Recommendation system can greatly alleviate the "information overload" in the big data era. Existing recommendation methods, however, typically focus on predicting missing rating values via analyzing user-it...Recommendation system can greatly alleviate the "information overload" in the big data era. Existing recommendation methods, however, typically focus on predicting missing rating values via analyzing user-item dualistic relationship, which neglect an important fact that the latent interests of users can influence their rating behaviors. Moreover, traditional recommendation methods easily suffer from the high dimensional problem and cold-start problem. To address these challenges, in this paper, we propose a PBUED(PLSA-Based Uniform Euclidean Distance) scheme, which utilizes topic model and uniform Euclidean distance to recommend the suitable items for users. The solution first employs probabilistic latent semantic analysis(PLSA) to extract users' interests, users with different interests are divided into different subgroups. Then, the uniform Euclidean distance is adopted to compute the users' similarity in the same interest subset; finally, the missing rating values of data are predicted via aggregating similar neighbors' ratings. We evaluate PBUED on two datasets and experimental results show PBUED can lead to better predicting performance and ranking performance than other approaches.展开更多
In this paper, the method based on uniform design and neural network is proposed to model the complex system. In order to express the system characteristics all round, uniform design method is used to choose the model...In this paper, the method based on uniform design and neural network is proposed to model the complex system. In order to express the system characteristics all round, uniform design method is used to choose the modeling samples and obtain the overall information of the system;for the purpose of modeling the system or its characteristics, the artificial neural network is used to construct the model. Experiment indicates that this method can model the complex system effectively.展开更多
Convective storms and lightning are among the most important weather phenomena that are challenging to forecast.In this study,a novel multi-task learning(MTL)encoder-decoder U-net neural network was developed to forec...Convective storms and lightning are among the most important weather phenomena that are challenging to forecast.In this study,a novel multi-task learning(MTL)encoder-decoder U-net neural network was developed to forecast convective storms and lightning with lead times for up to 90 min,using GOES-16 geostationary satellite infrared brightness temperatures(IRBTs),lightning flashes from Geostationary Lightning Mapper(GLM),and vertically integrated liquid(VIL)from Next Generation Weather Radar(NEXRAD).To cope with the heavily skewed distribution of lightning data,a spatiotemporal exponent-weighted loss function and log-transformed lightning normalization approach were developed.The effects of MTL,single-task learning(STL),and IRBTs as auxiliary input features on convection and lightning nowcasting were investigated.The results showed that normalizing the heavily skew-distributed lightning data along with a log-transformation dramatically outperforms the min-max normalization method for nowcasting an intense lightning event.The MTL model significantly outperformed the STL model for both lightning nowcasting and VIL nowcasting,particularly for intense lightning events.The MTL also helped delay the lightning forecast performance decay with the lead times.Furthermore,incorporating satellite IRBTs as auxiliary input features substantially improved lightning nowcasting,but produced little difference in VIL forecasting.Finally,the MTL model performed better for forecasting both lightning and the VIL of organized convective storms than for isolated cells.展开更多
The cast preformed forming process(CPFP) is increasingly considered and applied in the metal forming industries due to its short process, low cost, and environmental friendliness, especially in the aerospace field. Ho...The cast preformed forming process(CPFP) is increasingly considered and applied in the metal forming industries due to its short process, low cost, and environmental friendliness, especially in the aerospace field. However, how to establish a unified model of a non-uniform as-cast billet depicting the flow stress and microstructure evolution behaviors during hot working is the key to microstructure prediction and parameter optimization of the CPFP. In this work, hot compression tests are performed using a non-uniform as-cast 42 CrMo billet at 1123–1423 K and 0.01–1sà1. The effect laws of the non-uniform state of the as-cast billet with different initial grain sizes on the flow stress and microstructure are revealed deeply. Based on experimental results, a unified model of flow stress and grain size evolutions is developed by the internal variable modeling method. Verified results show that the model can well describe the responses of the flow stress and microstructure to deformation conditions and initial grain sizes. To further evaluate its reliability, the unified model is applied to FE simulation of the cast preformed ring rolling process.The predictions of the rolling force and grain size indicate that it could well describe the flow stress and microstructure evolutions during the process.展开更多
Hot compression tests of Mg–11 Gd–4 Y–2 Zn–0.4 Zr alloy(GWZK114)were conducted at a deformation temperature range of 300–500°C and a strain rate range of 0.01–10.0 s-1.Based on systematic microstructure obs...Hot compression tests of Mg–11 Gd–4 Y–2 Zn–0.4 Zr alloy(GWZK114)were conducted at a deformation temperature range of 300–500°C and a strain rate range of 0.01–10.0 s-1.Based on systematic microstructure observation,it is confirmed that long period stacking ordered(LPSO)phase displays essential and evolving roles on the dynamic recrystallization(DRX)behavior.The results indicate that the plastic deformation is mainly coordinated by simultaneous exist of LPSO kinking of lamella 14 H-LPSO phase and DRX at 350–450℃,and DRX at 500℃.Further,it is found that the LPSO kinking induced during 350–450℃can delay the DRX.A phenomenological DRX model of GWZK114 alloy is established to be XDRX=1.exp[-0.5((ε-εc)/ε^*)0.91].Non-uniform distribution of plastic strain during compression was considered via finite element method and it ensures a good prediction of DRX fraction under a large plastic strain.Meanwhile,an enhanced DRX model,taking its formulation as XDRX={1.exp[-0.5((ε-εc)/ε*)0.91]}(T/(226.8)-1)n,n=3.82ε0.083,is proposed for the first time to capture the hindering effect of 14 H-LPSO kinking on DRX behavior.The predicted results of this enhanced DRX model agree well with the experimental cases,where 14 H-LPSO kinking is dominated or partially involved(300–450℃).Besides,a size model of DRX grains is also established and can depict the evolution of DRX grain size for all the investigated compression conditions with accounting for temperature rising at high strain rates(5 s^-1 and 10 s^-1).展开更多
For two-way contingency tables with ordered categories, the present paper gives a theorem that the independence model holds if and only if the logit uniform association model holds and equality of concordance and disc...For two-way contingency tables with ordered categories, the present paper gives a theorem that the independence model holds if and only if the logit uniform association model holds and equality of concordance and discordance for all pairs of adjacent rows and all dichotomous collapsing of the columns holds. Using the theorem, we analyze the cross-classification of duodenal ulcer patients according to operation and dumping severity.展开更多
The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spa...The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spatial-temporal structures,and the deep learning model can fully describe the potential semantic structure of human motion.To improve the authenticity of the generated human motion sequences,we propose a multi-task motion generation model that consists of a discriminator and a generator.The discriminator classifies motion sequences into different styles according to their similarity to the mean spatial-temporal templates from motion sequences of 17 crucial human joints in three-freedom degrees.And target motion sequences are created with these styles by the generator.Unlike traditional related works,our model can handle multiple tasks,such as identifying styles and generating data.In addition,by extracting 17 crucial joints from 29 human joints,our model avoids data redundancy and improves the accuracy of model recognition.The experimental results show that the discriminator of the model can effectively recognize diversified movements,and the generated data can correctly fit the actual data.The combination of discriminator and generator solves the problem of low reuse rate of motion data,and the generated motion sequences are more suitable for actual movement.展开更多
Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover e...Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.展开更多
Stability, boundedness and persistence are three important aspects for an ecological model. In this paper, a further analysis of a class of anaerobic digestion ecological models is performed. Based on the Liupunov Met...Stability, boundedness and persistence are three important aspects for an ecological model. In this paper, a further analysis of a class of anaerobic digestion ecological models is performed. Based on the Liupunov Method, the local stability of all equilibria in the system is got. According to the vector fields described by the system, the proof of the boundedness of the solution on the anaerobic digestion processes is completed in three steps. The method proposed in the discussion on the boundedness can be generalized to the similar problems. Results in this paper give information on how to run the ecological system well by adjusting the system parameters.展开更多
Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-...Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.展开更多
In this paper, the influencing factors that affect few-mode and multi core optical fiber channel are analyzed in a comprehensive way. The theoretical modeling and computer simulation of the information channel are car...In this paper, the influencing factors that affect few-mode and multi core optical fiber channel are analyzed in a comprehensive way. The theoretical modeling and computer simulation of the information channel are carried out and then the modeling scheme of few-mode multicore optical fiber channel based on non-uniform mode field distribution is put forward. The proposed modeling scheme can not only exponentially increases the system capacity through fewmode multi-core optical fiber channel, but has better transmission performance compared to the channel of the same type to the uniform channel revealing from the simulation results.展开更多
The mineralization process of microbial-induced calcium carbonate precipitation(MICP)is influenced by many factors,and the uniformity of the calcium carbonate precipitation has become the main focus and challenge for ...The mineralization process of microbial-induced calcium carbonate precipitation(MICP)is influenced by many factors,and the uniformity of the calcium carbonate precipitation has become the main focus and challenge for MICP technology.In this study,the uniformity of the saturated calcareous sand treated with MICP was in-vestigated through one-dimensional calcareous sand column tests and model tests.The coefficient of variation was employed in one-dimensional sand column tests to investigate the impact of injection rate,cementation solution concentration,and number of injection cycles on the uniformity of the MICP treatment.Additionally,model tests were conducted to investigate the impact of injection pressure and methods on the treatment range and uniformity under three-dimensional seepage conditions.Test results demonstrate that the reinforcement strength and uniformity are significantly influenced by the injection rate of the cementation solution,with a rate of 3 mL/min,yielding a favorable treatment effect.Excessive concentration of the cementation solution can lead to significant non-uniformity and a reduction in the compressive strength of MICP-treated samples.Conversely,excessively low concentrations may result in decreased bonding efficiency.Among the four considered con-centrations,0.5 mol/L and 1 mol/L exhibit superior reinforcing effects.The morphological development of calcareous sandy foundation reinforcement is associated with the spatial distribution pattern of the bacterial solution,exhibiting a relatively larger reinforcement area in proximity to the lower region of the model and a gradually decreasing range towards the upper part.Under three-dimensional seepage conditions,in addition to the non-uniform radial cementation along the injection pipe,there is also vertical heterogeneity of cementation along the length of the injection pipe due to gravitational effects,resulting in preferential deposition of calcium carbonate at the lower section,The application of injection pressure and a double-pipe circulation injection method can mitigate the accumulation of bacterial solution and cementation solution at the bottom,thereby improving the reinforcement range and uniformity.展开更多
Long-duration energy storage has become critical for renewable energy integration.While redox flow batteries,especially vanadium-based systems,are scaling up in capacity,their performance at the stack level remains in...Long-duration energy storage has become critical for renewable energy integration.While redox flow batteries,especially vanadium-based systems,are scaling up in capacity,their performance at the stack level remains insufficiently optimized,demanding more profound mechanistic studies and engineering refinements.To address the difficulties in resolving the flow inhomogeneity at the stack scale,this study establishes a multi-physics field coupling model and analyzes the pressure distributions,flow rate differences,active substance concentration,and electrochemical characteristics.The results show that the uneven cell pressure distribution is a key factor affecting the consistency of the system performance,and the increase in the flow rate improves the reactant homogeneity,with both the average concentration and the uniformity factor increasing with the flow rate.In contrast,high current densities lead to an increased imbalance between electrochemical depletion and reactant replenishment,resulting in a significant decrease in reactant concentration in the under-ribs region.In addition,a higher flow rate can expand the high-current-density region where the stack operates efficiently.This study provides a theoretical basis for optimizing the design of the stack components.展开更多
Scour around bridge pier foundations is a complex phenomenon that can threaten structural stability.Accurate prediction of scour depth around compound piers remains challenging for bridge engineers.This study investig...Scour around bridge pier foundations is a complex phenomenon that can threaten structural stability.Accurate prediction of scour depth around compound piers remains challenging for bridge engineers.This study investigated the effect of foundation elevation on scour around compound piers and developed reliable scour depth prediction models for economical foundation design.Experiments were conducted under clear-water conditions using two circular piers:(1)a uniform pier(with a diameter of D)and(2)a compound pier consisting of a uniform pier resting on a circular foundation(with a foundation diameter(D_(f))of 2D)positioned at various elevations(Z)relative to the channel bed.Results showed that foundation elevation significantly affected scour depth.Foundations at or below the bed(Z/D≥0)reduced scour,while those projecting into the flow field(Z/D<0)increased scour.The optimal foundation elevation was found to be 0.1D below the bed level,yielding a 57%reduction in scour depth compared to the uniform pier due to its shielding effect against downflow and horseshoe vortices.In addition,regression,artificial neural network(ANN),and M5 model tree models were developed using experimental data from this and previous studies.The M5 model outperformed the traditional HEC-18 equation,regression,and ANN models,with a coefficient of determination greater than 0.85.Sensitivity analysis indicated that flow depth,foundation elevation,and diameter significantly influenced scour depth prediction,whereas sediment size had a lesser impact.展开更多
The received signal of the polarization sensitive array is proved to have trilinear model characteristics. The blind parallel factor（PARAFAC） signal detection algorithm for the polarization sensitive array is propos...The received signal of the polarization sensitive array is proved to have trilinear model characteristics. The blind parallel factor（PARAFAC） signal detection algorithm for the polarization sensitive array is proposed. The trilinear alternating least square （TALS） algorithm is used to abtain the source matrix, and then the matrix is judged. Simulation results show that the bit error rate （BER） of the detection algorithm is close to that of the non-blind decorrelating method and the algorithm works well under the array error condition. BER difference between the non-blind method and this algorithm is less than 2 dB under a high SNR. The algorithm is blind and robust. The channel fading, the direction of arrive（DOA） imformation and the polarization information are needless in the algorithm.展开更多
A modified mixed strengthening model was proposed for describing the yield strength of particle reinforced aluminum matrix composites.The strengthening mechanisms of the composites were analyzed based on the microstru...A modified mixed strengthening model was proposed for describing the yield strength of particle reinforced aluminum matrix composites.The strengthening mechanisms of the composites were analyzed based on the microstructures and compression mechanical properties.The distribution uniformity of reinforcements and cooperation relationship among dislocation mechanisms were considered in the modified mixed strengthening model by introducing a distribution uniformity factor u and a cooperation coefficient fc,respectively.The results show that the modified mixed strengthening model can accurately describe the yield strengths of Al3Ti/2024Al composites with a relative deviation less than1.2%,which is much more accurate than other strengthening models.The modified mixed model can also be used to predict the yield strength of Al3Ti/2024Al composites with different fractions of reinforcements.展开更多
The global nuclear mass based on the macroscopic-microscopic model was studied by applying a newly designed multi-task learning artificial neural network(MTL-ANN). First, the reported nuclear binding energies of 2095 ...The global nuclear mass based on the macroscopic-microscopic model was studied by applying a newly designed multi-task learning artificial neural network(MTL-ANN). First, the reported nuclear binding energies of 2095 nuclei(Z ≥ 8, N ≥ 8) released in the latest Atomic Mass Evaluation AME2020 and the deviations between the fitting result of the liquid drop model(LDM)and data from AME2020 for each nucleus were obtained.To compensate for the deviations and investigate the possible ignored physics in the LDM, the MTL-ANN method was introduced in the model. Compared to the single-task learning(STL) method, this new network has a powerful ability to simultaneously learn multi-nuclear properties,such as the binding energies and single neutron and proton separation energies. Moreover, it is highly effective in reducing the risk of overfitting and achieving better predictions. Consequently, good predictions can be obtained using this nuclear mass model for both the training and validation datasets and for the testing dataset. In detail, the global root mean square(RMS) of the binding energy is effectively reduced from approximately 2.4 MeV of LDM to the current 0.2 MeV, and the RMS of Sn, Spcan also reach approximately 0.2 MeV. Moreover, compared to STL, for the training and validation sets, 3-9% improvement can be achieved with the binding energy, and 20-30% improvement for S_(n), S_(p);for the testing sets, the reduction in deviations can even reach 30-40%, which significantly illustrates the advantage of the current MTL.展开更多
Grinding is a crucial process in machining workpieces because it plays a vital role in achieving the desired precision and surface quality.However,a significant technical challenge in grinding is the potential increas...Grinding is a crucial process in machining workpieces because it plays a vital role in achieving the desired precision and surface quality.However,a significant technical challenge in grinding is the potential increase in temperature due to high specific energy,which can lead to surface thermal damage.Therefore,ensuring control over the surface integrity of workpieces during grinding becomes a critical concern.This necessitates the development of temperature field models that consider various parameters,such as workpiece materials,grinding wheels,grinding parameters,cooling methods,and media,to guide industrial production.This study thoroughly analyzes and summarizes grinding temperature field models.First,the theory of the grinding temperature field is investigated,classifying it into traditional models based on a continuous belt heat source and those based on a discrete heat source,depending on whether the heat source is uniform and continuous.Through this examination,a more accurate grinding temperature model that closely aligns with practical grinding conditions is derived.Subsequently,various grinding thermal models are summarized,including models for the heat source distribution,energy distribution proportional coefficient,and convective heat transfer coefficient.Through comprehensive research,the most widely recognized,utilized,and accurate model for each category is identified.The application of these grinding thermal models is reviewed,shedding light on the governing laws that dictate the influence of the heat source distribution,heat distribution,and convective heat transfer in the grinding arc zone on the grinding temperature field.Finally,considering the current issues in the field of grinding temperature,potential future research directions are proposed.The aim of this study is to provide theoretical guidance and technical support for predicting workpiece temperature and improving surface integrity.展开更多
This paper proposes a systematic method, integrating the uniform design (UD) of experiments and quantum-behaved particle swarm optimization (QPSO), to solve the problem of a robust design for a railway vehicle suspens...This paper proposes a systematic method, integrating the uniform design (UD) of experiments and quantum-behaved particle swarm optimization (QPSO), to solve the problem of a robust design for a railway vehicle suspension system. Based on the new nonlinear creep model derived from combining Hertz contact theory, Kalker's linear theory and a heuristic nonlinear creep model, the modeling and dynamic analysis of a 24 degree-of-freedom railway vehicle system were investigated. The Lyapunov indirect method was used to examine the effects of suspension parameters, wheel conicities and wheel rolling radii on critical hunting speeds. Generally, the critical hunting speeds of a vehicle system resulting from worn wheels with different wheel rolling radii are lower than those of a vehicle system having original wheels without different wheel rolling radii. Because of worn wheels, the critical hunting speed of a running railway vehicle substantially declines over the long term. For safety reasons, it is necessary to design the suspension system parameters to increase the robustness of the system and decrease the sensitive of wheel noises. By applying UD and QPSO, the nominal-the-best signal-to-noise ratio of the system was increased from -48.17 to -34.05 dB. The rate of improvement was 29.31%. This study has demonstrated that the integration of UD and QPSO can successfully reveal the optimal solution of suspension parameters for solving the robust design problem of a railway vehicle suspension system.展开更多
基金supported in part by the National High‐tech R&D Program of China (863 Program) under Grant No. 2013AA102301technological project of Henan province (162102210214)
文摘Recommendation system can greatly alleviate the "information overload" in the big data era. Existing recommendation methods, however, typically focus on predicting missing rating values via analyzing user-item dualistic relationship, which neglect an important fact that the latent interests of users can influence their rating behaviors. Moreover, traditional recommendation methods easily suffer from the high dimensional problem and cold-start problem. To address these challenges, in this paper, we propose a PBUED(PLSA-Based Uniform Euclidean Distance) scheme, which utilizes topic model and uniform Euclidean distance to recommend the suitable items for users. The solution first employs probabilistic latent semantic analysis(PLSA) to extract users' interests, users with different interests are divided into different subgroups. Then, the uniform Euclidean distance is adopted to compute the users' similarity in the same interest subset; finally, the missing rating values of data are predicted via aggregating similar neighbors' ratings. We evaluate PBUED on two datasets and experimental results show PBUED can lead to better predicting performance and ranking performance than other approaches.
文摘In this paper, the method based on uniform design and neural network is proposed to model the complex system. In order to express the system characteristics all round, uniform design method is used to choose the modeling samples and obtain the overall information of the system;for the purpose of modeling the system or its characteristics, the artificial neural network is used to construct the model. Experiment indicates that this method can model the complex system effectively.
基金supported by the Science and Technology Grant No.520120210003,Jibei Electric Power Company of the State Grid Corporation of China。
文摘Convective storms and lightning are among the most important weather phenomena that are challenging to forecast.In this study,a novel multi-task learning(MTL)encoder-decoder U-net neural network was developed to forecast convective storms and lightning with lead times for up to 90 min,using GOES-16 geostationary satellite infrared brightness temperatures(IRBTs),lightning flashes from Geostationary Lightning Mapper(GLM),and vertically integrated liquid(VIL)from Next Generation Weather Radar(NEXRAD).To cope with the heavily skewed distribution of lightning data,a spatiotemporal exponent-weighted loss function and log-transformed lightning normalization approach were developed.The effects of MTL,single-task learning(STL),and IRBTs as auxiliary input features on convection and lightning nowcasting were investigated.The results showed that normalizing the heavily skew-distributed lightning data along with a log-transformation dramatically outperforms the min-max normalization method for nowcasting an intense lightning event.The MTL model significantly outperformed the STL model for both lightning nowcasting and VIL nowcasting,particularly for intense lightning events.The MTL also helped delay the lightning forecast performance decay with the lead times.Furthermore,incorporating satellite IRBTs as auxiliary input features substantially improved lightning nowcasting,but produced little difference in VIL forecasting.Finally,the MTL model performed better for forecasting both lightning and the VIL of organized convective storms than for isolated cells.
基金supported by the National Natural Science Foundation of China (No’s. 51575448 and 51135007)
文摘The cast preformed forming process(CPFP) is increasingly considered and applied in the metal forming industries due to its short process, low cost, and environmental friendliness, especially in the aerospace field. However, how to establish a unified model of a non-uniform as-cast billet depicting the flow stress and microstructure evolution behaviors during hot working is the key to microstructure prediction and parameter optimization of the CPFP. In this work, hot compression tests are performed using a non-uniform as-cast 42 CrMo billet at 1123–1423 K and 0.01–1sà1. The effect laws of the non-uniform state of the as-cast billet with different initial grain sizes on the flow stress and microstructure are revealed deeply. Based on experimental results, a unified model of flow stress and grain size evolutions is developed by the internal variable modeling method. Verified results show that the model can well describe the responses of the flow stress and microstructure to deformation conditions and initial grain sizes. To further evaluate its reliability, the unified model is applied to FE simulation of the cast preformed ring rolling process.The predictions of the rolling force and grain size indicate that it could well describe the flow stress and microstructure evolutions during the process.
文摘Hot compression tests of Mg–11 Gd–4 Y–2 Zn–0.4 Zr alloy(GWZK114)were conducted at a deformation temperature range of 300–500°C and a strain rate range of 0.01–10.0 s-1.Based on systematic microstructure observation,it is confirmed that long period stacking ordered(LPSO)phase displays essential and evolving roles on the dynamic recrystallization(DRX)behavior.The results indicate that the plastic deformation is mainly coordinated by simultaneous exist of LPSO kinking of lamella 14 H-LPSO phase and DRX at 350–450℃,and DRX at 500℃.Further,it is found that the LPSO kinking induced during 350–450℃can delay the DRX.A phenomenological DRX model of GWZK114 alloy is established to be XDRX=1.exp[-0.5((ε-εc)/ε^*)0.91].Non-uniform distribution of plastic strain during compression was considered via finite element method and it ensures a good prediction of DRX fraction under a large plastic strain.Meanwhile,an enhanced DRX model,taking its formulation as XDRX={1.exp[-0.5((ε-εc)/ε*)0.91]}(T/(226.8)-1)n,n=3.82ε0.083,is proposed for the first time to capture the hindering effect of 14 H-LPSO kinking on DRX behavior.The predicted results of this enhanced DRX model agree well with the experimental cases,where 14 H-LPSO kinking is dominated or partially involved(300–450℃).Besides,a size model of DRX grains is also established and can depict the evolution of DRX grain size for all the investigated compression conditions with accounting for temperature rising at high strain rates(5 s^-1 and 10 s^-1).
文摘For two-way contingency tables with ordered categories, the present paper gives a theorem that the independence model holds if and only if the logit uniform association model holds and equality of concordance and discordance for all pairs of adjacent rows and all dichotomous collapsing of the columns holds. Using the theorem, we analyze the cross-classification of duodenal ulcer patients according to operation and dumping severity.
文摘The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spatial-temporal structures,and the deep learning model can fully describe the potential semantic structure of human motion.To improve the authenticity of the generated human motion sequences,we propose a multi-task motion generation model that consists of a discriminator and a generator.The discriminator classifies motion sequences into different styles according to their similarity to the mean spatial-temporal templates from motion sequences of 17 crucial human joints in three-freedom degrees.And target motion sequences are created with these styles by the generator.Unlike traditional related works,our model can handle multiple tasks,such as identifying styles and generating data.In addition,by extracting 17 crucial joints from 29 human joints,our model avoids data redundancy and improves the accuracy of model recognition.The experimental results show that the discriminator of the model can effectively recognize diversified movements,and the generated data can correctly fit the actual data.The combination of discriminator and generator solves the problem of low reuse rate of motion data,and the generated motion sequences are more suitable for actual movement.
文摘Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.
基金Supported by the National Natural Science Foundation of China (No.60372012) and NSF of Chongqing (No.0831)
文摘Stability, boundedness and persistence are three important aspects for an ecological model. In this paper, a further analysis of a class of anaerobic digestion ecological models is performed. Based on the Liupunov Method, the local stability of all equilibria in the system is got. According to the vector fields described by the system, the proof of the boundedness of the solution on the anaerobic digestion processes is completed in three steps. The method proposed in the discussion on the boundedness can be generalized to the similar problems. Results in this paper give information on how to run the ecological system well by adjusting the system parameters.
基金The National Natural Science Foundation of China(62136008,62293541)The Beijing Natural Science Foundation(4232056)The Beijing Nova Program(20240484514).
文摘Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.
基金supports from National High Technology 863 Program of China(No.2013AA013403,2015AA015501,2015AA015502,2015AA015504)National NSFC(No.61425022/61522501/61307086/61475024/61275158/61201151/61275074/61372109)+4 种基金Beijing Nova Program(No.Z141101001814048)Beijing Excellent Ph.D.Thesis Guidance Foundation(No.20121001302)the Universities Ph.D.Special Research Funds(No.20120005110003/20120005120007)Fund of State Key Laboratory of IPOC(BUPT)P.R.China
文摘In this paper, the influencing factors that affect few-mode and multi core optical fiber channel are analyzed in a comprehensive way. The theoretical modeling and computer simulation of the information channel are carried out and then the modeling scheme of few-mode multicore optical fiber channel based on non-uniform mode field distribution is put forward. The proposed modeling scheme can not only exponentially increases the system capacity through fewmode multi-core optical fiber channel, but has better transmission performance compared to the channel of the same type to the uniform channel revealing from the simulation results.
基金support of Natural Science Foundation of China(Grant No.52108324,No.52008207,and No.52108298)for conducting this study.
文摘The mineralization process of microbial-induced calcium carbonate precipitation(MICP)is influenced by many factors,and the uniformity of the calcium carbonate precipitation has become the main focus and challenge for MICP technology.In this study,the uniformity of the saturated calcareous sand treated with MICP was in-vestigated through one-dimensional calcareous sand column tests and model tests.The coefficient of variation was employed in one-dimensional sand column tests to investigate the impact of injection rate,cementation solution concentration,and number of injection cycles on the uniformity of the MICP treatment.Additionally,model tests were conducted to investigate the impact of injection pressure and methods on the treatment range and uniformity under three-dimensional seepage conditions.Test results demonstrate that the reinforcement strength and uniformity are significantly influenced by the injection rate of the cementation solution,with a rate of 3 mL/min,yielding a favorable treatment effect.Excessive concentration of the cementation solution can lead to significant non-uniformity and a reduction in the compressive strength of MICP-treated samples.Conversely,excessively low concentrations may result in decreased bonding efficiency.Among the four considered con-centrations,0.5 mol/L and 1 mol/L exhibit superior reinforcing effects.The morphological development of calcareous sandy foundation reinforcement is associated with the spatial distribution pattern of the bacterial solution,exhibiting a relatively larger reinforcement area in proximity to the lower region of the model and a gradually decreasing range towards the upper part.Under three-dimensional seepage conditions,in addition to the non-uniform radial cementation along the injection pipe,there is also vertical heterogeneity of cementation along the length of the injection pipe due to gravitational effects,resulting in preferential deposition of calcium carbonate at the lower section,The application of injection pressure and a double-pipe circulation injection method can mitigate the accumulation of bacterial solution and cementation solution at the bottom,thereby improving the reinforcement range and uniformity.
基金supported by National Natural Science Foundation of China(No.524B2078,12426307,51906203)Guangdong Major Project of Basic and Applied Basic Research(2023B0303000002)+6 种基金Guangdong Basic and Applied Basic Research Foundation(2023B1515120005)Natural Science Foundation of Shenzhen(JCYJ20241202125327036,JCYJ20240813100103005)Shenzhen Engineering Research Center of Redox Flow Battery for Energy Storage(XMHT20230208003)Research Project on Medium-and Long-Duration Flow Battery Energy Storage Technology(2024KJTW0015)China Association for Science and Technology(OR2308010)High level of special funds(G03034K001)supported by the Center for Computational Science and Engineering at the Southern University of Science and Technology.
文摘Long-duration energy storage has become critical for renewable energy integration.While redox flow batteries,especially vanadium-based systems,are scaling up in capacity,their performance at the stack level remains insufficiently optimized,demanding more profound mechanistic studies and engineering refinements.To address the difficulties in resolving the flow inhomogeneity at the stack scale,this study establishes a multi-physics field coupling model and analyzes the pressure distributions,flow rate differences,active substance concentration,and electrochemical characteristics.The results show that the uneven cell pressure distribution is a key factor affecting the consistency of the system performance,and the increase in the flow rate improves the reactant homogeneity,with both the average concentration and the uniformity factor increasing with the flow rate.In contrast,high current densities lead to an increased imbalance between electrochemical depletion and reactant replenishment,resulting in a significant decrease in reactant concentration in the under-ribs region.In addition,a higher flow rate can expand the high-current-density region where the stack operates efficiently.This study provides a theoretical basis for optimizing the design of the stack components.
文摘Scour around bridge pier foundations is a complex phenomenon that can threaten structural stability.Accurate prediction of scour depth around compound piers remains challenging for bridge engineers.This study investigated the effect of foundation elevation on scour around compound piers and developed reliable scour depth prediction models for economical foundation design.Experiments were conducted under clear-water conditions using two circular piers:(1)a uniform pier(with a diameter of D)and(2)a compound pier consisting of a uniform pier resting on a circular foundation(with a foundation diameter(D_(f))of 2D)positioned at various elevations(Z)relative to the channel bed.Results showed that foundation elevation significantly affected scour depth.Foundations at or below the bed(Z/D≥0)reduced scour,while those projecting into the flow field(Z/D<0)increased scour.The optimal foundation elevation was found to be 0.1D below the bed level,yielding a 57%reduction in scour depth compared to the uniform pier due to its shielding effect against downflow and horseshoe vortices.In addition,regression,artificial neural network(ANN),and M5 model tree models were developed using experimental data from this and previous studies.The M5 model outperformed the traditional HEC-18 equation,regression,and ANN models,with a coefficient of determination greater than 0.85.Sensitivity analysis indicated that flow depth,foundation elevation,and diameter significantly influenced scour depth prediction,whereas sediment size had a lesser impact.
文摘The received signal of the polarization sensitive array is proved to have trilinear model characteristics. The blind parallel factor（PARAFAC） signal detection algorithm for the polarization sensitive array is proposed. The trilinear alternating least square （TALS） algorithm is used to abtain the source matrix, and then the matrix is judged. Simulation results show that the bit error rate （BER） of the detection algorithm is close to that of the non-blind decorrelating method and the algorithm works well under the array error condition. BER difference between the non-blind method and this algorithm is less than 2 dB under a high SNR. The algorithm is blind and robust. The channel fading, the direction of arrive（DOA） imformation and the polarization information are needless in the algorithm.
基金Projects (51875121,51405100) supported by the National Natural Science Foundation of ChinaProjects (2014M551233,2017T100237) supported by the China Postdoctoral Science Foundation+2 种基金Project (ZR2017PA003) supported by the Natural Science Foundation of Shandong Province,ChinaProject (2017GGX202006) supported by the Plan of Key Research and Development of Shandong Province,ChinaProject (2016DXGJMS05) supported by the Plan of Science and Technology Development of Weihai,China
文摘A modified mixed strengthening model was proposed for describing the yield strength of particle reinforced aluminum matrix composites.The strengthening mechanisms of the composites were analyzed based on the microstructures and compression mechanical properties.The distribution uniformity of reinforcements and cooperation relationship among dislocation mechanisms were considered in the modified mixed strengthening model by introducing a distribution uniformity factor u and a cooperation coefficient fc,respectively.The results show that the modified mixed strengthening model can accurately describe the yield strengths of Al3Ti/2024Al composites with a relative deviation less than1.2%,which is much more accurate than other strengthening models.The modified mixed model can also be used to predict the yield strength of Al3Ti/2024Al composites with different fractions of reinforcements.
基金supported by the National Natural Science Foundation of China(Nos.1187050492,12005303,and 12175170).
文摘The global nuclear mass based on the macroscopic-microscopic model was studied by applying a newly designed multi-task learning artificial neural network(MTL-ANN). First, the reported nuclear binding energies of 2095 nuclei(Z ≥ 8, N ≥ 8) released in the latest Atomic Mass Evaluation AME2020 and the deviations between the fitting result of the liquid drop model(LDM)and data from AME2020 for each nucleus were obtained.To compensate for the deviations and investigate the possible ignored physics in the LDM, the MTL-ANN method was introduced in the model. Compared to the single-task learning(STL) method, this new network has a powerful ability to simultaneously learn multi-nuclear properties,such as the binding energies and single neutron and proton separation energies. Moreover, it is highly effective in reducing the risk of overfitting and achieving better predictions. Consequently, good predictions can be obtained using this nuclear mass model for both the training and validation datasets and for the testing dataset. In detail, the global root mean square(RMS) of the binding energy is effectively reduced from approximately 2.4 MeV of LDM to the current 0.2 MeV, and the RMS of Sn, Spcan also reach approximately 0.2 MeV. Moreover, compared to STL, for the training and validation sets, 3-9% improvement can be achieved with the binding energy, and 20-30% improvement for S_(n), S_(p);for the testing sets, the reduction in deviations can even reach 30-40%, which significantly illustrates the advantage of the current MTL.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52205481,51975305 and 52105457)Shandong Natural Science Foundation(Grant Nos.ZR2020ME158,ZR2023QE057,ZR2022QE028,ZR2021QE116,ZR2020KE027,and ZR2022QE159)+1 种基金Qingdao Science and Technology Planning Park Cultivation Plan(23-1-5-yqpy-17-qy)China Postdoctral Science Foundation(2021M701810).
文摘Grinding is a crucial process in machining workpieces because it plays a vital role in achieving the desired precision and surface quality.However,a significant technical challenge in grinding is the potential increase in temperature due to high specific energy,which can lead to surface thermal damage.Therefore,ensuring control over the surface integrity of workpieces during grinding becomes a critical concern.This necessitates the development of temperature field models that consider various parameters,such as workpiece materials,grinding wheels,grinding parameters,cooling methods,and media,to guide industrial production.This study thoroughly analyzes and summarizes grinding temperature field models.First,the theory of the grinding temperature field is investigated,classifying it into traditional models based on a continuous belt heat source and those based on a discrete heat source,depending on whether the heat source is uniform and continuous.Through this examination,a more accurate grinding temperature model that closely aligns with practical grinding conditions is derived.Subsequently,various grinding thermal models are summarized,including models for the heat source distribution,energy distribution proportional coefficient,and convective heat transfer coefficient.Through comprehensive research,the most widely recognized,utilized,and accurate model for each category is identified.The application of these grinding thermal models is reviewed,shedding light on the governing laws that dictate the influence of the heat source distribution,heat distribution,and convective heat transfer in the grinding arc zone on the grinding temperature field.Finally,considering the current issues in the field of grinding temperature,potential future research directions are proposed.The aim of this study is to provide theoretical guidance and technical support for predicting workpiece temperature and improving surface integrity.
基金the Ministry of Science and Technology of Taiwan (Grants MOST 104-2221-E-327019, MOST 105-2221-E-327-014) for financial support of this study
文摘This paper proposes a systematic method, integrating the uniform design (UD) of experiments and quantum-behaved particle swarm optimization (QPSO), to solve the problem of a robust design for a railway vehicle suspension system. Based on the new nonlinear creep model derived from combining Hertz contact theory, Kalker's linear theory and a heuristic nonlinear creep model, the modeling and dynamic analysis of a 24 degree-of-freedom railway vehicle system were investigated. The Lyapunov indirect method was used to examine the effects of suspension parameters, wheel conicities and wheel rolling radii on critical hunting speeds. Generally, the critical hunting speeds of a vehicle system resulting from worn wheels with different wheel rolling radii are lower than those of a vehicle system having original wheels without different wheel rolling radii. Because of worn wheels, the critical hunting speed of a running railway vehicle substantially declines over the long term. For safety reasons, it is necessary to design the suspension system parameters to increase the robustness of the system and decrease the sensitive of wheel noises. By applying UD and QPSO, the nominal-the-best signal-to-noise ratio of the system was increased from -48.17 to -34.05 dB. The rate of improvement was 29.31%. This study has demonstrated that the integration of UD and QPSO can successfully reveal the optimal solution of suspension parameters for solving the robust design problem of a railway vehicle suspension system.
