This paper proposes one method of feature selection by using Bayes＇ theorem. The purpose of the proposed method is to reduce the computational complexity and increase the classification accuracy of the selected featu...This paper proposes one method of feature selection by using Bayes＇ theorem. The purpose of the proposed method is to reduce the computational complexity and increase the classification accuracy of the selected feature subsets. The dependence between two attributes （binary） is determined based on the probabilities of their joint values that contribute to positive and negative classification decisions. If opposing sets of attribute values do not lead to opposing classification decisions （zero probability）, then the two attributes are considered independent of each other, otherwise dependent, and one of them can be removed and thus the number of attributes is reduced. The process must be repeated on all combinations of attributes. The paper also evaluates the approach by comparing it with existing feature selection algorithms over 8 datasets from University of California, Irvine （UCI） machine learning databases. The proposed method shows better results in terms of number of selected features, classification accuracy, and running time than most existing algorithms.展开更多
In this contribution, we present iHEARu-PLAY, an online, multi-player platform for crowdsourced database collection and labelling, including the voice analysis application (VoiLA), a free web-based speech classificati...In this contribution, we present iHEARu-PLAY, an online, multi-player platform for crowdsourced database collection and labelling, including the voice analysis application (VoiLA), a free web-based speech classification tool designed to educate iHEARu-PLAY users about state-of-the-art speech analysis paradigms. Via this associated speech analysis web interface, in addition, VoiLA encourages users to take an active role in improving the service by providing labelled speech data. The platform allows users to record and upload voice samples directly from their browser, which are then analysed in a state-of-the-art classification pipeline. A set of pre-trained models targeting a range of speaker states and traits such as gender, valence, arousal, dominance, and 24 different discrete emotions is employed. The analysis results are visualised in a way that they are easily interpretable by laymen, giving users unique insights into how their voice sounds. We assess the effectiveness of iHEARu-PLAY and its integrated VoiLA feature via a series of user evaluations which indicate that it is fun and easy to use, and that it provides accurate and informative results.展开更多
In the face of a growing number of large-scale data sets, affinity propagation clustering algorithm to calculate the process required to build the similarity matrix, will bring huge storage and computation. Therefore,...In the face of a growing number of large-scale data sets, affinity propagation clustering algorithm to calculate the process required to build the similarity matrix, will bring huge storage and computation. Therefore, this paper proposes an improved affinity propagation clustering algorithm. First, add the subtraction clustering, using the density value of the data points to obtain the point of initial clusters. Then, calculate the similarity distance between the initial cluster points, and reference the idea of semi-supervised clustering, adding pairs restriction information, structure sparse similarity matrix. Finally, the cluster representative points conduct AP clustering until a suitable cluster division.Experimental results show that the algorithm allows the calculation is greatly reduced, the similarity matrix storage capacity is also reduced, and better than the original algorithm on the clustering effect and processing speed.展开更多
Systemarchitecture The Intelligent Teaching Team of the Shanghai Institute(Laboratory)of AI Education and the Institute of Curriculum and Instruction of East China Normal University collaborated to develop the High-Qu...Systemarchitecture The Intelligent Teaching Team of the Shanghai Institute(Laboratory)of AI Education and the Institute of Curriculum and Instruction of East China Normal University collaborated to develop the High-Quality Classroom Intelligent Analysis Standard system.This system was measured from the dimensions of Class Eficiency,Equity and Democracy,referred to as CEED system.展开更多
1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Int...1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.展开更多
The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the...The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the forging process.Using the previously optimized shape and initial position of preform,the influence of the friction condition(friction factor m=0.1–0.3)on material flow and cavity filling was studied by numerical method with a shear friction model.A novel filling index was defined to reflect material flow into left and right flashes and zoom in on friction-induced results.The results indicate that the workpiece moves rigidly to the right direction,with the displacement decreasing as m increases.When m<0.18,the underfilling defect will occur in the left side of strut forging,while overflow occurs in the right forging die cavity.By combining the filling index and analyses of material flow and filling status,a reasonable friction factor interval of m=0.21–0.24 can be determined.Within this interval,the cavity filling behavior demonstrates robustness,with friction fluctuations exerting minimal influence.展开更多
Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for rese...Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.展开更多
Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints,resulting in what is termed a large-scale optimization problem.Nowadays,such large-scale opti...Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints,resulting in what is termed a large-scale optimization problem.Nowadays,such large-scale optimization problems are solved using computing machines,leading to an enormous computational time being required,which may delay deriving timely solutions.Decomposition methods,which partition a large-scale optimization problem into lower-dimensional subproblems,represent a key approach to addressing time-efficiency issues.There has been significant progress in both applied mathematics and emerging artificial intelligence approaches on this front.This work aims at providing an overview of the decomposition methods from both the mathematics and computer science points of view.We also remark on the state-of-the-art developments and recent applications of the decomposition methods,and discuss the future research and development perspectives.展开更多
This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management m...This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management measures.Through practical observation and logical analysis,this article elaborates on the management connotations of large-scale machinery and equipment in highway construction,affirming its management value from different perspectives.On this basis,it carefully analyzes the problems existing in the management of large-scale machinery and equipment,providing a detailed interpretation of issues such as the weak foundation of the equipment management system and the disconnection between equipment selection and configuration from reality.Combining the manifestations of related problems,this article proposes strategies such as strengthening the institutional foundation of equipment management,selecting and configuring equipment based on actual conditions,aiming to provide references for large-scale machinery and equipment management to relevant enterprises.展开更多
The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,...The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,in combination with numerical simulation,was conducted to investigate the influence of ground fissures on a metro shield tunnel.The results indicate that the lining contact pressure at the vault increases in the hanging wall while decreases in the footwall,resulting in a two-dimensional stress state of vertical shear and axial tension-compression,and simultaneous vertical dislocation and axial tilt for the segments around the ground fissure.In addition,the damage to curved bolts includes tensile yield,flexural yield,and shear twist,leading to obvious concrete lining damage,particularly at the vault,arch bottom,and hance,indicating that the joints in these positions are weak areas.The shield tunnel orthogonal to the ground fissure ultimately experiences shear failure,suggesting that the maximum actual dislocation of ground fissure that the structure can withstand is approximately 20 cm,and five segment rings in the hanging wall and six segment rings in the footwall also need to be reinforced.This study could provide a reference for metro design in ground fissure sites.展开更多
It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the ...It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.展开更多
Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by co...Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by conducting large-scale(1:13)experiments to investigate the scour hole pattern and equilibrium scour depth around both slender and large monopiles under irregular waves.The experiments adopted KeuleganeCarpenter number(NKC)values from 1.01 to 8.89 and diffraction parameter(D/L,where D is the diameter of the monopile,and L is the wave length)values from 0.016 to 0.056.The results showed that changes in the maximum scour location and scour hole shape around a slender monopile were associated with NKC,with differences observed between irregular and regular waves.Improving the calculation of NKC enhanced the accuracy of existing scour formulae under irregular waves.The maximum scour locations around a large monopile were consistently found on both sides,regardless of NKC and D/L,but the scour hole topography was influenced by both parameters.Notably,the scour range around a large monopile was at least as large as the monopile diameter.展开更多
In 2022, South China(SC) experienced record-breaking rainfall during its first rainy season, causing severe socioeconomic losses. This study examines the large-scale circulation anomalies responsible for this extreme ...In 2022, South China(SC) experienced record-breaking rainfall during its first rainy season, causing severe socioeconomic losses. This study examines the large-scale circulation anomalies responsible for this extreme event.Analysis reveals that the lower-tropospheric cyclonic anomaly over SC plays a crucial role. This cyclonic anomaly consists of extratropical northeasterly anomalies to the north of SC and tropical southwesterly anomalies to the south. Both components were particularly intense during the 2022 first rainy season, contributing to the heavy rainfall in SC. Moreover,the lower-tropospheric cyclonic anomaly is enhanced by its counterpart in the upper troposphere, which is associated with a wave train propagating from the North Atlantic to East Asia across the mid-high latitudes of the Eurasian continent.Further analysis indicates that the extratropical wave train correlates with sea surface temperature anomalies(SSTAs) in the North Atlantic. Additionally, the SSTAs over the North Indian Ocean also play a role in enhancing the tropical southwesterlies in the lower troposphere. This study highlights the combined influence of tropical and extratropical circulation anomalies, offering a comprehensive understanding of the record-breaking rainfall.展开更多
This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is...This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is placed on data acquisition and processing methods using total stations and automated monitoring systems.Through a comprehensive analysis of lateral,longitudinal,and vertical displacement data from 26 subgrade monitoring points,catenary columns,and track sections,this research evaluates how construction activities influence railway structures.The results show that displacement variations in the subgrades,catenary columns,and tracks remained within the established alert thresholds,exhibiting stable deformation trends and indicating that any adverse environmental impact was effectively contained.Furthermore,this paper proposes an early warning mechanism based on an automated monitoring system,which can promptly detect abnormal deformations and initiate emergency response procedures,thereby ensuring the safe operation of the railway.The integration of big data analysis and deformation prediction models offers a practical foundation for future safety management in railway construction.展开更多
The research on optimization methods for constellation launch deployment strategies focused on the consideration of mission interval time constraints at the launch site.Firstly,a dynamic modeling of the constellation ...The research on optimization methods for constellation launch deployment strategies focused on the consideration of mission interval time constraints at the launch site.Firstly,a dynamic modeling of the constellation deployment process was established,and the relationship between the deployment window and the phase difference of the orbit insertion point,as well as the cost of phase adjustment after orbit insertion,was derived.Then,the combination of the constellation deployment position sequence was treated as a parameter,together with the sequence of satellite deployment intervals,as optimization variables,simplifying a highdimensional search problem within a wide range of dates to a finite-dimensional integer programming problem.An improved genetic algorithm with local search on deployment dates was introduced to optimize the launch deployment strategy.With the new description of the optimization variables,the total number of elements in the solution space was reduced by N orders of magnitude.Numerical simulation confirms that the proposed optimization method accelerates the convergence speed from hours to minutes.展开更多
The existing deep-sea sediment plume tests are mostly under small-scale static water and rarely under large-scale flowing water conditions.In this study,large-scale tank experiments of flowing water were designed and ...The existing deep-sea sediment plume tests are mostly under small-scale static water and rarely under large-scale flowing water conditions.In this study,large-scale tank experiments of flowing water were designed and conducted to investigate the morphological characteristics and concentration evolution of the sediment plumes under different discharge rates(Q)and initial sediment concentrations(c).Viscosity tests,resuspension tests and free settling tests of the sediment solution with different c values were performed to reveal the settling mechanism of the plume diffusion process.The results show that the plume diffusion morphology variation in flowing water has four stages and the plume concentration evolution has three stages.The larger the Q,the smaller the initial incidence angle at the discharge outlet,the larger the diffusion range,the poorer the stability and the more complicated the diffusion morphology.The larger the c,the larger the settling velocity,the faster the formation of high-concentration accumulation zone,the better the stability and the clearer the diffusion boundary.The research results could provide experimental data for assessing the impact of deep-sea mining on the ocean environment.展开更多
This study examined the development of technician teams on large-scale instrument platforms in universities,using the State Key Laboratory of Natural and Biomimetic Drugs in the Peking University School of Pharmaceuti...This study examined the development of technician teams on large-scale instrument platforms in universities,using the State Key Laboratory of Natural and Biomimetic Drugs in the Peking University School of Pharmaceutical Sciences as a case study.Data were collected through questionnaire surveys and interviews conducted in 2017,followed by a questionnaire survey in 2023,offering both subjective and objective insights.The evolution of the platform’s technician team over the past 5 years was analyzed,highlighting key experiences and identifying ongoing challenges.Recommendations to enhance technician team development include recruiting skilled faculty,clearly defining job responsibilities,and refining the assessment and incentive systems.展开更多
Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise re...Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.展开更多
The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context ...The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context of large-scale distributed renewable energy integration into the power grid,conventional island power grid line layouts can no longer meet actual demands.It is necessary to combine the operational characteristics of island power systems and historical load data to perform load forecasting,thereby generating power grid line layout paths.This article focuses on large-scale distributed renewable energy integration,summarizing optimization strategies for island power grid line layouts,and providing a solid guarantee for the safe and stable operation of island power systems.展开更多
This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires t...This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.展开更多
文摘This paper proposes one method of feature selection by using Bayes＇ theorem. The purpose of the proposed method is to reduce the computational complexity and increase the classification accuracy of the selected feature subsets. The dependence between two attributes （binary） is determined based on the probabilities of their joint values that contribute to positive and negative classification decisions. If opposing sets of attribute values do not lead to opposing classification decisions （zero probability）, then the two attributes are considered independent of each other, otherwise dependent, and one of them can be removed and thus the number of attributes is reduced. The process must be repeated on all combinations of attributes. The paper also evaluates the approach by comparing it with existing feature selection algorithms over 8 datasets from University of California, Irvine （UCI） machine learning databases. The proposed method shows better results in terms of number of selected features, classification accuracy, and running time than most existing algorithms.
基金supported by the European Community’s Seventh Framework Programme(No.338164)(ERC Starting Grant iHEARu)
文摘In this contribution, we present iHEARu-PLAY, an online, multi-player platform for crowdsourced database collection and labelling, including the voice analysis application (VoiLA), a free web-based speech classification tool designed to educate iHEARu-PLAY users about state-of-the-art speech analysis paradigms. Via this associated speech analysis web interface, in addition, VoiLA encourages users to take an active role in improving the service by providing labelled speech data. The platform allows users to record and upload voice samples directly from their browser, which are then analysed in a state-of-the-art classification pipeline. A set of pre-trained models targeting a range of speaker states and traits such as gender, valence, arousal, dominance, and 24 different discrete emotions is employed. The analysis results are visualised in a way that they are easily interpretable by laymen, giving users unique insights into how their voice sounds. We assess the effectiveness of iHEARu-PLAY and its integrated VoiLA feature via a series of user evaluations which indicate that it is fun and easy to use, and that it provides accurate and informative results.
基金This research has been partially supported by the national natural science foundation of China (51175169) and the national science and technology support program (2012BAF02B01).
文摘In the face of a growing number of large-scale data sets, affinity propagation clustering algorithm to calculate the process required to build the similarity matrix, will bring huge storage and computation. Therefore, this paper proposes an improved affinity propagation clustering algorithm. First, add the subtraction clustering, using the density value of the data points to obtain the point of initial clusters. Then, calculate the similarity distance between the initial cluster points, and reference the idea of semi-supervised clustering, adding pairs restriction information, structure sparse similarity matrix. Finally, the cluster representative points conduct AP clustering until a suitable cluster division.Experimental results show that the algorithm allows the calculation is greatly reduced, the similarity matrix storage capacity is also reduced, and better than the original algorithm on the clustering effect and processing speed.
基金supported by the China National Social Science Foundation(BHA220144).
文摘Systemarchitecture The Intelligent Teaching Team of the Shanghai Institute(Laboratory)of AI Education and the Institute of Curriculum and Instruction of East China Normal University collaborated to develop the High-Quality Classroom Intelligent Analysis Standard system.This system was measured from the dimensions of Class Eficiency,Equity and Democracy,referred to as CEED system.
基金supported by the National Key Research and Development Program of China(2022YFE0206700)。
文摘1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.
基金National Natural Science Foundation of China(52375378)National Key Laboratory of Metal Forming Technology and Heavy Equipment(S2308100.W12)Huxiang High-Level Talent Gathering Project of Hunan Province(2021RC5001)。
文摘The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the forging process.Using the previously optimized shape and initial position of preform,the influence of the friction condition(friction factor m=0.1–0.3)on material flow and cavity filling was studied by numerical method with a shear friction model.A novel filling index was defined to reflect material flow into left and right flashes and zoom in on friction-induced results.The results indicate that the workpiece moves rigidly to the right direction,with the displacement decreasing as m increases.When m<0.18,the underfilling defect will occur in the left side of strut forging,while overflow occurs in the right forging die cavity.By combining the filling index and analyses of material flow and filling status,a reasonable friction factor interval of m=0.21–0.24 can be determined.Within this interval,the cavity filling behavior demonstrates robustness,with friction fluctuations exerting minimal influence.
文摘Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.
基金The Australian Research Council(DP200101197,DP230101107).
文摘Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints,resulting in what is termed a large-scale optimization problem.Nowadays,such large-scale optimization problems are solved using computing machines,leading to an enormous computational time being required,which may delay deriving timely solutions.Decomposition methods,which partition a large-scale optimization problem into lower-dimensional subproblems,represent a key approach to addressing time-efficiency issues.There has been significant progress in both applied mathematics and emerging artificial intelligence approaches on this front.This work aims at providing an overview of the decomposition methods from both the mathematics and computer science points of view.We also remark on the state-of-the-art developments and recent applications of the decomposition methods,and discuss the future research and development perspectives.
文摘This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management measures.Through practical observation and logical analysis,this article elaborates on the management connotations of large-scale machinery and equipment in highway construction,affirming its management value from different perspectives.On this basis,it carefully analyzes the problems existing in the management of large-scale machinery and equipment,providing a detailed interpretation of issues such as the weak foundation of the equipment management system and the disconnection between equipment selection and configuration from reality.Combining the manifestations of related problems,this article proposes strategies such as strengthening the institutional foundation of equipment management,selecting and configuring equipment based on actual conditions,aiming to provide references for large-scale machinery and equipment management to relevant enterprises.
基金supported by the National Key Research&Development Program of China(Grant No.2023YFC3008404)the Key Laboratory of Earth Fissures Geological Disaster,Ministry of Natural Resources,China(Grant Nos.EFGD20240609 and EFGD20240610).
文摘The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,in combination with numerical simulation,was conducted to investigate the influence of ground fissures on a metro shield tunnel.The results indicate that the lining contact pressure at the vault increases in the hanging wall while decreases in the footwall,resulting in a two-dimensional stress state of vertical shear and axial tension-compression,and simultaneous vertical dislocation and axial tilt for the segments around the ground fissure.In addition,the damage to curved bolts includes tensile yield,flexural yield,and shear twist,leading to obvious concrete lining damage,particularly at the vault,arch bottom,and hance,indicating that the joints in these positions are weak areas.The shield tunnel orthogonal to the ground fissure ultimately experiences shear failure,suggesting that the maximum actual dislocation of ground fissure that the structure can withstand is approximately 20 cm,and five segment rings in the hanging wall and six segment rings in the footwall also need to be reinforced.This study could provide a reference for metro design in ground fissure sites.
基金supported by the Fundamental Research Funds for the Central Universities(Grant Nos.lzujbky-2021-62 and lzujbky-2024-jdzx06)the National Natural Science Foundation of China(Grant No.12247101)+1 种基金the Natural Science Foundation of Gansu Province,China(Grant Nos.22JR5RA389 and 23JRRA1740)the‘111 Center’Fund(Grant No.B20063).
文摘It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.
基金supported by the National Nature Science Foundation of China National Outstanding Youth Science Fund Project(Grant No.52122109)the National Natural Science Foundation of China(Grants No.51861165102 and 52039005).
文摘Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by conducting large-scale(1:13)experiments to investigate the scour hole pattern and equilibrium scour depth around both slender and large monopiles under irregular waves.The experiments adopted KeuleganeCarpenter number(NKC)values from 1.01 to 8.89 and diffraction parameter(D/L,where D is the diameter of the monopile,and L is the wave length)values from 0.016 to 0.056.The results showed that changes in the maximum scour location and scour hole shape around a slender monopile were associated with NKC,with differences observed between irregular and regular waves.Improving the calculation of NKC enhanced the accuracy of existing scour formulae under irregular waves.The maximum scour locations around a large monopile were consistently found on both sides,regardless of NKC and D/L,but the scour hole topography was influenced by both parameters.Notably,the scour range around a large monopile was at least as large as the monopile diameter.
基金Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004)National Natural Science Foundation of China (42275041)Hainan Province Science and Technology Special Fund (SOLZSKY2025006)。
文摘In 2022, South China(SC) experienced record-breaking rainfall during its first rainy season, causing severe socioeconomic losses. This study examines the large-scale circulation anomalies responsible for this extreme event.Analysis reveals that the lower-tropospheric cyclonic anomaly over SC plays a crucial role. This cyclonic anomaly consists of extratropical northeasterly anomalies to the north of SC and tropical southwesterly anomalies to the south. Both components were particularly intense during the 2022 first rainy season, contributing to the heavy rainfall in SC. Moreover,the lower-tropospheric cyclonic anomaly is enhanced by its counterpart in the upper troposphere, which is associated with a wave train propagating from the North Atlantic to East Asia across the mid-high latitudes of the Eurasian continent.Further analysis indicates that the extratropical wave train correlates with sea surface temperature anomalies(SSTAs) in the North Atlantic. Additionally, the SSTAs over the North Indian Ocean also play a role in enhancing the tropical southwesterlies in the lower troposphere. This study highlights the combined influence of tropical and extratropical circulation anomalies, offering a comprehensive understanding of the record-breaking rainfall.
文摘This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is placed on data acquisition and processing methods using total stations and automated monitoring systems.Through a comprehensive analysis of lateral,longitudinal,and vertical displacement data from 26 subgrade monitoring points,catenary columns,and track sections,this research evaluates how construction activities influence railway structures.The results show that displacement variations in the subgrades,catenary columns,and tracks remained within the established alert thresholds,exhibiting stable deformation trends and indicating that any adverse environmental impact was effectively contained.Furthermore,this paper proposes an early warning mechanism based on an automated monitoring system,which can promptly detect abnormal deformations and initiate emergency response procedures,thereby ensuring the safe operation of the railway.The integration of big data analysis and deformation prediction models offers a practical foundation for future safety management in railway construction.
文摘The research on optimization methods for constellation launch deployment strategies focused on the consideration of mission interval time constraints at the launch site.Firstly,a dynamic modeling of the constellation deployment process was established,and the relationship between the deployment window and the phase difference of the orbit insertion point,as well as the cost of phase adjustment after orbit insertion,was derived.Then,the combination of the constellation deployment position sequence was treated as a parameter,together with the sequence of satellite deployment intervals,as optimization variables,simplifying a highdimensional search problem within a wide range of dates to a finite-dimensional integer programming problem.An improved genetic algorithm with local search on deployment dates was introduced to optimize the launch deployment strategy.With the new description of the optimization variables,the total number of elements in the solution space was reduced by N orders of magnitude.Numerical simulation confirms that the proposed optimization method accelerates the convergence speed from hours to minutes.
基金supported by the Major Project of Hunan Natural Science Foundation,China(No.2021JC0010)the National Natural Science Foundation of China(No.51274251)。
文摘The existing deep-sea sediment plume tests are mostly under small-scale static water and rarely under large-scale flowing water conditions.In this study,large-scale tank experiments of flowing water were designed and conducted to investigate the morphological characteristics and concentration evolution of the sediment plumes under different discharge rates(Q)and initial sediment concentrations(c).Viscosity tests,resuspension tests and free settling tests of the sediment solution with different c values were performed to reveal the settling mechanism of the plume diffusion process.The results show that the plume diffusion morphology variation in flowing water has four stages and the plume concentration evolution has three stages.The larger the Q,the smaller the initial incidence angle at the discharge outlet,the larger the diffusion range,the poorer the stability and the more complicated the diffusion morphology.The larger the c,the larger the settling velocity,the faster the formation of high-concentration accumulation zone,the better the stability and the clearer the diffusion boundary.The research results could provide experimental data for assessing the impact of deep-sea mining on the ocean environment.
文摘This study examined the development of technician teams on large-scale instrument platforms in universities,using the State Key Laboratory of Natural and Biomimetic Drugs in the Peking University School of Pharmaceutical Sciences as a case study.Data were collected through questionnaire surveys and interviews conducted in 2017,followed by a questionnaire survey in 2023,offering both subjective and objective insights.The evolution of the platform’s technician team over the past 5 years was analyzed,highlighting key experiences and identifying ongoing challenges.Recommendations to enhance technician team development include recruiting skilled faculty,clearly defining job responsibilities,and refining the assessment and incentive systems.
基金supported by the National Natural Science Foundation of China(Grant Nos.12302435 and 12221002)。
文摘Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.
文摘The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context of large-scale distributed renewable energy integration into the power grid,conventional island power grid line layouts can no longer meet actual demands.It is necessary to combine the operational characteristics of island power systems and historical load data to perform load forecasting,thereby generating power grid line layout paths.This article focuses on large-scale distributed renewable energy integration,summarizing optimization strategies for island power grid line layouts,and providing a solid guarantee for the safe and stable operation of island power systems.
基金supported by the National Natural Science Foundation of China under Grant 62073190the Science Center Program of National Natural Science Foundation of China under Grant 62188101.
文摘This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.
