Background:Mastitis seriously affects the mammary health of humans and animals.Studies have found that inflammation and oxidative stress play key roles in the occur-rence and development of mastitis.Therefore,in-depth...Background:Mastitis seriously affects the mammary health of humans and animals.Studies have found that inflammation and oxidative stress play key roles in the occur-rence and development of mastitis.Therefore,in-depth research on related molecular mechanisms is of great significance.Methods:Postpartum mice were anesthetized with pentobarbital and administered lipopolysaccharide to develop the mouse mastitis model.Proteomic analysis was per-formed to compare protein expression in mitochondria-associated endoplasmic retic-ulum membranes(MAM)from two mouse mammary gland groups.Western blot was used to detect the expression of MAM-related proteins in mitochondria.AlphaFold3 was used to predict the molecular structures of phosphofurin acidic cluster sorting protein 2(PACS2)and mitofusin 2(MFN2)and their interaction levels.The MFN2-PACS2 interaction was investigated using co-immunoprecipitation and small interfer-ing RNA.Results:The results showed that the inflammation level in the mammary gland tissue of mice with mastitis significantly increased,the total antioxidant capacity decreased,and the expression of MAM-related proteins MFN2 and PACS2 was significantly downregulated.In cell experiments,overexpression of MFN2 can inhibit inflamma-tion and oxidative stress responses,and promote the interaction between MFN2 and PACS2 to affect the formation of MAMs.Conclusion:In summary,this study suggests that mastitis can alter the expression of MAM-related proteins in mouse breast tissue.The interaction between MFN2 and PACS2 regulates the formation of MAMs.Overexpression of MFN2 can promote the formation of MAMs and inhibit inflammation and oxidative stress response in mam-mary epithelial cells.Our results provided a new theoretical basis and potential thera-peutic targets for the prevention and treatment of mastitis.展开更多
The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an exa...The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an example, a 5 MW wind turbine blade design is presented by taking the maximum power coefficient and the minimum blade mass as the optimization objectives. The optimal results show that this algorithm has good performance in handling the multi-objective optimization of wind turbines, and it gives a Pareto-optimal solution set rather than the optimum solutions to the conventional multi objective optimization problems. The wind turbine blade optimization method presented in this paper provides a new and general algorithm for the multi-objective optimization of wind turbines.展开更多
In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed...In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.展开更多
Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to sol...Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-II into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by in-troduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated;this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions.展开更多
Vehicle routing problem in distribution(VRPD)is a widely used type of vehicle routing problem(VRP),which has been proved as NP-Hard,and it is usually modeled as single objective optimization problem when modeling.For ...Vehicle routing problem in distribution(VRPD)is a widely used type of vehicle routing problem(VRP),which has been proved as NP-Hard,and it is usually modeled as single objective optimization problem when modeling.For multi-objective optimization model,most researches consider two objectives.A multi-objective mathematical model for VRP is proposed,which considers the number of vehicles used,the length of route and the time arrived at each client.Genetic algorithm is one of the most widely used algorithms to solve VRP.As a type of genetic algorithm(GA),non-dominated sorting in genetic algorithm-Ⅱ(NSGA-Ⅱ)also suffers from premature convergence and enclosure competition.In order to avoid these kinds of shortage,a greedy NSGA-Ⅱ(GNSGA-Ⅱ)is proposed for VRP problem.Greedy algorithm is implemented in generating the initial population,cross-over and mutation.All these procedures ensure that NSGA-Ⅱis prevented from premature convergence and refine the performance of NSGA-Ⅱat each step.In the distribution problem of a distribution center in Michigan,US,the GNSGA-Ⅱis compared with NSGA-Ⅱ.As a result,the GNSGA-Ⅱis the most efficient one and can get the most optimized solution to VRP problem.Also,in GNSGA-Ⅱ,premature convergence is better avoided and search efficiency has been improved sharply.展开更多
With the continuous increase of rapid urbanization and population growth,sustainable urban land-use planning is becoming a more complex and challenging task for urban planners and decision-makers.Multi-objective land-...With the continuous increase of rapid urbanization and population growth,sustainable urban land-use planning is becoming a more complex and challenging task for urban planners and decision-makers.Multi-objective land-use allocation can be regarded as a complex spatial optimization problem that aims to achieve the possible trade-offs among multiple and conflicting objectives.This paper proposes an improved Non-dominated Sorting Biogeography-Based Optimization(NSBBO)algorithm for solving the multi-objective land-use allocation problem,in which maximum accessibility,maximum compactness,and maximum spatial integration were formulated as spatial objectives;and space syntax analysis was used to analyze the potential movement patterns in the new urban planning area of the city of Kigali,Rwanda.Efficient Non-dominated Sorting(ENS)algorithm and crossover operator were integrated into classical NSBBO to improve the quality of non-dominated solutions,and local search ability,and to accelerate the convergence speed of the algorithm.The results showed that the proposed NSBBO exhibited good optimal solutions with a high hypervolume index compared to the classical NSBBO.Furthermore,the proposed algorithm could generate optimal land use scenarios according to the preferred objectives,thus having the potential to support the decision-making of urban planners and stockholders in revising and updating the existing detailed master plan of land use.展开更多
This paper uses the Butterfly Optimization Algorithm(BOA)with dominated sorting and crowding distance mechanisms to solve multi-objective optimization problems.There is also an improvement to the original version of B...This paper uses the Butterfly Optimization Algorithm(BOA)with dominated sorting and crowding distance mechanisms to solve multi-objective optimization problems.There is also an improvement to the original version of BOA to alleviate its drawbacks before extending it into a multi-objective version.Due to better coverage and a well-distributed Pareto front,non-dominant rankings are applied to the modified BOA using the crowding distance strategy.Seven benchmark functions and eight real-world problems have been used to test the performance of multi-objective non-dominated advanced BOA(MONSBOA),including unconstrained,constrained,and real-world design multiple-objective,highly nonlinear constraint problems.Various performance metrics,such as Generational Distance(GD),Inverted Generational Distance(IGD),Maximum Spread(MS),and Spacing(S),have been used for performance comparison.It is demonstrated that the new MONSBOA algorithm is better than the compared algorithms in more than 80%occasions in solving problems with a variety of linear,nonlinear,continuous,and discrete characteristics based on the Pareto front when compared quantitatively.From all the analysis,it may be concluded that the suggested MONSBOA is capable of producing high-quality Pareto fronts with very competitive results with rapid convergence.展开更多
Silicon Carbide (SiC) machining by traditional methods with regards to its high hardness is not possible. Electro Discharge Machining, among non-traditional machining methods, is used for machining of SiC. The present...Silicon Carbide (SiC) machining by traditional methods with regards to its high hardness is not possible. Electro Discharge Machining, among non-traditional machining methods, is used for machining of SiC. The present work is aimed to optimize the surface roughness and material removal rate of electro discharge machining of SiC parameters simultaneously. As the output parameters are conflicting in nature, so there is no single combination of machining parameters, which provides the best machining performance. Artificial neural network (ANN) with back propagation algorithm is used to model the process. A multi-objective optimization method, non-dominating sorting genetic algorithm-II is used to optimize the process. Affects of three important input parameters of process viz., discharge current, pulse on time (Ton), pulse off time (Toff) on electric discharge machining of SiC are considered. Experiments have been conducted over a wide range of considered input parameters for training and verification of the model. Testing results demonstrate that the model is suitable for predicting the response parameters. A pareto-optimal set has been predicted in this work.展开更多
The progress of modern industry has given rise to great requirements for network transmission latency and reliability in domains such as smart grid and intelligent driving.To address these challenges,the concept of Ti...The progress of modern industry has given rise to great requirements for network transmission latency and reliability in domains such as smart grid and intelligent driving.To address these challenges,the concept of Time-sensitive networking(TSN)is proposed by IEEE 802.1TSN working group.In order to achieve low latency,Cyclic queuing and forwarding(CQF)mechanism is introduced to schedule Timetriggered(TT)flows.In this paper,we construct a TSN model based on CQF and formulate the flow scheduling problem as an optimization problem aimed at maximizing the success rate of flow scheduling.The problem is tackled by a novel algorithm that makes full use of the characteristics and the relationship between the flows.Firstly,by K-means algorithm,the flows are initially partitioned into subsets based on their correlations.Subsequently,the flows within each subset are sorted by a new special criteria extracted from multiple features of flow.Finally,a flow offset selecting method based on load balance is used for resource mapping,so as to complete the process of flow scheduling.Experimental results demonstrate that the proposed algorithm exhibits significant advantages in terms of scheduling success rate and time efficiency.展开更多
The somatotopic representation of specific body parts is a well-established spatial organizational principle in the primary somatosensory and motor cortices.
The main function of electronic support measure system is to detect threating signals in order to take countermeasures against them. To accomplish this objective, a process of associating each interleaved pulse with i...The main function of electronic support measure system is to detect threating signals in order to take countermeasures against them. To accomplish this objective, a process of associating each interleaved pulse with its emitter must be done. This process is termed sorting or de-interleaving. A novel point symmetry based radar sorting (PSBRS) algorithm is addressed. In order to deal with all kinds of radar signals, the symmetry measure distance is used to cluster pulses instead of the conventional Euclidean distance. The reference points of the symmetrical clusters are initialized by the alternative fuzzy c-means (AFCM) algorithm to ameliorate the effects of noise and the false sorting. Besides, the density filtering (DF) algorithm is proposed to discard the noise pulses or clutter. The performance of the algorithm is evaluated under the effects of noise and missing pulses. It has been observed that the PSBRS algorithm can cope with a large number of noise pulses and it is completely independent of missing pulses. Finally, PSBRS is compared with some benchmark algorithms, and the simulation results reveal the feasibility and efficiency of the algorithm.展开更多
Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore ...Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings production.However,long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology,equipment sorting actuator,and information processing algorithm.The high precision,strong anti-interference capability,and high speed of these factors guarantee the separation efficiency of intelligent ore sorting equipment.Color ore sorter,X-ray ore transmission sorter,dual-energy X-ray transmission ore sorter,X-ray fluorescence ore sorter,and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting efficiency.With the continuous improvement of mine automation level,the application of online element rapid analysis technology with high speed,high precision,and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the future.Laser-induced breakdown spectroscopy,transientγneutron activation analysis,online Fourier transform infrared spectroscopy,and nuclear magnetic resonance techniques will promote the development of ore sorting equipment.In addition,the improvement and joint application of additional high-speed and high-precision operation algorithms(such as peak area,principal component analysis,artificial neural network,partial least squares,and Monte Carlo library least squares methods)are an essential part of the development of intelligent ore sorting equipment in the future.展开更多
A novel class of periodically changing features hidden in radar pulse sequence environment,named G features,is proposed.Combining fractal theory and Hilbert-Huang transform,the features are extracted using changing ch...A novel class of periodically changing features hidden in radar pulse sequence environment,named G features,is proposed.Combining fractal theory and Hilbert-Huang transform,the features are extracted using changing characteristics of pulse parameters in radar emitter signals.The features can be applied in modern complex electronic warfare environment to address the issue of signal sorting when radar emitter pulse signal parameters severely or even completely overlap.Experiment results show that the proposed feature class and feature extraction method can discriminate periodically changing pulse sequence signal sorting features from radar pulse signal flow with complex variant features,therefore provide a new methodology for signal sorting.展开更多
The deterministic lateral displacement (DLD) is an important method used to sort particles and cells of different sizes. In this paper, the flexible cell sorting with the DLD method is studied by using a numerical mod...The deterministic lateral displacement (DLD) is an important method used to sort particles and cells of different sizes. In this paper, the flexible cell sorting with the DLD method is studied by using a numerical model based on the immersed boundary-lattice Boltzmann method (IB-LBM). In this model, the fluid motion is solved by the LBM, and the cell membrane-fluid interaction is modeled with the LBM. The proposed model is validated by simulating the rigid particle sorted with the DLD method, and the results are found in good agreement with those measured in experiments. We first study the effect of flexibility on a single cell and multiple cells continuously going through a DLD device. It is found that the cell flexibility can significantly affect the cell path, which means the flexibility could have significant effects on the continuous cell sorting by the DLD method. The sorting characteristics of white blood cells and red blood cells are further studied by varying the spatial distribution of cylinder arrays and the initial cell-cell distance. The numerical results indicate that a well concentrated cell sorting can be obtained under a proper arrangement of cylinder arrays and a large enough initial cell-cell distance.展开更多
Common sorting method have low sorting rates and is sensitive to the Signal-to-Noise Ratio(SNR),wavelet characteristics of Wigner-Ville distribution are applied to sort unknown complicated radar signal,high sorting ac...Common sorting method have low sorting rates and is sensitive to the Signal-to-Noise Ratio(SNR),wavelet characteristics of Wigner-Ville distribution are applied to sort unknown complicated radar signal,high sorting accuracy can be got.The Wigner-Ville distribution of received signal is calculated,then it is predigested to two-dimensional characteristics.Using wavelet transformation to extract characteristics from two-dimensional of Wigner-Ville distribution,the best characteristics are selected to be used as sorting parameters.Experiment results demonstrated that the characteristics of eight typical radar emitter signals extracted by this method showed good performance of noise-resistance and clustering at large-scale SNR.展开更多
Objective: In this paper we compared the two methods of cell sorting (magnetic cell sorting and flow cytometry sorting) for the isolation and function analysis of mouse CD4+ CD25+ regulatory T (Treg) cells, in order t...Objective: In this paper we compared the two methods of cell sorting (magnetic cell sorting and flow cytometry sorting) for the isolation and function analysis of mouse CD4+ CD25+ regulatory T (Treg) cells, in order to inform further studies in Treg cell function. Methods: We separately used magnetic cell sorting and flow cytometry sorting to identify CD4+ CD25+ Treg cells. After magnetic cell separation, we further used flow cytometry to analyze the purity of CD4+ CD25+ Treg cells, trypan blue staining to detect cell viability, and propidium iodide (PI) staining to assess the cell viability. We detected the immune inhibition of CD4+ CD25+ Treg cells in the in vitro proliferation experiments. Results: The results showed that compared to flow cytometry sorting, magnetic cell sorting took more time and effort, but fewer live cells were obtained than with flow cytometry sorting. The CD4+ CD25+ Treg cells, however, obtained with both methods have similar immunosuppressive capacities. Conclusion: The result suggests that both methods can be used in isolating CD4+ CD25+ Treg cells, and one can select the best method according to specific needs and availability of the methodologies.展开更多
基金National Natural Science Foundation of China,Grant/Award Number:32302826 and 32372961Jilin Provincial Special Project for Health Research Talents,Grant/Award Number:2020SCZ40China Postdoctoral Science Foundation,Grant/Award Number:2023M740623。
文摘Background:Mastitis seriously affects the mammary health of humans and animals.Studies have found that inflammation and oxidative stress play key roles in the occur-rence and development of mastitis.Therefore,in-depth research on related molecular mechanisms is of great significance.Methods:Postpartum mice were anesthetized with pentobarbital and administered lipopolysaccharide to develop the mouse mastitis model.Proteomic analysis was per-formed to compare protein expression in mitochondria-associated endoplasmic retic-ulum membranes(MAM)from two mouse mammary gland groups.Western blot was used to detect the expression of MAM-related proteins in mitochondria.AlphaFold3 was used to predict the molecular structures of phosphofurin acidic cluster sorting protein 2(PACS2)and mitofusin 2(MFN2)and their interaction levels.The MFN2-PACS2 interaction was investigated using co-immunoprecipitation and small interfer-ing RNA.Results:The results showed that the inflammation level in the mammary gland tissue of mice with mastitis significantly increased,the total antioxidant capacity decreased,and the expression of MAM-related proteins MFN2 and PACS2 was significantly downregulated.In cell experiments,overexpression of MFN2 can inhibit inflamma-tion and oxidative stress responses,and promote the interaction between MFN2 and PACS2 to affect the formation of MAMs.Conclusion:In summary,this study suggests that mastitis can alter the expression of MAM-related proteins in mouse breast tissue.The interaction between MFN2 and PACS2 regulates the formation of MAMs.Overexpression of MFN2 can promote the formation of MAMs and inhibit inflammation and oxidative stress response in mam-mary epithelial cells.Our results provided a new theoretical basis and potential thera-peutic targets for the prevention and treatment of mastitis.
基金Project supported by the National Basic Research Program of China (973 Program) (No. 2007CB714600)
文摘The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an example, a 5 MW wind turbine blade design is presented by taking the maximum power coefficient and the minimum blade mass as the optimization objectives. The optimal results show that this algorithm has good performance in handling the multi-objective optimization of wind turbines, and it gives a Pareto-optimal solution set rather than the optimum solutions to the conventional multi objective optimization problems. The wind turbine blade optimization method presented in this paper provides a new and general algorithm for the multi-objective optimization of wind turbines.
基金Foundation item： Projects（61102106, 61102105） supported by the National Natural Science Foundation of China Project（2013M530148） supported by China Postdoctoral Science Foundation Project（HEUCF120806） supported by the Fundamental Research Funds for the Central Universities of China
文摘In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.
基金the Natural Science Key Foundation of Heilongjiang Province of China (No. ZJG0503) China-UK Sci-ence Network from Royal Society UK
文摘Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-II into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by in-troduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated;this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions.
基金supported by National Natural Science Foundation of China(No.60474059)Hi-tech Research and Development Program of China(863 Program,No.2006AA04Z160).
文摘Vehicle routing problem in distribution(VRPD)is a widely used type of vehicle routing problem(VRP),which has been proved as NP-Hard,and it is usually modeled as single objective optimization problem when modeling.For multi-objective optimization model,most researches consider two objectives.A multi-objective mathematical model for VRP is proposed,which considers the number of vehicles used,the length of route and the time arrived at each client.Genetic algorithm is one of the most widely used algorithms to solve VRP.As a type of genetic algorithm(GA),non-dominated sorting in genetic algorithm-Ⅱ(NSGA-Ⅱ)also suffers from premature convergence and enclosure competition.In order to avoid these kinds of shortage,a greedy NSGA-Ⅱ(GNSGA-Ⅱ)is proposed for VRP problem.Greedy algorithm is implemented in generating the initial population,cross-over and mutation.All these procedures ensure that NSGA-Ⅱis prevented from premature convergence and refine the performance of NSGA-Ⅱat each step.In the distribution problem of a distribution center in Michigan,US,the GNSGA-Ⅱis compared with NSGA-Ⅱ.As a result,the GNSGA-Ⅱis the most efficient one and can get the most optimized solution to VRP problem.Also,in GNSGA-Ⅱ,premature convergence is better avoided and search efficiency has been improved sharply.
基金supported by the Styrelsen för Internationellt Utvecklingssamarbete.
文摘With the continuous increase of rapid urbanization and population growth,sustainable urban land-use planning is becoming a more complex and challenging task for urban planners and decision-makers.Multi-objective land-use allocation can be regarded as a complex spatial optimization problem that aims to achieve the possible trade-offs among multiple and conflicting objectives.This paper proposes an improved Non-dominated Sorting Biogeography-Based Optimization(NSBBO)algorithm for solving the multi-objective land-use allocation problem,in which maximum accessibility,maximum compactness,and maximum spatial integration were formulated as spatial objectives;and space syntax analysis was used to analyze the potential movement patterns in the new urban planning area of the city of Kigali,Rwanda.Efficient Non-dominated Sorting(ENS)algorithm and crossover operator were integrated into classical NSBBO to improve the quality of non-dominated solutions,and local search ability,and to accelerate the convergence speed of the algorithm.The results showed that the proposed NSBBO exhibited good optimal solutions with a high hypervolume index compared to the classical NSBBO.Furthermore,the proposed algorithm could generate optimal land use scenarios according to the preferred objectives,thus having the potential to support the decision-making of urban planners and stockholders in revising and updating the existing detailed master plan of land use.
文摘This paper uses the Butterfly Optimization Algorithm(BOA)with dominated sorting and crowding distance mechanisms to solve multi-objective optimization problems.There is also an improvement to the original version of BOA to alleviate its drawbacks before extending it into a multi-objective version.Due to better coverage and a well-distributed Pareto front,non-dominant rankings are applied to the modified BOA using the crowding distance strategy.Seven benchmark functions and eight real-world problems have been used to test the performance of multi-objective non-dominated advanced BOA(MONSBOA),including unconstrained,constrained,and real-world design multiple-objective,highly nonlinear constraint problems.Various performance metrics,such as Generational Distance(GD),Inverted Generational Distance(IGD),Maximum Spread(MS),and Spacing(S),have been used for performance comparison.It is demonstrated that the new MONSBOA algorithm is better than the compared algorithms in more than 80%occasions in solving problems with a variety of linear,nonlinear,continuous,and discrete characteristics based on the Pareto front when compared quantitatively.From all the analysis,it may be concluded that the suggested MONSBOA is capable of producing high-quality Pareto fronts with very competitive results with rapid convergence.
文摘Silicon Carbide (SiC) machining by traditional methods with regards to its high hardness is not possible. Electro Discharge Machining, among non-traditional machining methods, is used for machining of SiC. The present work is aimed to optimize the surface roughness and material removal rate of electro discharge machining of SiC parameters simultaneously. As the output parameters are conflicting in nature, so there is no single combination of machining parameters, which provides the best machining performance. Artificial neural network (ANN) with back propagation algorithm is used to model the process. A multi-objective optimization method, non-dominating sorting genetic algorithm-II is used to optimize the process. Affects of three important input parameters of process viz., discharge current, pulse on time (Ton), pulse off time (Toff) on electric discharge machining of SiC are considered. Experiments have been conducted over a wide range of considered input parameters for training and verification of the model. Testing results demonstrate that the model is suitable for predicting the response parameters. A pareto-optimal set has been predicted in this work.
基金supported by Science and Technology Project of State Grid Corporation Headquarters under Grant 5108-202218280A-2-170-XG(Development and Application of Power Time-Sensitive Network Switching Chip。
文摘The progress of modern industry has given rise to great requirements for network transmission latency and reliability in domains such as smart grid and intelligent driving.To address these challenges,the concept of Time-sensitive networking(TSN)is proposed by IEEE 802.1TSN working group.In order to achieve low latency,Cyclic queuing and forwarding(CQF)mechanism is introduced to schedule Timetriggered(TT)flows.In this paper,we construct a TSN model based on CQF and formulate the flow scheduling problem as an optimization problem aimed at maximizing the success rate of flow scheduling.The problem is tackled by a novel algorithm that makes full use of the characteristics and the relationship between the flows.Firstly,by K-means algorithm,the flows are initially partitioned into subsets based on their correlations.Subsequently,the flows within each subset are sorted by a new special criteria extracted from multiple features of flow.Finally,a flow offset selecting method based on load balance is used for resource mapping,so as to complete the process of flow scheduling.Experimental results demonstrate that the proposed algorithm exhibits significant advantages in terms of scheduling success rate and time efficiency.
文摘The somatotopic representation of specific body parts is a well-established spatial organizational principle in the primary somatosensory and motor cortices.
基金supported by the National Natural Science Foundation of China(61172116)
文摘The main function of electronic support measure system is to detect threating signals in order to take countermeasures against them. To accomplish this objective, a process of associating each interleaved pulse with its emitter must be done. This process is termed sorting or de-interleaving. A novel point symmetry based radar sorting (PSBRS) algorithm is addressed. In order to deal with all kinds of radar signals, the symmetry measure distance is used to cluster pulses instead of the conventional Euclidean distance. The reference points of the symmetrical clusters are initialized by the alternative fuzzy c-means (AFCM) algorithm to ameliorate the effects of noise and the false sorting. Besides, the density filtering (DF) algorithm is proposed to discard the noise pulses or clutter. The performance of the algorithm is evaluated under the effects of noise and missing pulses. It has been observed that the PSBRS algorithm can cope with a large number of noise pulses and it is completely independent of missing pulses. Finally, PSBRS is compared with some benchmark algorithms, and the simulation results reveal the feasibility and efficiency of the algorithm.
基金supported by the National Science and Technology Support Program of China(No.2012BAC11B07)the Jiangxi Science and Technology Innovation Base Plan(No.20212BCD42017)。
文摘Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings production.However,long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology,equipment sorting actuator,and information processing algorithm.The high precision,strong anti-interference capability,and high speed of these factors guarantee the separation efficiency of intelligent ore sorting equipment.Color ore sorter,X-ray ore transmission sorter,dual-energy X-ray transmission ore sorter,X-ray fluorescence ore sorter,and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting efficiency.With the continuous improvement of mine automation level,the application of online element rapid analysis technology with high speed,high precision,and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the future.Laser-induced breakdown spectroscopy,transientγneutron activation analysis,online Fourier transform infrared spectroscopy,and nuclear magnetic resonance techniques will promote the development of ore sorting equipment.In addition,the improvement and joint application of additional high-speed and high-precision operation algorithms(such as peak area,principal component analysis,artificial neural network,partial least squares,and Monte Carlo library least squares methods)are an essential part of the development of intelligent ore sorting equipment in the future.
基金supported by the National Natural Science Foundation of China (60872108)the Postdoctoral Science Foundation of China(200902411+3 种基金20080430903)Heilongjiang Postdoctoral Financial Assistance (LBH-Z08129)the Scientific and Technological Creative Talents Special Research Foundation of Harbin Municipality (2008RFQXG030)Central University Basic Research Professional Expenses Special Fund Project
文摘A novel class of periodically changing features hidden in radar pulse sequence environment,named G features,is proposed.Combining fractal theory and Hilbert-Huang transform,the features are extracted using changing characteristics of pulse parameters in radar emitter signals.The features can be applied in modern complex electronic warfare environment to address the issue of signal sorting when radar emitter pulse signal parameters severely or even completely overlap.Experiment results show that the proposed feature class and feature extraction method can discriminate periodically changing pulse sequence signal sorting features from radar pulse signal flow with complex variant features,therefore provide a new methodology for signal sorting.
基金supported by the National Natural Science Foundation of China (Grant 81301291)the Beijing Higher Education Young Elite Teacher Project (Grant YETP1208)UNSW Special Research Grants Program
文摘The deterministic lateral displacement (DLD) is an important method used to sort particles and cells of different sizes. In this paper, the flexible cell sorting with the DLD method is studied by using a numerical model based on the immersed boundary-lattice Boltzmann method (IB-LBM). In this model, the fluid motion is solved by the LBM, and the cell membrane-fluid interaction is modeled with the LBM. The proposed model is validated by simulating the rigid particle sorted with the DLD method, and the results are found in good agreement with those measured in experiments. We first study the effect of flexibility on a single cell and multiple cells continuously going through a DLD device. It is found that the cell flexibility can significantly affect the cell path, which means the flexibility could have significant effects on the continuous cell sorting by the DLD method. The sorting characteristics of white blood cells and red blood cells are further studied by varying the spatial distribution of cylinder arrays and the initial cell-cell distance. The numerical results indicate that a well concentrated cell sorting can be obtained under a proper arrangement of cylinder arrays and a large enough initial cell-cell distance.
基金Supported by the National Science and Technology Supported Program of China(No.2011BAH24B05)
文摘Common sorting method have low sorting rates and is sensitive to the Signal-to-Noise Ratio(SNR),wavelet characteristics of Wigner-Ville distribution are applied to sort unknown complicated radar signal,high sorting accuracy can be got.The Wigner-Ville distribution of received signal is calculated,then it is predigested to two-dimensional characteristics.Using wavelet transformation to extract characteristics from two-dimensional of Wigner-Ville distribution,the best characteristics are selected to be used as sorting parameters.Experiment results demonstrated that the characteristics of eight typical radar emitter signals extracted by this method showed good performance of noise-resistance and clustering at large-scale SNR.
基金Project supported by the National Natural Science Foundation of China (Nos. 30872578 and 30753761)the Natural Science Founda-tion of Shanxi Province (No. SJ08C201)+1 种基金the Science and Technology Key Projects Foundation of Shanxi Province (No. 2008K13-04)the Science and Technology Plan Projects Foundation of Xi’an (No. SF08006-2), China
文摘Objective: In this paper we compared the two methods of cell sorting (magnetic cell sorting and flow cytometry sorting) for the isolation and function analysis of mouse CD4+ CD25+ regulatory T (Treg) cells, in order to inform further studies in Treg cell function. Methods: We separately used magnetic cell sorting and flow cytometry sorting to identify CD4+ CD25+ Treg cells. After magnetic cell separation, we further used flow cytometry to analyze the purity of CD4+ CD25+ Treg cells, trypan blue staining to detect cell viability, and propidium iodide (PI) staining to assess the cell viability. We detected the immune inhibition of CD4+ CD25+ Treg cells in the in vitro proliferation experiments. Results: The results showed that compared to flow cytometry sorting, magnetic cell sorting took more time and effort, but fewer live cells were obtained than with flow cytometry sorting. The CD4+ CD25+ Treg cells, however, obtained with both methods have similar immunosuppressive capacities. Conclusion: The result suggests that both methods can be used in isolating CD4+ CD25+ Treg cells, and one can select the best method according to specific needs and availability of the methodologies.
