During the rotor assembly of aeroengines,the combined effect of blade mass moment variations and fixed tenon slot constraints makes single-phase rotor unbalance optimization strategies insufficient for real-world indu...During the rotor assembly of aeroengines,the combined effect of blade mass moment variations and fixed tenon slot constraints makes single-phase rotor unbalance optimization strategies insufficient for real-world industrial assembly scenarios.This often leads to excessive residual unbalance after assembly,resulting in engine vibrations and compromised operational stability.To address the lack of blade selection strategies and low qualification rates due to tenon slot constraints in industrial settings,this paper proposes a co-optimization method for blade selection and sequencing under industrial assembly constraints.A two-stage data-driven optimization framework is developed.In the first stage,a Dynamic Replacement Roulette Selection(DRWS)algorithm is introduced for global multi-set blade selection,improving blade utilization and avoiding selection failure caused by excessive moment dispersion.In the second stage,under fixed tenon slot constraints,blade sequencing is optimized using a Constrained Adaptive Genetic Algorithm(CAGA),effectively suppressing residual unbalance.Experimental results demonstrate that the proposed method achieves a blade utilization rate of 92.4%on 145 samples,with well-balanced group sets.Under tenon slot constraints,the residual unbalance is reduced from 58 g·mm and 94 g·mm(random assembly)to 7 g·mm and 10 g·mm,respectively.This study offers a novel solution and technical support for improving assembly precision and enabling intelligent decision-making in aeroengine rotor assembly lines.展开更多
Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics...Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.展开更多
The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuse...The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.展开更多
Digital image security is a fundamental and tedious process on shared communication channels.Several methods have been employed for accomplishing security on digital image transmission,such as encryption,steganography...Digital image security is a fundamental and tedious process on shared communication channels.Several methods have been employed for accomplishing security on digital image transmission,such as encryption,steganography,and watermarking.Image stenography and encryption are commonly used models to achieve improved security.Besides,optimal pixel selection process(OPSP)acts as a vital role in the encryption process.With this motivation,this study designs a new competitive swarmoptimization with encryption based stenographic technique for digital image security,named CSOES-DIS technique.The proposed CSOES-DIS model aims to encrypt the secret image prior to the embedding process.In addition,the CSOES-DIS model applies a double chaotic digital image encryption(DCDIE)technique to encrypt the secret image,and then embedding method was implemented.Also,the OPSP can be carried out by the design of CSO algorithm and thereby increases the secrecy level.In order to portray the enhanced outcomes of the CSOES-DIS model,a comparative examination with recent methods is performed and the results reported the betterment of the CSOES-DIS model based on different measures.展开更多
Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One ...Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.展开更多
A multi-objective lectotype optimization model based on site conditions and seismic fortification intensity is presented for mid-highrise residential buildings taking into account multiple items such as the original i...A multi-objective lectotype optimization model based on site conditions and seismic fortification intensity is presented for mid-highrise residential buildings taking into account multiple items such as the original investment, disaster losses and maintenance cost, the integral stiffness, the total ductility, the construction period, and so on. A Three-Scale Fuzzy Analytical Hierarchy process is proposed by introducing the Three-Scale Analytical Hierarchy process and the trapezoid fuzzy number. The result of a calculation example shows that the T-FAHP is practical.展开更多
Responding to complex analytical queries in the data warehouse(DW)is one of the most challenging tasks that require prompt attention.The problem of materialized view(MV)selection relies on selecting the most optimal v...Responding to complex analytical queries in the data warehouse(DW)is one of the most challenging tasks that require prompt attention.The problem of materialized view(MV)selection relies on selecting the most optimal views that can respond to more queries simultaneously.This work introduces a combined approach in which the constraint handling process is combined with metaheuristics to select the most optimal subset of DW views from DWs.The proposed work initially refines the solution to enable a feasible selection of views using the ensemble constraint handling technique(ECHT).The constraints such as self-adaptive penalty,epsilon(ε)-parameter and stochastic ranking(SR)are considered for constraint handling.These two constraints helped the proposed model select the finest views that minimize the objective function.Further,a novel and effective combination of Ebola and coot optimization algorithms named hybrid Ebola with coot optimization(CHECO)is introduced to choose the optimal MVs.Ebola and Coot have recently introduced metaheuristics that identify the global optimal set of views from the given population.By combining these two algorithms,the proposed framework resulted in a highly optimized set of views with minimized costs.Several cost functions are described to enable the algorithm to choose the finest solution from the problem space.Finally,extensive evaluations are conducted to prove the performance of the proposed approach compared to existing algorithms.The proposed framework resulted in a view maintenance cost of 6,329,354,613,784,query processing cost of 3,522,857,483,566 and execution time of 226 s when analyzed using the TPC-H benchmark dataset.展开更多
A spectral match optimization based on grey incidence matrix was put forward to evaluate camouflage painting design.A synthetic degree of incidence (SDI) was defined to comprehensively reflect the spectrum similarity ...A spectral match optimization based on grey incidence matrix was put forward to evaluate camouflage painting design.A synthetic degree of incidence (SDI) was defined to comprehensively reflect the spectrum similarity based on theory of grey incidence analysis.A grey optimization model for camouflage painting sheme was constructed on the basis of SDI and grey incidence matrix.Its weight values were determined according to area percentages of all components in the camouflage scene,and a quantitative ordering for various schemes could be obtained according to the evaluation coefficients.Experiment results show that the method mentioned in this paper can provide a quantitative basis for the camouflage decision-making,and it can also be used in other camouflage scheme selection.展开更多
Selection of air conditioning（AC） cold/heat sources generally concerns about certain aspects and cannot reveal the whole profile of the problems. Grey relation analysis （GRA） is a data processing method to categor...Selection of air conditioning（AC） cold/heat sources generally concerns about certain aspects and cannot reveal the whole profile of the problems. Grey relation analysis （GRA） is a data processing method to categorize the correlation extent of compared sequences and a certain reference sequence in a system with uncertain information. It is applied to evaluating and selecting AC cold/heat sources from four main aspects, which are technology, economy, reliability, and operation and management. Case study shows that the result for selecting AC cold/heat sources with the GRA method can be more reasonable and convincible. Thus it offers a new approach for designers in heating, ventilating and air conditioning field to compare and evaluate different AC cold/heat sou rces.展开更多
Pacing-induced cardiomyopathy (PICM) resultsf rom the detrimental effect of frequent right ventricular pacing.^([1]) The diagnosis relies on a combination of pacing-associated ventricular dyschrony manifested with ECG...Pacing-induced cardiomyopathy (PICM) resultsf rom the detrimental effect of frequent right ventricular pacing.^([1]) The diagnosis relies on a combination of pacing-associated ventricular dyschrony manifested with ECG wide LBBB-pattern QRS duration and clinical assessment, imaging studies. Conduction system pacing (CSP), such as His bundle pacing (HBP)and left bundle branch pacing (LBBP), may help to prevent PICM,^([2]) but the criteria for optimal patient selection remain inadequately defined.展开更多
With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter ...With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter switching frequency of the inverter is one of the impacting factors.At the same time,the control accuracy of the system also needs to be considered,and the torque ripple and flux ripple are usually considered to be its important indexes.This paper proposes a three-stage series Model Predictive Torque and Flux Control system(three-stage series MPTFC)based on fast optimal voltage vector selection to reduce switching frequency and suppress torque ripple and flux ripple.Firstly,the analytical model of the PMSM is established and the multi-stage series control method is used to reduce the switching frequency.Secondly,selectable voltage vectors are extended from 8 to 26 and a fast selection method for optimal voltage vector sectors is designed based on the hysteresis comparator,which can suppress the torque ripple and flux ripple to improve the control accuracy.Thirdly,a three-stage series control is obtained by expanding the two-stage series control using the P-Q torque decomposition theory.Finally,a model predictive torque and flux control experimental platform is built,and the feasibility and effectiveness of this method are verified through comparison experiments.展开更多
The absorbing process in isolating and coating process of α-olefin drag reducing polymer was studied by molecular dynamic simulation method, on basis of coating theory of α-olefin drag reducing polymer particles wit...The absorbing process in isolating and coating process of α-olefin drag reducing polymer was studied by molecular dynamic simulation method, on basis of coating theory of α-olefin drag reducing polymer particles with polyurethane as coating material. The distributions of sodium laurate, sodium dodeeyl sulfate, and sodium dodeeyl benzene sulfonate on the surface of α-olefin drag reducing polymer particles were almost the same, but the bending degrees of them were obviously different. The bending degree of SLA molecules was greater than those of the other two surfactant molecules. Simulation results of absorbing and accumulating structure showed that, though hydrophobie properties of surfactant molecules were almost the same, water density around long chain sulfonate sodium was bigger than that around alkyl sulfate sodium. This property goes against useful absorbing and accumulating on the surface of α-olefin drag reducing polymer particles; simulation results of interactions of different surfactant and multiple hydroxyl compounds on surface of particles showed that, interactions of different surfaetant and one kind of multiple hydroxyl compound were similar to those of one kind of surfaetant and different multiple hydroxyl compounds. These two contrast types of interactions also exhibited the differences of absorbing distribution and closing degrees to surface of particles. The sequence of closing degrees was derived from simulation; control step of addition polymerization interaction in coating process was absorbing mass transfer process, so the more closed to surface of particle the multiple hydroxyl compounds were, the easier interactions With isoeyanate were. Simulation results represented the compatibility relationship between surfactant and multiple hydroxyl compounds. The isolating and coating processes of α-olefin drag reducing polymer were further understood on molecule and atom level through above simulation research, and based on the simulation, a referenced theoretical basis was provided for practical optimal selection and experimental preparation of α-olefin drag reducing polymer particles suspension isolation agent.展开更多
The numerical calculation method is widely used in the evaluation of slope stability,but it cannot take the randomness and fuzziness into account that exist in rock and soil engineering objectively.The fuzzy optimizat...The numerical calculation method is widely used in the evaluation of slope stability,but it cannot take the randomness and fuzziness into account that exist in rock and soil engineering objectively.The fuzzy optimization theory is thus introduced to the evaluation of slope stability by this paper and a method of fuzzy optimal selection of similar slopes is put forward to analyze slope stability.By comparing the relative membership degrees that the evaluated object sample of slope is similar to the source samples of which the stabilities are detected clearly,the source sample with the maximal relative membership degree will be chosen as the best similar one to the object sample,and the stability of the object sample can be evaluated by that of the best similar source sample.In the process many uncertain influential factors are considered and characteristics and knowledge of the source samples are obtained.The practical calculation indicates that it can achieve good results to evaluate slope stability by using this method.展开更多
The nitrile butadiene rubber(NBR)hardness effect on the sealing characteristics of hydraulic O-ring rod seals is analyzed based on a mixed lubrication elastohydrodynamic model.Parameterized studies are conducted to re...The nitrile butadiene rubber(NBR)hardness effect on the sealing characteristics of hydraulic O-ring rod seals is analyzed based on a mixed lubrication elastohydrodynamic model.Parameterized studies are conducted to reveal the mechanism of the influence of rubber hardness on the static and dynamic behavior of seals.The optimized selections of rubber hardness are then investigated under different conditions.Results show that the low hardness seal is prone to stress concentration due to the extrusion effect under high pressure conditions;it is also more prone to leaking.A high hardness seal can better prevent leakage by reducing film thickness but it will cause large frictional power loss and increase the probability of wear failure.The choice of low hardness is recommended to reduce friction with the premise that leakage requirements are met.展开更多
Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services sele...Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.展开更多
A directional filter algorithm for intensity synthetic aperture radar （SAR） image based on nonsubsampled contourlet transform （NSCT） and immune clonal selection （ICS） is presented. The proposed filter mainly foc...A directional filter algorithm for intensity synthetic aperture radar （SAR） image based on nonsubsampled contourlet transform （NSCT） and immune clonal selection （ICS） is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.展开更多
Recent estimates indicate that one-fifth of botanical species worldwide are considered at risk of becoming extinct in the wild. One available strategy for conserving many rare plant species is reintroduction, which ho...Recent estimates indicate that one-fifth of botanical species worldwide are considered at risk of becoming extinct in the wild. One available strategy for conserving many rare plant species is reintroduction, which holds much promise especially when carefully planned by following guidelines and when monitored long-term. We review the Center for Plant Conservation Best Reintroduction Practice Guidelines and highlight important components for planning plant reintroductions. Before attempting reintroductions practitioners should justify them, should consider alternative conservation strategies, understand threats, and ensure that these threats are absent from any recipient site. Planning a reintroduction requires considering legal and logistic parameters as well as target species and recipient site attributes.Carefully selecting the genetic composition of founders, founder population size, and recipient site will influence establishment and population growth. Whenever possible practitioners should conduct reintroductions as experiments and publish results. To document whether populations are sustainable will require long-term monitoring for decades, therefore planning an appropriate monitoring technique for the taxon must consider current and future needs. Botanical gardens can play a leading role in developing the science and practice of plant reintroduction.展开更多
In order to get cheap and excellent PEE (Powdery Emulsion Explosives), themodel of optimizing selection on preparation of PEE was established by the Neural Net Theory (NNT).On the basis of some data in the study of PE...In order to get cheap and excellent PEE (Powdery Emulsion Explosives), themodel of optimizing selection on preparation of PEE was established by the Neural Net Theory (NNT).On the basis of some data in the study of PEE, the training, prediction and optimizing selection ofthe Neural Net (NN) model were finished by compiling procedures. The results indicate that the modelis helpful to the preparation of PEE and worthy to extend and apply broadly.展开更多
Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems,...Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. Here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.展开更多
基金supported by Basic Research Project for Young Students of the National Natural Science Foundation of China(grant number:524B2070)National Key Research and Development Program of China National Key R&D Program of China(2024YFF0726600,2024YFF0726601,2024YFF0726602,2024YFF0726604)+2 种基金Fundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China 52275525Postdoctoral Fellowship Program of CPSF under Grant Number BX20240476.
文摘During the rotor assembly of aeroengines,the combined effect of blade mass moment variations and fixed tenon slot constraints makes single-phase rotor unbalance optimization strategies insufficient for real-world industrial assembly scenarios.This often leads to excessive residual unbalance after assembly,resulting in engine vibrations and compromised operational stability.To address the lack of blade selection strategies and low qualification rates due to tenon slot constraints in industrial settings,this paper proposes a co-optimization method for blade selection and sequencing under industrial assembly constraints.A two-stage data-driven optimization framework is developed.In the first stage,a Dynamic Replacement Roulette Selection(DRWS)algorithm is introduced for global multi-set blade selection,improving blade utilization and avoiding selection failure caused by excessive moment dispersion.In the second stage,under fixed tenon slot constraints,blade sequencing is optimized using a Constrained Adaptive Genetic Algorithm(CAGA),effectively suppressing residual unbalance.Experimental results demonstrate that the proposed method achieves a blade utilization rate of 92.4%on 145 samples,with well-balanced group sets.Under tenon slot constraints,the residual unbalance is reduced from 58 g·mm and 94 g·mm(random assembly)to 7 g·mm and 10 g·mm,respectively.This study offers a novel solution and technical support for improving assembly precision and enabling intelligent decision-making in aeroengine rotor assembly lines.
基金National Natural Science Foundation of China (51175502)
文摘Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.
基金supported by the National Natural Science Foundation of China(51175502)
文摘The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.
基金Taif University Researchers Supporting Project Number(TURSP-2020/154),Taif University,Taif,Saudi Arabia.
文摘Digital image security is a fundamental and tedious process on shared communication channels.Several methods have been employed for accomplishing security on digital image transmission,such as encryption,steganography,and watermarking.Image stenography and encryption are commonly used models to achieve improved security.Besides,optimal pixel selection process(OPSP)acts as a vital role in the encryption process.With this motivation,this study designs a new competitive swarmoptimization with encryption based stenographic technique for digital image security,named CSOES-DIS technique.The proposed CSOES-DIS model aims to encrypt the secret image prior to the embedding process.In addition,the CSOES-DIS model applies a double chaotic digital image encryption(DCDIE)technique to encrypt the secret image,and then embedding method was implemented.Also,the OPSP can be carried out by the design of CSO algorithm and thereby increases the secrecy level.In order to portray the enhanced outcomes of the CSOES-DIS model,a comparative examination with recent methods is performed and the results reported the betterment of the CSOES-DIS model based on different measures.
基金supported by the National Basic Research Program of China (973 Program) under Grant 2013CB329104the National Natural Science Foundation of China under Grant 61372124 and 61427801the Key Projects of Natural Science Foundation of Jiangsu University under Grant 11KJA510001
文摘Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.
文摘A multi-objective lectotype optimization model based on site conditions and seismic fortification intensity is presented for mid-highrise residential buildings taking into account multiple items such as the original investment, disaster losses and maintenance cost, the integral stiffness, the total ductility, the construction period, and so on. A Three-Scale Fuzzy Analytical Hierarchy process is proposed by introducing the Three-Scale Analytical Hierarchy process and the trapezoid fuzzy number. The result of a calculation example shows that the T-FAHP is practical.
文摘Responding to complex analytical queries in the data warehouse(DW)is one of the most challenging tasks that require prompt attention.The problem of materialized view(MV)selection relies on selecting the most optimal views that can respond to more queries simultaneously.This work introduces a combined approach in which the constraint handling process is combined with metaheuristics to select the most optimal subset of DW views from DWs.The proposed work initially refines the solution to enable a feasible selection of views using the ensemble constraint handling technique(ECHT).The constraints such as self-adaptive penalty,epsilon(ε)-parameter and stochastic ranking(SR)are considered for constraint handling.These two constraints helped the proposed model select the finest views that minimize the objective function.Further,a novel and effective combination of Ebola and coot optimization algorithms named hybrid Ebola with coot optimization(CHECO)is introduced to choose the optimal MVs.Ebola and Coot have recently introduced metaheuristics that identify the global optimal set of views from the given population.By combining these two algorithms,the proposed framework resulted in a highly optimized set of views with minimized costs.Several cost functions are described to enable the algorithm to choose the finest solution from the problem space.Finally,extensive evaluations are conducted to prove the performance of the proposed approach compared to existing algorithms.The proposed framework resulted in a view maintenance cost of 6,329,354,613,784,query processing cost of 3,522,857,483,566 and execution time of 226 s when analyzed using the TPC-H benchmark dataset.
文摘A spectral match optimization based on grey incidence matrix was put forward to evaluate camouflage painting design.A synthetic degree of incidence (SDI) was defined to comprehensively reflect the spectrum similarity based on theory of grey incidence analysis.A grey optimization model for camouflage painting sheme was constructed on the basis of SDI and grey incidence matrix.Its weight values were determined according to area percentages of all components in the camouflage scene,and a quantitative ordering for various schemes could be obtained according to the evaluation coefficients.Experiment results show that the method mentioned in this paper can provide a quantitative basis for the camouflage decision-making,and it can also be used in other camouflage scheme selection.
文摘Selection of air conditioning（AC） cold/heat sources generally concerns about certain aspects and cannot reveal the whole profile of the problems. Grey relation analysis （GRA） is a data processing method to categorize the correlation extent of compared sequences and a certain reference sequence in a system with uncertain information. It is applied to evaluating and selecting AC cold/heat sources from four main aspects, which are technology, economy, reliability, and operation and management. Case study shows that the result for selecting AC cold/heat sources with the GRA method can be more reasonable and convincible. Thus it offers a new approach for designers in heating, ventilating and air conditioning field to compare and evaluate different AC cold/heat sou rces.
文摘Pacing-induced cardiomyopathy (PICM) resultsf rom the detrimental effect of frequent right ventricular pacing.^([1]) The diagnosis relies on a combination of pacing-associated ventricular dyschrony manifested with ECG wide LBBB-pattern QRS duration and clinical assessment, imaging studies. Conduction system pacing (CSP), such as His bundle pacing (HBP)and left bundle branch pacing (LBBP), may help to prevent PICM,^([2]) but the criteria for optimal patient selection remain inadequately defined.
基金co-supported by the National Natural Science Foundation of China(No.52477063)the National Key Research and Development Program of China(No.2023YFF0719100)。
文摘With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter switching frequency of the inverter is one of the impacting factors.At the same time,the control accuracy of the system also needs to be considered,and the torque ripple and flux ripple are usually considered to be its important indexes.This paper proposes a three-stage series Model Predictive Torque and Flux Control system(three-stage series MPTFC)based on fast optimal voltage vector selection to reduce switching frequency and suppress torque ripple and flux ripple.Firstly,the analytical model of the PMSM is established and the multi-stage series control method is used to reduce the switching frequency.Secondly,selectable voltage vectors are extended from 8 to 26 and a fast selection method for optimal voltage vector sectors is designed based on the hysteresis comparator,which can suppress the torque ripple and flux ripple to improve the control accuracy.Thirdly,a three-stage series control is obtained by expanding the two-stage series control using the P-Q torque decomposition theory.Finally,a model predictive torque and flux control experimental platform is built,and the feasibility and effectiveness of this method are verified through comparison experiments.
文摘The absorbing process in isolating and coating process of α-olefin drag reducing polymer was studied by molecular dynamic simulation method, on basis of coating theory of α-olefin drag reducing polymer particles with polyurethane as coating material. The distributions of sodium laurate, sodium dodeeyl sulfate, and sodium dodeeyl benzene sulfonate on the surface of α-olefin drag reducing polymer particles were almost the same, but the bending degrees of them were obviously different. The bending degree of SLA molecules was greater than those of the other two surfactant molecules. Simulation results of absorbing and accumulating structure showed that, though hydrophobie properties of surfactant molecules were almost the same, water density around long chain sulfonate sodium was bigger than that around alkyl sulfate sodium. This property goes against useful absorbing and accumulating on the surface of α-olefin drag reducing polymer particles; simulation results of interactions of different surfactant and multiple hydroxyl compounds on surface of particles showed that, interactions of different surfaetant and one kind of multiple hydroxyl compound were similar to those of one kind of surfaetant and different multiple hydroxyl compounds. These two contrast types of interactions also exhibited the differences of absorbing distribution and closing degrees to surface of particles. The sequence of closing degrees was derived from simulation; control step of addition polymerization interaction in coating process was absorbing mass transfer process, so the more closed to surface of particle the multiple hydroxyl compounds were, the easier interactions With isoeyanate were. Simulation results represented the compatibility relationship between surfactant and multiple hydroxyl compounds. The isolating and coating processes of α-olefin drag reducing polymer were further understood on molecule and atom level through above simulation research, and based on the simulation, a referenced theoretical basis was provided for practical optimal selection and experimental preparation of α-olefin drag reducing polymer particles suspension isolation agent.
基金Sponsored by the Natural Science Foundation of Liaoning Province in China(Grant No.20022106).
文摘The numerical calculation method is widely used in the evaluation of slope stability,but it cannot take the randomness and fuzziness into account that exist in rock and soil engineering objectively.The fuzzy optimization theory is thus introduced to the evaluation of slope stability by this paper and a method of fuzzy optimal selection of similar slopes is put forward to analyze slope stability.By comparing the relative membership degrees that the evaluated object sample of slope is similar to the source samples of which the stabilities are detected clearly,the source sample with the maximal relative membership degree will be chosen as the best similar one to the object sample,and the stability of the object sample can be evaluated by that of the best similar source sample.In the process many uncertain influential factors are considered and characteristics and knowledge of the source samples are obtained.The practical calculation indicates that it can achieve good results to evaluate slope stability by using this method.
基金supported by the National Natural Science Foundation of China(No.52005470)the Natural Science Foundation of Zhejiang Province(No.LQ21E050020)the Fundamental Research Funds for the Provincial Universities of Zhejiang(No.2021YW17),China.
文摘The nitrile butadiene rubber(NBR)hardness effect on the sealing characteristics of hydraulic O-ring rod seals is analyzed based on a mixed lubrication elastohydrodynamic model.Parameterized studies are conducted to reveal the mechanism of the influence of rubber hardness on the static and dynamic behavior of seals.The optimized selections of rubber hardness are then investigated under different conditions.Results show that the low hardness seal is prone to stress concentration due to the extrusion effect under high pressure conditions;it is also more prone to leaking.A high hardness seal can better prevent leakage by reducing film thickness but it will cause large frictional power loss and increase the probability of wear failure.The choice of low hardness is recommended to reduce friction with the premise that leakage requirements are met.
基金Project(70631004)supported by the Key Project of the National Natural Science Foundation of ChinaProject(20080440988)supported by the Postdoctoral Science Foundation of China+1 种基金Project(09JJ4030)supported by the Natural Science Foundation of Hunan Province,ChinaProject supported by the Postdoctoral Science Foundation of Central South University,China
文摘Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.
基金supported by National Natural Science Foundationof China (No. 60802061)Natural Science Research Item of the Education Department of Henan Province (No. 2008B510001)Innovation Scientists and Technicians Troop Construction Projects of Henan Province (No. 084100510012)
文摘A directional filter algorithm for intensity synthetic aperture radar （SAR） image based on nonsubsampled contourlet transform （NSCT） and immune clonal selection （ICS） is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.
基金Guangxi Chairman's Foundation grant #09203-04 to Hong Liu and colleagues supported JM attendance at the IABG conference possiblefunding from the U.S. Fish and Wildlife Service(1448-40181-99-G173)+4 种基金Florida Department of Agriculture and Consumer Services (#20161,021010,022647)Miami-Dade County Natural Areas Management and Environmentally Endangered Lands Program (R-80807)Arizona Department of TransportationU.S. Forest ServiceU.S. National Park Service
文摘Recent estimates indicate that one-fifth of botanical species worldwide are considered at risk of becoming extinct in the wild. One available strategy for conserving many rare plant species is reintroduction, which holds much promise especially when carefully planned by following guidelines and when monitored long-term. We review the Center for Plant Conservation Best Reintroduction Practice Guidelines and highlight important components for planning plant reintroductions. Before attempting reintroductions practitioners should justify them, should consider alternative conservation strategies, understand threats, and ensure that these threats are absent from any recipient site. Planning a reintroduction requires considering legal and logistic parameters as well as target species and recipient site attributes.Carefully selecting the genetic composition of founders, founder population size, and recipient site will influence establishment and population growth. Whenever possible practitioners should conduct reintroductions as experiments and publish results. To document whether populations are sustainable will require long-term monitoring for decades, therefore planning an appropriate monitoring technique for the taxon must consider current and future needs. Botanical gardens can play a leading role in developing the science and practice of plant reintroduction.
基金This work was financially supported by the National Natural Science Foundation of China (No.50174008).
文摘In order to get cheap and excellent PEE (Powdery Emulsion Explosives), themodel of optimizing selection on preparation of PEE was established by the Neural Net Theory (NNT).On the basis of some data in the study of PEE, the training, prediction and optimizing selection ofthe Neural Net (NN) model were finished by compiling procedures. The results indicate that the modelis helpful to the preparation of PEE and worthy to extend and apply broadly.
基金support by the National Natural Science Foundation of China (Grant No. 62005049)Natural Science Foundation of Fujian Province (Grant Nos. 2020J01451, 2022J05113)Education and Scientific Research Program for Young and Middleaged Teachers in Fujian Province (Grant No. JAT210035)。
文摘Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. Here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.
