EEMD and bidimensional RLS to suppress physiological interference for heterogeneous distribution in fNIRS study

Near-infrared spectroscopy(NIRS)can provide the hemodynamics information based on the hemoglobin concentration representing the blood oxygen metabolism of the cerebral cortical,which can be deployed for the cerebral function study.However,NIRS-based cerebral function detection accuracy can be signi¯cantly in°uenced by the physiological activities such as cardic cycle,respiration,spontaneous low-frequency oscillation and ultra-low frequency oscillation.The distribution difference of the capillary,artery and vein leads to the heterogeneity feature of the cerebral tissues.In the case that the heterogeneity is not serious,good detection accuracy and stable performance can be achieved through the regression analysis as the reference signal can well represent the interference in the measurement signal when conducting the multi-distance measurement approach.The direct use of the reference signal to estimate the interference is not able to achieve good performance in the case that the heterogeneity is serious.In this study,the cerebral function activity signal is extracted using recursive least square(RLS)method based on the multi-distance measurement method in which the reference signal is processed by ensemble empirical mode decomposition(EEMD)algorithm.The temporal and dimensional correlation of the neighboring sampling values are applied to estimate the interference in the measurement signal.Monte Carlo simulation based on a heterogeneous model is adopted here to investigate the effectiveness of this methodology.The results show that this methodology can effectively suppress the physiological interference and improve the detection accuracy of cerebral activity signal.

Competitive and Cooperative-Based Strength Pareto Evolutionary Algorithm for Green Distributed Heterogeneous Flow Shop Scheduling

This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm(CCSPEA)which contains the following features:1)An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence.2)A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution.3)A competitive selection is designed which divides the population into a winner and a loser swarms based on the comprehensive metric.4)A cooperative evolutionary schema is proposed for winner and loser swarms to accelerate the convergence of global search.5)Five local search strategies based on problem knowledge are designed to improve convergence.6)Aproblem-based energy-saving strategy is presented to reduce TEC.Finally,to evaluate the performance of CCSPEA,it is compared to four state-of-art and run on 22 instances based on the Taillard benchmark.The numerical experiment results demonstrate that 1)the proposed comprehensive metric can efficiently represent the heuristic information of each solution to help the later step divide the population.2)The global search based on the competitive and cooperative schema can accelerate loser solutions convergence and further improve the winner’s exploration.3)The problembased initialization,local search,and energy-saving strategies can efficiently reduce the makespan and TEC.4)The proposed CCSPEA is superior to the state-of-art for solving DHPFSP.

Resilience approach for heterogeneous distributed networked unmanned weapon systems

Disconnection in the distributed heterogeneous networked unmanned weapon systems is caused by multiple weapon units' failure.The technical routes were analyzed to achieve resilience in the disconnection situation.A heterogeneous distributed network model of networked unmanned weapon systems was established.And an approach of adding relay weapon units was proposed to achieve fault tolerance after weapon units' failure due to attack or energy exhaustion.An improved genetic algorithm was proposed to determine and optimize the position of the relay weapon units.Simulation results in the MATLAB show that the improved resilience-based genetic algorithm can restore the network connection maximally when the number of relay units is limited,the network can keep on working after failure,and the implementation cost is controlled in a reasonable range.

Dynamic reconfiguration for TEG systems under heterogeneous temperature distribution via adaptive coordinated seeker

A thermoelectric generation(TEG)system has the weakness of relatively low thermoelectric conversion efficiency caused by heterogeneous temperature distribution(HgTD).Dynamic reconfiguration is an effective technique to improve its overall energy efficiency under HgTD.Nevertheless,numerous combinations of electrical switches make dynamic reconfiguration a complex combinatorial optimization problem.This paper aims to design a novel adaptive coordinated seeker(ACS)based on an optimal configuration strategy for large-scale TEG systems with series-paral-lel connected modules under HgTDs.To properly balance global exploration and local exploitation,ACS is based on'divide-and-conquer'parallel computing,which synthetically coordinates the local searching capability of tabu search(TS)and the global searching capability of a pelican optimization algorithm(POA)during iterations.In addition,an equivalent re-optimization strategy for a reconfiguration solution obtained by meta-heuristic algorithms(MhAs)is proposed to reduce redundant switching actions caused by the randomness of MhAs.Two case studies are carried out to assess the feasibility and superiority of AcS in comparison with the artificial bee colony algorithm,ant colony optimization,genetic algorithm,particle swarm optimization,simulated annealing algorithm,TS,and POA.Simulation results indicate that ACS can realize fast and stable dynamic reconfiguration of a TEG system under HgTDs.In addition,RTLAB platform-based hardware-in-the-loop experiments are carried out to further validate the hardware implemen-tation feasibility.

Origin of strong solid solution strengthening in the CrCoNi-W medium entropy alloy

Solid solution strengthening is one of the most conventional strategies for optimizing alloys strength,while the corresponding mechanisms can be more complicated than we traditionally thought specifically as heterogeneity of microstructure is involved.In this work,by comparing the change of chemical distribution,dislocation behaviors and mechanical properties after doping equivalent amount of tungsten(W)atoms in CrCoNi alloy and pure Ni,respectively,it is found that the alloying element W in CrCoNi alloy resulted in much stronger strengthening effect due to the significant increase of heterogeneity in chemical distribution after doping trace amount of W.The large atomic scale concentration fluctuation of all elements in CrCoNi-3W causes dislocation motion via strong nanoscale segment detrapping and severe dislocation pile up which is not the case in Ni-3W.The results revealed the high sensitivity of elements distribution in multi-principle element alloys to composition and the significant consequent influence in tuning the mechanical properties,giving insight for complex alloy design.

Effects of plant species richness on stand structure and productivity

Aims Aboveground biomass production commonly increases with species richness in plant biodiversity experiments.Little is known about the direct mechanisms that cause this result.We tested if by occupying different heights and depths above and below ground,and by optimizing the vertical distribution of leaf nitrogen,species in mixtures can contribute to increased resource uptake and,thus,increased productivity of the community in comparison with monocultures.Methods We grew 24 grassland plant species,grouped into four nonoverlapping species pools,in monoculture and 3-and 6-species mixture in spatially heterogeneous and uniform soil nutrient conditions.Layered harvests of above-and belowground biomass,as well as leaf nitrogen and light measurements,were taken to assess vertical canopy and root space structure.Important Findings The distribution of leaf mass was shifted toward greater heights and light absorption was correspondingly enhanced in mixtures.How ever,only some mixtures had leaf nitrogen concentration profiles predicted to optimize whole-community carbon gain,whereas in other mixtures species seemed to behave more‘selfish’.Nevertheless,even in these communities,biomass production increased with species richness.The distribution of root biomass below ground did not change from monocultures to three-and six-species mixtures and there was also no indication that mixtures were better than monocultures at extracting heterogeneously as compared to homogeneously distributed soil resources.We conclude that positive biodiversity effect on aboveground biomass production cannot easily be explained by a single or few common mechanisms of differential space use.Rather,it seems that mechanisms vary with the particular set of species combined in a community.

Proportional Current Sharing Based on Periodic Dynamic Event-driven H_(∞) Consensus in DC Microgrids with Power Coupling

Although the proportional current sharing has been widely studied,the heterogeneous characteristic of the different interfaced converters and power coupling terms among distributed generators(DGs)are rarely considered.Therefore,this paper proposes a secondary H_(∞)consensus method with a periodic dynamic event-driven scheme for dc microgrids with power coupling to accomplish the precise proportional current-sharing.It is useful for reducing carbon.First,a generalized converter is constructed through equivalent transformation between rectifier and boost converter.Moreover,the heterogeneous characteristic of the interfaced converters regarding different DGs,such as wind and solar generators,is embedded into controller design.Furthermore,the standard linear heterogeneous multi-agent system with power coupling term is built.On this basis,the problem of proportional current sharing is modified into the output consistency problem of multi-agent systems.Furthermore,the H_(∞)consensus approach is proposed to accomplish the precise proportional current sharing.Meanwhile,to shorten communication bandwidth,the periodic dynamic event-driven communication strategy is designed.Compared with traditional event-driven communication schemes,a lower communication frequency has been obtained through the proposed communication scheme.In addition,this communication scheme not only avoids Zeno-behavior,but also acquires the smallest sampling time interval.Finally,effectiveness of the proposed approach is verified by two test systems.