Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and ...Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.展开更多
To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartogra...To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartography of heterogeneous combat networks based on the operational chain”(FCBOC).In this framework,a functional module detection algorithm named operational chain-based label propagation algorithm(OCLPA),which considers the cooperation and interactions among combat entities and can thus naturally tackle network heterogeneity,is proposed to identify the functional modules of the network.Then,the nodes and their modules are classified into different roles according to their properties.A case study shows that FCBOC can provide a simplified description of disorderly information of combat networks and enable us to identify their functional and structural network characteristics.The results provide useful information to help commanders make precise and accurate decisions regarding the protection,disintegration or optimization of combat networks.Three algorithms are also compared with OCLPA to show that FCBOC can most effectively find functional modules with practical meaning.展开更多
The rapid development of military technology has prompted different types of equipment to break the limits of operational domains and emerged through complex interactions to form a vast combat system of systems(CSoS),...The rapid development of military technology has prompted different types of equipment to break the limits of operational domains and emerged through complex interactions to form a vast combat system of systems(CSoS),which can be abstracted as a heterogeneous combat network(HCN).It is of great military significance to study the disintegration strategy of combat networks to achieve the breakdown of the enemy’s CSoS.To this end,this paper proposes an integrated framework called HCN disintegration based on double deep Q-learning(HCN-DDQL).Firstly,the enemy’s CSoS is abstracted as an HCN,and an evaluation index based on the capability and attack costs of nodes is proposed.Meanwhile,a mathematical optimization model for HCN disintegration is established.Secondly,the learning environment and double deep Q-network model of HCN-DDQL are established to train the HCN’s disintegration strategy.Then,based on the learned HCN-DDQL model,an algorithm for calculating the HCN’s optimal disintegration strategy under different states is proposed.Finally,a case study is used to demonstrate the reliability and effectiveness of HCNDDQL,and the results demonstrate that HCN-DDQL can disintegrate HCNs more effectively than baseline methods.展开更多
When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ...When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.展开更多
To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on be...To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.展开更多
Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this iss...Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.展开更多
Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A light...Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.展开更多
Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce t...Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.展开更多
Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of...Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of task scheduling algorithms for homogeneous environments have been proposed, whereas, a few for heterogeneous environments can be found in the literature. A novel task scheduling algorithm for heterogeneous environments, called the heterogeneous critical task （HCT） scheduling algorithm is presented. By means of the directed acyclic graph and the gantt graph, the HCT algorithm defines the critical task and the idle time slot. After determining the critical tasks of a given task, the HCT algorithm tentatively duplicates the critical tasks onto the processor that has the given task in the idle time slot, to reduce the start time of the given task. To compare the performance of the HCT algorithm with several recently proposed algorithms, a large set of randomly generated applications and the Gaussian elimination application are randomly generated. The experimental result has shown that the HCT algorithm outperforms the other algorithm.展开更多
Shockwaves from fuel-air explosive(FAE)cloud explosions may cause significant casualties.The ground overpressure field is usually used to evaluate the damage range of explosion shockwaves.In this paper,a finite elemen...Shockwaves from fuel-air explosive(FAE)cloud explosions may cause significant casualties.The ground overpressure field is usually used to evaluate the damage range of explosion shockwaves.In this paper,a finite element model of multi-sources FAE explosion is established to simulate the process of multiple shockwaves propagation and interaction.The model is verified with the experimental data of a fourfoldsource FAE explosion,with the total fuel mass of 340 kg.Simulation results show that the overpressure fields of multi-sources FAE explosions are different from that of the single-source.In the case of multisources,the overpressure fields are influenced significantly by source scattering distance and source number.Subsequently,damage ranges of overpressure under three different levels are calculated.Within a suitable source scattering distance,the damage range of multi-sources situation is greater than that of the single-source,under the same amount of total fuel mass.This research provides a basis for personnel shockwave protection from multi-sources FAE explosion.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
A new vertical handoff decision algorithm is proposed to maximize the system benefit in heterogeneous wireless networks which comprise cellular networks and wireless local area networks （WLANs）. Firstly the block pr...A new vertical handoff decision algorithm is proposed to maximize the system benefit in heterogeneous wireless networks which comprise cellular networks and wireless local area networks （WLANs）. Firstly the block probability, the drop probability and the number of users in the heterogeneous networks are calculated in the channel-guard call admission method, and a function of the system benefit which is based on the new call arrival rate and the handoff call arrival rate is proposed. Then the optimal radius of WLAN is obtained by using simulation annealing （SA） method to maximize the benefit. All the nodes should handoff from cellular network to WLAN if they enter WLAN＇s scope and handoff from WLAN to cellular network if they leave the scope. Finally, the algorithm in different new call arrival rates and handoff call arrival rates is analyzed and results show that it can achieve good effects.展开更多
In order to verify the validity of finite element numerical simulation method for asphalt mixture, which consists of aggregates, mastic （where mastic is a kind of fine mixture composed of asphalt binder mixed with fi...In order to verify the validity of finite element numerical simulation method for asphalt mixture, which consists of aggregates, mastic （where mastic is a kind of fine mixture composed of asphalt binder mixed with fines and fine aggregates） and air voids, based on three-dimensional （3D） heterogeneous specimen, X-ray computerized tomography （X-ray CT） was used to scan the asphalt specimens to obtain the real internal microstrnctures of asphalt mixture. CT images were reconstructed to build up 3D digital specimen, and the viscoelastic properties of mastic were described with Burgers model The uniaxial creep numerical simulations of three different levels of aggregate gradation were conducted. The simulation results agree well with the experimental results. The numerical simulation of asphalt mixture incorporated with real 3D microstructure based on finite element method is a promising application to conduct research of asphalt concrete. Additionally, this method can increase the mechanistic understanding of global viscoelastic properties of asphalt mixtures by linking the real 3D microstructure.展开更多
Heterogeneous Fenton-like process using fly ash as a catalyst was studied to degrade n-butyl xanthate form aqueous solution. The different reaction parameters on the degradation efficiency of the process were investig...Heterogeneous Fenton-like process using fly ash as a catalyst was studied to degrade n-butyl xanthate form aqueous solution. The different reaction parameters on the degradation efficiency of the process were investigated. The fly ash/H2O2 catalyst possesses a high oxidation activity for n-butyl xanthate degradation in aqueous solution. It is found that both the dosage of catalyst and initial solution pH significantly affect the n-butyl xanthate conversion efficient. The results indicate that by using 1.176 mmol/L H2O2 and 1.0 g/L fly ash catalyst with mass fraction of 4.14% Fe(III) oxide at pH 3.0, almost 96.90% n-butyl xanthate conversion and over 96.66% COD removal can be achieved within 120 min with heterogeneous catalysis by fly ash. CS2 as an intermediate of n-butyl xanthate oxidation. Finally, it is demonstrated that the fly ash/H2O2 catalytic oxidation process can be an efficient method for the treatment of n-butyl xanthate containing wastewater.展开更多
The planetary reducer is a common type of transmission mechanism,which can provide high transmission accuracy and has been widely used,and it is usually required with high reliability of transmission characteristics i...The planetary reducer is a common type of transmission mechanism,which can provide high transmission accuracy and has been widely used,and it is usually required with high reliability of transmission characteristics in practice.During the manufacturing and usage stages of planetary reducers,uncertainties are ubiquitous and wear is inevitable,which affect the transmission characteristics and the reliability of planetary reducers.In this paper,belief reliability modeling and analysis considering multi-uncertainties and wear are proposed for planetary reducers.Firstly,based on the functional principle and the influence of wear,the performance margin degradation model is established using the hysteresis error as the key performance parameter,where the degradation is mainly caused by the accumulated wear.After that,multi-source uncertainties are analyzed and quantified separately,including manufacturing errors,uncertainties in operational and environmental conditions,and uncertainties in performance thresholds.Finally,the belief reliability model is established based on the performance margin degradation model.A case study of a planetary reducer is applied and the reliability sensitivity analysis is implemented to show the practicability of the proposed method.The results show that the proposed method can provide some suggestions to the design and manufacturing phases of the planetary reducer.展开更多
Heterogeneous wireless access technologies will coexist in next generation wireless networks.These technologies form integrated networks,and these networks support multiple services with high quality level.Various acc...Heterogeneous wireless access technologies will coexist in next generation wireless networks.These technologies form integrated networks,and these networks support multiple services with high quality level.Various access technologies allow users to select the best available access network to meet the requirements of each type of communication service.Being always best connected anytime and anywhere is a major concern in a heterogeneous wireless networks environment.Always best connected enables network selection mechanisms to keep mobile users always connected to the best network.We present an overview of the network selection and prediction problems and challenges.In addition,we discuss a comprehensive classification of related theoretic approaches,and also study the integration between these methods,finding the best solution of network selection and prediction problems.The optimal solution can fulfill the requirements of the next generation wireless networks.展开更多
The present article deals with thermally stratified stagnation-point flow saturated in porous medium on surface of variable thickness along with more convincing and reliable surface condition termed as melting heat tr...The present article deals with thermally stratified stagnation-point flow saturated in porous medium on surface of variable thickness along with more convincing and reliable surface condition termed as melting heat transfer.Homogeneous–heterogeneous reaction and radiative effects have been further taken into account to reconnoiterproperties of heat transfer.Melting heat transfer and phenomenon of homogeneous–heterogeneous reaction have engrossed widespread utilization in purification of metals,welding process,electroslag melting,biochemical systems,catalysis and several industrial developments.Suitable transformations are utilized to attain a scheme of ordinary differential equations possessing exceedingly nonlinear nature.Homotopic process is employed to develop convergent solutions of the resulting problem.Discussion regarding velocity,thermal field and concentration distribution for several involved parameters is pivotal part.Graphical behaviors of skin friction coefficient and Nusselt number are also portrayed.Concentration of the reactants is found to depreciate as a result of strength of both heterogeneous and homogeneous reaction parameters.With existence of melting phenomenon,declining attitude of fluid temperature is observed for higher radiation parameter.展开更多
The development of 3D geological models involves the integration of large amounts of geological data,as well as additional accessible proprietary lithological, structural,geochemical,geophysical,and borehole data.Luan...The development of 3D geological models involves the integration of large amounts of geological data,as well as additional accessible proprietary lithological, structural,geochemical,geophysical,and borehole data.Luanchuan,the case study area,southwestern Henan Province,is an important molybdenum-tungsten -lead-zinc polymetallic belt in China.展开更多
Particle-in-cell (PIC) method has got much benefits from GPU-accelerated heterogeneous systems.However,the performance of PIC is constrained by the interpolation operations in the weighting process on GPU (graphic pro...Particle-in-cell (PIC) method has got much benefits from GPU-accelerated heterogeneous systems.However,the performance of PIC is constrained by the interpolation operations in the weighting process on GPU (graphic processing unit).Aiming at this problem,a fast weighting method for PIC simulation on GPU-accelerated systems was proposed to avoid the atomic memory operations during the weighting process.The method was implemented by taking advantage of GPU's thread synchronization mechanism and dividing the problem space properly.Moreover,software managed shared memory on the GPU was employed to buffer the intermediate data.The experimental results show that the method achieves speedups up to 3.5 times compared to previous works,and runs 20.08 times faster on one NVIDIA Tesla M2090 GPU compared to a single core of Intel Xeon X5670 CPU.展开更多
Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to co...Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.展开更多
基金supported by the National Natural Science Foundation of China(724701189072431011).
文摘Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.
文摘To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartography of heterogeneous combat networks based on the operational chain”(FCBOC).In this framework,a functional module detection algorithm named operational chain-based label propagation algorithm(OCLPA),which considers the cooperation and interactions among combat entities and can thus naturally tackle network heterogeneity,is proposed to identify the functional modules of the network.Then,the nodes and their modules are classified into different roles according to their properties.A case study shows that FCBOC can provide a simplified description of disorderly information of combat networks and enable us to identify their functional and structural network characteristics.The results provide useful information to help commanders make precise and accurate decisions regarding the protection,disintegration or optimization of combat networks.Three algorithms are also compared with OCLPA to show that FCBOC can most effectively find functional modules with practical meaning.
基金supported by the National Natural Science Foundation of China(7200120972231011+2 种基金72071206)the Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province(2020RC4046)the Science Foundation for Outstanding Youth Scholars of Hunan Province(2022JJ20047).
文摘The rapid development of military technology has prompted different types of equipment to break the limits of operational domains and emerged through complex interactions to form a vast combat system of systems(CSoS),which can be abstracted as a heterogeneous combat network(HCN).It is of great military significance to study the disintegration strategy of combat networks to achieve the breakdown of the enemy’s CSoS.To this end,this paper proposes an integrated framework called HCN disintegration based on double deep Q-learning(HCN-DDQL).Firstly,the enemy’s CSoS is abstracted as an HCN,and an evaluation index based on the capability and attack costs of nodes is proposed.Meanwhile,a mathematical optimization model for HCN disintegration is established.Secondly,the learning environment and double deep Q-network model of HCN-DDQL are established to train the HCN’s disintegration strategy.Then,based on the learned HCN-DDQL model,an algorithm for calculating the HCN’s optimal disintegration strategy under different states is proposed.Finally,a case study is used to demonstrate the reliability and effectiveness of HCNDDQL,and the results demonstrate that HCN-DDQL can disintegrate HCNs more effectively than baseline methods.
文摘When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.
基金This work was supported by the Youth Foundation of National Science Foundation of China(62001503)the Special Fund for Taishan Scholar Project(ts 201712072).
文摘To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.
基金supported by the National Natural Science Foundation of China(61903305,62073267)the Fundamental Research Funds for the Central Universities(HXGJXM202214).
文摘Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.
基金This work was supported by the Natural Science Foundation of Heilongjiang Province(LH2022F049).
文摘Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01B187).
文摘Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.
文摘Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of task scheduling algorithms for homogeneous environments have been proposed, whereas, a few for heterogeneous environments can be found in the literature. A novel task scheduling algorithm for heterogeneous environments, called the heterogeneous critical task （HCT） scheduling algorithm is presented. By means of the directed acyclic graph and the gantt graph, the HCT algorithm defines the critical task and the idle time slot. After determining the critical tasks of a given task, the HCT algorithm tentatively duplicates the critical tasks onto the processor that has the given task in the idle time slot, to reduce the start time of the given task. To compare the performance of the HCT algorithm with several recently proposed algorithms, a large set of randomly generated applications and the Gaussian elimination application are randomly generated. The experimental result has shown that the HCT algorithm outperforms the other algorithm.
基金The authors would like to acknowledge the China Postdoctoral Science Foundation(Grant No.2019M660488)to provide fund for this work.
文摘Shockwaves from fuel-air explosive(FAE)cloud explosions may cause significant casualties.The ground overpressure field is usually used to evaluate the damage range of explosion shockwaves.In this paper,a finite element model of multi-sources FAE explosion is established to simulate the process of multiple shockwaves propagation and interaction.The model is verified with the experimental data of a fourfoldsource FAE explosion,with the total fuel mass of 340 kg.Simulation results show that the overpressure fields of multi-sources FAE explosions are different from that of the single-source.In the case of multisources,the overpressure fields are influenced significantly by source scattering distance and source number.Subsequently,damage ranges of overpressure under three different levels are calculated.Within a suitable source scattering distance,the damage range of multi-sources situation is greater than that of the single-source,under the same amount of total fuel mass.This research provides a basis for personnel shockwave protection from multi-sources FAE explosion.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
文摘A new vertical handoff decision algorithm is proposed to maximize the system benefit in heterogeneous wireless networks which comprise cellular networks and wireless local area networks （WLANs）. Firstly the block probability, the drop probability and the number of users in the heterogeneous networks are calculated in the channel-guard call admission method, and a function of the system benefit which is based on the new call arrival rate and the handoff call arrival rate is proposed. Then the optimal radius of WLAN is obtained by using simulation annealing （SA） method to maximize the benefit. All the nodes should handoff from cellular network to WLAN if they enter WLAN＇s scope and handoff from WLAN to cellular network if they leave the scope. Finally, the algorithm in different new call arrival rates and handoff call arrival rates is analyzed and results show that it can achieve good effects.
基金Project(51038004) supported by the National Natural Science Foundation of China
文摘In order to verify the validity of finite element numerical simulation method for asphalt mixture, which consists of aggregates, mastic （where mastic is a kind of fine mixture composed of asphalt binder mixed with fines and fine aggregates） and air voids, based on three-dimensional （3D） heterogeneous specimen, X-ray computerized tomography （X-ray CT） was used to scan the asphalt specimens to obtain the real internal microstrnctures of asphalt mixture. CT images were reconstructed to build up 3D digital specimen, and the viscoelastic properties of mastic were described with Burgers model The uniaxial creep numerical simulations of three different levels of aggregate gradation were conducted. The simulation results agree well with the experimental results. The numerical simulation of asphalt mixture incorporated with real 3D microstructure based on finite element method is a promising application to conduct research of asphalt concrete. Additionally, this method can increase the mechanistic understanding of global viscoelastic properties of asphalt mixtures by linking the real 3D microstructure.
基金Project(CZQ13002)supported by the Special Fund for Basic Scientific Research of Central Universities,China
文摘Heterogeneous Fenton-like process using fly ash as a catalyst was studied to degrade n-butyl xanthate form aqueous solution. The different reaction parameters on the degradation efficiency of the process were investigated. The fly ash/H2O2 catalyst possesses a high oxidation activity for n-butyl xanthate degradation in aqueous solution. It is found that both the dosage of catalyst and initial solution pH significantly affect the n-butyl xanthate conversion efficient. The results indicate that by using 1.176 mmol/L H2O2 and 1.0 g/L fly ash catalyst with mass fraction of 4.14% Fe(III) oxide at pH 3.0, almost 96.90% n-butyl xanthate conversion and over 96.66% COD removal can be achieved within 120 min with heterogeneous catalysis by fly ash. CS2 as an intermediate of n-butyl xanthate oxidation. Finally, it is demonstrated that the fly ash/H2O2 catalytic oxidation process can be an efficient method for the treatment of n-butyl xanthate containing wastewater.
基金This work was supported by the National Natural Science Foundation of China(51775020,51875019)the Fundamental Research Funds for the Central Universities(YWF-20-BJ-J-515).
文摘The planetary reducer is a common type of transmission mechanism,which can provide high transmission accuracy and has been widely used,and it is usually required with high reliability of transmission characteristics in practice.During the manufacturing and usage stages of planetary reducers,uncertainties are ubiquitous and wear is inevitable,which affect the transmission characteristics and the reliability of planetary reducers.In this paper,belief reliability modeling and analysis considering multi-uncertainties and wear are proposed for planetary reducers.Firstly,based on the functional principle and the influence of wear,the performance margin degradation model is established using the hysteresis error as the key performance parameter,where the degradation is mainly caused by the accumulated wear.After that,multi-source uncertainties are analyzed and quantified separately,including manufacturing errors,uncertainties in operational and environmental conditions,and uncertainties in performance thresholds.Finally,the belief reliability model is established based on the performance margin degradation model.A case study of a planetary reducer is applied and the reliability sensitivity analysis is implemented to show the practicability of the proposed method.The results show that the proposed method can provide some suggestions to the design and manufacturing phases of the planetary reducer.
基金funded by the University of Malaya, under Grant No.RG208-11AFR
文摘Heterogeneous wireless access technologies will coexist in next generation wireless networks.These technologies form integrated networks,and these networks support multiple services with high quality level.Various access technologies allow users to select the best available access network to meet the requirements of each type of communication service.Being always best connected anytime and anywhere is a major concern in a heterogeneous wireless networks environment.Always best connected enables network selection mechanisms to keep mobile users always connected to the best network.We present an overview of the network selection and prediction problems and challenges.In addition,we discuss a comprehensive classification of related theoretic approaches,and also study the integration between these methods,finding the best solution of network selection and prediction problems.The optimal solution can fulfill the requirements of the next generation wireless networks.
文摘The present article deals with thermally stratified stagnation-point flow saturated in porous medium on surface of variable thickness along with more convincing and reliable surface condition termed as melting heat transfer.Homogeneous–heterogeneous reaction and radiative effects have been further taken into account to reconnoiterproperties of heat transfer.Melting heat transfer and phenomenon of homogeneous–heterogeneous reaction have engrossed widespread utilization in purification of metals,welding process,electroslag melting,biochemical systems,catalysis and several industrial developments.Suitable transformations are utilized to attain a scheme of ordinary differential equations possessing exceedingly nonlinear nature.Homotopic process is employed to develop convergent solutions of the resulting problem.Discussion regarding velocity,thermal field and concentration distribution for several involved parameters is pivotal part.Graphical behaviors of skin friction coefficient and Nusselt number are also portrayed.Concentration of the reactants is found to depreciate as a result of strength of both heterogeneous and homogeneous reaction parameters.With existence of melting phenomenon,declining attitude of fluid temperature is observed for higher radiation parameter.
文摘The development of 3D geological models involves the integration of large amounts of geological data,as well as additional accessible proprietary lithological, structural,geochemical,geophysical,and borehole data.Luanchuan,the case study area,southwestern Henan Province,is an important molybdenum-tungsten -lead-zinc polymetallic belt in China.
基金Projects(61170049,60903044)supported by National Natural Science Foundation of ChinaProject(2012AA010903)supported by National High Technology Research and Development Program of China
文摘Particle-in-cell (PIC) method has got much benefits from GPU-accelerated heterogeneous systems.However,the performance of PIC is constrained by the interpolation operations in the weighting process on GPU (graphic processing unit).Aiming at this problem,a fast weighting method for PIC simulation on GPU-accelerated systems was proposed to avoid the atomic memory operations during the weighting process.The method was implemented by taking advantage of GPU's thread synchronization mechanism and dividing the problem space properly.Moreover,software managed shared memory on the GPU was employed to buffer the intermediate data.The experimental results show that the method achieves speedups up to 3.5 times compared to previous works,and runs 20.08 times faster on one NVIDIA Tesla M2090 GPU compared to a single core of Intel Xeon X5670 CPU.
基金Project(61170049) supported by the National Natural Science Foundation of ChinaProject(2012AA010903) supported by the National High Technology Research and Development Program of China
文摘Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.
