediate-level Chinese EFL learnerswere randomly assigned to a continuation group, a MAFW group, and a control group, each with30 learners. A pretest and a posttest were used to gauge L2 writing development. Results showedthat the continuation task outperformed the MAFW task not only in enhancing the overall qualityof L2 writing, but also in promoting the quality of three components of L2 writing, namely, content,organization, and language. The finding has important implications for L2 writing teaching andlearning.展开更多
Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energ...Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energy and load forecasting in active distribution networks(ADN),this paper proposes a multi-timescale coordinated optimal dispatch strategy that incorporates TSEH clusters.It utilizes the thermal storage characteristics and short-term regulation capabilities of TSEH,along with the rapid and gradual response characteristics of resources in active distribution grids,to develop a coordinated optimization dispatch mechanism for day-ahead,intraday,and real-time stages.It provides a coordinated optimized dispatch technique across several timescales for active distribution grids,taking into account the integration of TSEH clusters.The proposed method is validated on a modified IEEE 33-node system.Simulation results demonstrate that the participation of TSEH in collaborative optimization significantly reduces the total system operating cost by 8.71%compared to the scenario without TSEH.This cost reduction is attributed to a 10.84%decrease in interaction costs with the main grid and a 47.41%reduction in network loss costs,validating effective peak shaving and valley filling.The multi-timescale framework further enhances economic efficiency,with overall operating costs progressively decreasing by 3.91%(intraday)and 4.59%(real-time),and interaction costs further reduced by 5.34%and 9.25%,respectively.Moreover,the approach enhances system stability by effectively suppressing node voltage fluctuations and ensuring all voltages remain within safe operating limits during real-time operation.Therefore,the proposed approach achieves rational coordination of diverse resources,significantly improving the economic efficiency and stability of ADNs.展开更多
Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remain...Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.展开更多
Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always ...Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.展开更多
Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection appr...Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection approaches use either signature-based approaches to detect known TCs or anomaly-based approach by modeling the legitimate network traffic in order to detect unknown TCs. Un-fortunately, in a software-defined networking (SDN) environment, most existing TC detection approaches would fail due to factors such as volatile network traffic, imprecise timekeeping mechanisms, and dynamic network topology. Furthermore, stealthy TCs can be designed to mimic the legitimate traffic pattern and thus evade anomalous TC detection. In this paper, we overcome the above challenges by presenting a novel framework that harnesses the advantages of elastic re-sources in the cloud. In particular, our framework dynamically configures SDN to enable/disable differential analysis against outbound network flows of different virtual machines (VMs). Our framework is tightly coupled with a new metric that first decomposes the timing data of network flows into a number of using the discrete wavelet-based multi-resolution transform (DWMT). It then applies the Kullback-Leibler divergence (KLD) to measure the variance among flow pairs. The appealing feature of our approach is that, compared with the existing anomaly detection approaches, it can detect most existing and some new stealthy TCs without legitimate traffic for modeling, even with the presence of noise and imprecise timekeeping mechanism in an SDN virtual environment. We implement our framework as a prototype system, OBSERVER, which can be dynamically deployed in an SDN environment. Empirical evaluation shows that our approach can efficiently detect TCs with a higher detection rate, lower latency, and negligible performance overhead compared to existing approaches.展开更多
文摘This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.
基金supported by the Tianjin Manufacturing High Quality Development Special Foundation(No.20232185)the Roycom Foundation(No.70306901).
文摘Hard disk drives(HDDs)serve as the primary storage devices in modern data centers.Once a failure occurs,it often leads to severe data loss,significantly degrading the reliability of storage systems.Numerous studies have proposed machine learning-based HDD failure prediction models.However,the Self-Monitoring,Analysis,and Reporting Technology(SMART)attributes differ across HDD manufacturers.We define hard drives of the same brand and model as homogeneous HDD groups,and those from different brands or models as heterogeneous HDD groups.In practical engineering scenarios,a data center is often composed of a heterogeneous population of HDDs,spanning multiple vendors and models.Existing research predominantly focuses on homogeneous datasets,ignoring the model’s generalization capability across heterogeneous HDDs.As a result,HDD models with limited samples often suffer from poor training effectiveness and prediction performance.To address this issue,we investigate generalizable SMART predictors across heterogeneous HDD groups.By extracting time-series features within a fixed sliding time window,we propose a Heterogeneous Disk Failure Prediction Method based on Time Series Features(HDFPM)framework.This method is adaptable to HDD models with limited sample sizes,thereby enhancing its applicability and robustness across diverse drive populations.Experimental results show that the proposed model achieves an F1-score of 0.9518 when applied to two different Seagate HDD models,while maintaining the False Positive Rate(FPR)below 1%.After incorporating the Complexity-Ratio Dynamic Time Warping(CDTW)based feature enhancement method,the best prediction model achieves a True Positive Rate(TPR)of up to 0.93 between the two models.For next-day failure prediction across various Seagate models,the model achieves an F1-score of up to 0.8792.Moreover,the experimental results also show that within the same brand,the higher the proportion of shared SMART attributes across different models,the better the prediction performance.In addition,HDFPMdemonstrates the best stability andmost significant performance in heterogeneous environments.
基金supported by SHINE and Shanghai Municipal Science and Technology Major Project(No.2017SHZDZX02).
文摘The Shanghai High Repetition Rate XFEL and Extreme Light Facility(SHINE)is currently under construction as one of the world’s most advanced hard X-ray free-electron laser facilities.The timing system,as an essential part of the free-electron laser facility,provides precise timing of trigger pulse signals for a range of devices to ensure that particles are generated and accelerated to the designed energy while enabling the precise measurement of beam parameters.To precisely distribute and synchronize the 1.003086 MHz(1300/1296)timing signals over a distance of approximately 3.1 km based on White Rabbit technology,three technical routes have been proposed.This paper begins with a description of the design and development process of the timing system for the SHINE project,which culminates with the determination of the design scheme.During the installation and commissioning of the timing system,the jitter accuracy of the timing signal was tested and found to be less than 10 ps,which meets the requirements of the project.Furthermore,the precise clock synchronization signal provided by the timing system supported the joint debugging of various related systems and realization of beam acquisition.
基金National Natural Science Foundation of China under Grant Nos.51979205 and 51939008。
文摘This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality classification were determined based on wave theory of Kelvin medium.Then,a calculation model was obtained for the millisecond-delay cut blast vibration in Kelvin media using the Starfield charge superposition principle.Further,the influence of the delay time on the cut blast vibration was quantitatively analyzed and a method for calculating the reasonable cut blasting millisecond delay time is proposed according to the principle of dimensional analysis.Finally,field tests were used to verify the applicability of the method.The results show that 5 ms to 20 ms is a better detonator delay time range and cut blasting vibration can be effectively controlled using the delay time calculated by the calculation model described in this paper.
基金funded by the National Key R&D Project‘Innovation and Integration of Key Technologies for Integration of Agricultural Machinery and Agronomy in Weak Links of Hybrid Mid-season Rice in Hilly Areas of Southwest China’(2023YFD2301901).
文摘Chilo suppressalis(Walker)is one of the most important rice pests worldwide,posing a significant challenge to effective control.To develop a precision-timed,eco-friendly management strategy,overwintering population investigation and dynamic monitoring of C.suppressalis populations were conducted in the Meishan region of Sichuan,China,from 2023 to 2024.The optimal timing for insecticide application was estimated,followed by field trials evaluating the efficacy of different insecticides.Results demonstrated that the peak emergence of first-generation adults typically occurred in early July(under the environmental conditions of the Meishan region),with the ambient humidity below 75%and temperature around 29◦C.Pesticide efficacy trials show that insecticide combinations exhibited superior control.Notably,a combined treatment of emamectin benzoate⋅methoxyfenozide+chlorantraniliprole achieved the highest control efficacy(90.05%)and a corresponding yield of 12,491.55 kg/ha.All tested treatments were determined to be safe for rice growth.Furthermore,this optimized strategy resulted in notable economic benefits,including a 50%reduction in pesticide usage and cost savings of 4796.15 CNY compared to conventional practices.This study provides valuable insights into sustainable rice production and pest management and,for the first time,proposes a precision application time window based on intelligent monitoring.
基金supported by the Fundamental Research Funds for the Central Universities of China(FRF-TP-24-058A)with additional support from the National Key Laboratory of Helicopter Aeromechanics(2024-ZSJ-LB-02-02).
文摘Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.
基金Projects(2023 YFC 2907602,2022 YFF 1303302)supported by the National Key Research and Development Project of ChinaProject(52342404)supported by the National Natural Science Foundation of China+2 种基金Project(GXXT-2021-075)supported by the University Synergy Innovation Program of Anhui Province,ChinaProject(2022AH010053)supported by Excellent Scientific Research and Innovation Team of Universities in Anhui Province,ChinaProject(2022xscx080)supported by Anhui Provincial Department of Education Graduate Student Academic Innovation Fund,China。
文摘To study the influence of support timing and support strength on the mechanical properties and deformation damage characteristics of a single-sided unloaded rock mass,a true triaxial perturbation unloaded rock testing system was used to conduct rock damage tests on sandstone with different support timing and strength paths.Based on the acoustic emission monitoring system,the spatial and temporal evolution characteristics of the whole process of rock body loaded instability under two stress paths were studied,and the mechanism of the reinforcing effect of stress support on the unloaded rock mass was analyzed.The results show that,within the scope of this study,both earlier applications of shoring and an increase in shoring strength can effectively improve the ultimate bearing capacity of the unloaded rock,which increases the ultimate bearing capacity of the unloaded rock mass by 60.31% and 54.96%,respectively;There is a phenomenon of rebound deformation of the rock mass during sudden changes in stress(single-sided unloading,stress support),which shows opposite expansion and compression platforms on the stress−strain curve;The crack evolution of unloaded rock under different stress support conditions shows the state law of"initial crack activation→middle steady state expansion→late main crack penetration",and the lagging support significantly accelerates the crack evolution from local activation to main penetration;The single-sided unloading and stress-supporting stages have less influence on the unloading deformationsσ_(1u),σ_(2u) and support deformationsσ_(1) t,σ_(2t) in theσ_(1) andσ_(2)directions,while they show significant response characteristics toσ_(3u),σ_(vu) and σ_(3) t,σ_(vt),and with the increase of the support strength,the stress-supporting stagesσ_(3) t,σ_(vt) gradually increase and exceed the deformations generated by the unloading stagesσ_(3u),σ_(vu);The increase of support strength can effectively compensate for the rock stress loss caused by unloading,which makes the maximum,minimum,and volumetric strain support coefficients during the loading and unloading of the rock body increase gradually while the effect on the intermediate principal strain support coefficient is small;During loading,the support strength of rock masses seeks a new bearing area by regulating stress equilibrium states.This process primarily manifests as a shift in the locations of the crushing zone and the main bearing area,accompanied by a corresponding transformation in failure patterns.Consequently,the rock mass transitions from asymmetric three-zone damage under no or weak support to approximate symmetric three-zone damage under strong support.Simultaneously,the main load-bearing area of the rock mass shifts from deep bearing in the unsupported to middle bearing under strong support as the support strength increases.
基金Jiangsu Provincial Hospital Association Hospital Management Innovation Research Fund(Project Ni.:JSYGY-3-2025-267)。
文摘Severe trauma often involves complex injuries,leading to high disability and fatality rates.Effective treatment requires prompt and coordinated efforts across multiple disciplines to enhance success rates.Time-based chain rescue is crucial in managing severe trauma.A patient with chest and abdominal injuries and hemorrhagic shock was transferred from an ambulance to our hospital.Our trauma team-initiated pre-hospital first aid,utilized an emergency green channel,and conducted rapid ultrasound,collaborating across disciplines.The patient eventually recovered and was discharged.
基金supported in part by the Opening Project of Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory under Grant AD25069102in part by the Basic Ability Improvement Project of Young and Middle Aged Teachers in Guangxi Universities,under Grant 2023KY0226+6 种基金in part by Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education of China,underGrant CRKL220108in part by the Innovation Project of Guangxi Graduate Education,under Grant YCBZ2023131in part by the Doctoral Research Foundation of Guilin University of Electronic Technology,under Grant UF23038Yin part by the Bagui Youth Top Talent Projectin part by the Guangxi Key Research and Development Program under Grant AB25069510in part by Open Fund of IPOC(BUPT),No.IPOC2024B07in part by Guangxi Key Laboratory of Precision Navigation Technology and Application,under Grant DH202309.
文摘UAV-mounted intelligent reflecting surface(IRS)helps address the line-of-sight(LoS)blockage between sensor nodes(SNs)and the fusion center(FC)in Internet of Things(IoT).This paper considers an IoT assisted by multiple UAVs-mounted IRS(U-IRS),where the data from ground SNs are transmitted to the FC.In practice,energy efficiency(EE)and mission completion time are crucial metrics for evaluating system performance and operational costs.Recognizing their importance during data collection,we formulate a multi-objective optimization problem to maximize EE and minimize total mission completion time simultaneously.To characterize this tradeoff while considering optimization objective consistency,we construct an optimization problem that minimizes the weighted sum of the total mission completion time and the reciprocal of EE.Due to the non-convex nature of the formulated problem,obtaining optimal solutions is generally challenging.To tackle this issue,we decompose it into three subproblems:UAV-SN association,number of reflecting elements allocation,andUAVtrajectory optimization.An iterative algorithmcombining genetic algorithm,CS-BJ algorithm,and successive convex approximation technique is proposed to solve these sub-problems.Simulation results demonstrate that when the transmitted data amount is 10 and 30Mbits,compared to the static collection benchmark(the UAV hovers directly above each SN),the EE of the proposed method improves by more than 10.4% and 5.2%,while the total mission completion time is reduced by more than 5.4% and 3.3%,respectively.
基金supported by the National Natural Science Foundation of China under Grant No.72293575.
文摘Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.
文摘This study compares the relative efficacy of the continuation task and the model-as-feedbackwriting (MAFW) task in EFL writing development. Ninety intermediate-level Chinese EFL learnerswere randomly assigned to a continuation group, a MAFW group, and a control group, each with30 learners. A pretest and a posttest were used to gauge L2 writing development. Results showedthat the continuation task outperformed the MAFW task not only in enhancing the overall qualityof L2 writing, but also in promoting the quality of three components of L2 writing, namely, content,organization, and language. The finding has important implications for L2 writing teaching andlearning.
基金supported by Integrated Distribution Network Planning and Operational Enhancement Using Flexibility Domains Under Deep Human-Vehicle-Charger-Road-Grid Coupling(U22B20105).
文摘Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energy and load forecasting in active distribution networks(ADN),this paper proposes a multi-timescale coordinated optimal dispatch strategy that incorporates TSEH clusters.It utilizes the thermal storage characteristics and short-term regulation capabilities of TSEH,along with the rapid and gradual response characteristics of resources in active distribution grids,to develop a coordinated optimization dispatch mechanism for day-ahead,intraday,and real-time stages.It provides a coordinated optimized dispatch technique across several timescales for active distribution grids,taking into account the integration of TSEH clusters.The proposed method is validated on a modified IEEE 33-node system.Simulation results demonstrate that the participation of TSEH in collaborative optimization significantly reduces the total system operating cost by 8.71%compared to the scenario without TSEH.This cost reduction is attributed to a 10.84%decrease in interaction costs with the main grid and a 47.41%reduction in network loss costs,validating effective peak shaving and valley filling.The multi-timescale framework further enhances economic efficiency,with overall operating costs progressively decreasing by 3.91%(intraday)and 4.59%(real-time),and interaction costs further reduced by 5.34%and 9.25%,respectively.Moreover,the approach enhances system stability by effectively suppressing node voltage fluctuations and ensuring all voltages remain within safe operating limits during real-time operation.Therefore,the proposed approach achieves rational coordination of diverse resources,significantly improving the economic efficiency and stability of ADNs.
基金This study is financed by the European Union-NextGenerationEU,through the National Recovery and Resilience Plan of the Republic of Bulgaria,Project No.BG-RRP-2.013-0001.
文摘Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.
基金supported by the National Natural Science Foundation of China(72571094,72271076,71871079)。
文摘Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.
文摘Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection approaches use either signature-based approaches to detect known TCs or anomaly-based approach by modeling the legitimate network traffic in order to detect unknown TCs. Un-fortunately, in a software-defined networking (SDN) environment, most existing TC detection approaches would fail due to factors such as volatile network traffic, imprecise timekeeping mechanisms, and dynamic network topology. Furthermore, stealthy TCs can be designed to mimic the legitimate traffic pattern and thus evade anomalous TC detection. In this paper, we overcome the above challenges by presenting a novel framework that harnesses the advantages of elastic re-sources in the cloud. In particular, our framework dynamically configures SDN to enable/disable differential analysis against outbound network flows of different virtual machines (VMs). Our framework is tightly coupled with a new metric that first decomposes the timing data of network flows into a number of using the discrete wavelet-based multi-resolution transform (DWMT). It then applies the Kullback-Leibler divergence (KLD) to measure the variance among flow pairs. The appealing feature of our approach is that, compared with the existing anomaly detection approaches, it can detect most existing and some new stealthy TCs without legitimate traffic for modeling, even with the presence of noise and imprecise timekeeping mechanism in an SDN virtual environment. We implement our framework as a prototype system, OBSERVER, which can be dynamically deployed in an SDN environment. Empirical evaluation shows that our approach can efficiently detect TCs with a higher detection rate, lower latency, and negligible performance overhead compared to existing approaches.
