This work studied the preparation of starting powder mixture influenced by milling time and its effect on the particle morphology （especially the shape） and, consequently, density and compression properties of in si...This work studied the preparation of starting powder mixture influenced by milling time and its effect on the particle morphology （especially the shape） and, consequently, density and compression properties of in situ Ti-TiB composite materials produced by selective laser melting （SLM） technology. Starting powder composite system was prepared by mixing 95 wt% commercially pure titanium （CP-Ti） and 5 wt% titanium diboride （TiB2） powders and subsequently milled for two different times （i.e. 2 h and 4 h）. The milled powder mixtures after 2 h and 4 h show nearly spherical and irregular shape, respectively. Subsequently, the resultant Ti-5 wt% TiB2 powder mixtures were used for SLM processing. Scanning electron microscopy image of the SLM-processed Ti-TiB composite samples show needle-shape TiB phase distributed across the Ti matrix, which is the product of an in-situ chemical reaction between Ti and TiB2 during SLM. The Ti-TiB composite samples prepared from 2 h and 4 h milled Ti-TiB2 powders show different relative densities of 99.5% and 95.1%, respectively. Also, the compression properties such as ultimate strength and compression strain for the 99.5% dense composite samples is 1421 MPa and 17.8%, respectively, which are superior to those （883 MPa and 5.5%, respectively） for the 95.1% dense sample. The results indicate that once Ti and TiB2 powders are connected firmly to each other and powder mixture of nearly spherical shape is obtained, there is no additional benefit in increasing the milling time and, instead, it has a negative effect on the density （i.e. increasing porosity level） of the Ti-TiB composite materials and their mechanical properties.展开更多
The loss of rare earths(REs)takes place during the pre-decalcification process of mixed rare earth concentrate.In an effort to reduce such RE loss,a novel idea to improve the leaching selectivity of Ca to REs by apply...The loss of rare earths(REs)takes place during the pre-decalcification process of mixed rare earth concentrate.In an effort to reduce such RE loss,a novel idea to improve the leaching selectivity of Ca to REs by applying selective mechanical activation was proposed.First,regarding the key minerals affecting the leaching selectivity of Ca to REs,the differences in the mechanical activation behaviors of CaF_(2) and REFCO_(3) were studied,and we find that the lattice strain of CaF_(2) increases from 0.21%to 0.42%,whereas that of REFCO_(3) increases from 0.31%to 0.40%.Notably,CaF_(2) demonstrates a larger lattice strain than REFCO_(3),indicating greater mechanical activation energy storage and higher leaching activity.Next,the HCl leaching process was studied.A significant leaching selectivity of Ca to REs,from 21.6 to 35.1,is achieved through mechanical activation.The Ca leaching rate reaches 80.7%when the RE loss is 2.3%in the activated sample.This study provides an novel approach for achieving selective extraction of specific components via mechanical activation pretreatment.展开更多
For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater survei...For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater surveillance,location tracking system,etc.Most of the IoUT applications rely on acoustic medium.The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate,attenuation,limited bandwidth,limited battery,limited memory,connectivity problem,etc.One of the significant applications of IoUT include monitoring underwater diver networks.In order to perform a reliable and energy-efficient communication system in the underwater diver networks,a smart underwater hybrid softwaredefined modem(UHSDM)for the mobile ad-hoc network was developed that is used for selecting the best channel/medium among acoustic,visible light communication(VLC),and infrared(IR)based on the criteria established within the system.However,due to the mobility of underwater divers,the developed UHSDMmeets the challenges such as connectivity errors,frequent link failure,transmission delay caused by re-routing,etc.During emergency,the divers are most at the risk of survival.To deal with diver mobility,connectivity,energy efficiency,and reducing the latency in ADN,a handover mechanism based on pre-built UHSDM is proposed in this paper.This paper focuses on(1)design of UHSDM for ADN(2)propose the channel selection mechanism in UHSDM for selecting the best medium for handover and(3)propose handover protocol inADN.The implementation result shows that the proposed mechanism can be used to find the new route for divers in advance and the latency can be reduced significantly.Additionally,this paper shows the real field experiment of air tests and underwater tests with various distances.This research will contribute much to the profit of researchers in underwater diver networks and underwater networks,for improving the quality of services(QoS)of underwater applications.展开更多
Firstly data standardization technology and combined classification method have been applied to carry out classification of kinematic behaviors and mechanisms in the mapping field between the kinematic behavior level ...Firstly data standardization technology and combined classification method have been applied to carry out classification of kinematic behaviors and mechanisms in the mapping field between the kinematic behavior level and the mechanism level of conceptual design.The principle of computer coding and storing have been built to give a fast and broad selection of mechanisms that meets the requirements of basic motion characters.Then on the basis of mentioned above,the heuristic matching propagation principle (HMPP) of kinematic behaviors and its true table serves as a guide to perform mechanism types selection.Finally an application is given to indicate its practicability and effectiveness.展开更多
In order to improve the reliability of the mechanical movement of the rotary electronic dobby, the kinematics analysis of the heald selection mechanism is carried out and the simulation is carried out with Matlab. Fir...In order to improve the reliability of the mechanical movement of the rotary electronic dobby, the kinematics analysis of the heald selection mechanism is carried out and the simulation is carried out with Matlab. Firstly, the operation mechanism of the heald selection mechanism is analyzed in detail. The conjugate cam is mapped. The cam profile curve is fitted with cubic spline interpolation. Secondly, based on the overall analysis method and the complex vector method, the kinematics analysis of the key components after the high pair low generation is performed, and the angular displacement and angular velocity of each component are calculated with the rotation of the active cam. Finally, the movement curve diagram is drawn with Matlab, which lays the foundation for the dynamic analysis and in-depth study of the selection mechanism in the future.展开更多
A systematic investigation of oxidation on a superconductive Fe Te_（0.5）Se_（0.5）thin film,which was grown on Nb-doped SrTiO_3（001） by pulsed laser deposition,has been carried out.The sample was exposed to ambien...A systematic investigation of oxidation on a superconductive Fe Te_（0.5）Se_（0.5）thin film,which was grown on Nb-doped SrTiO_3（001） by pulsed laser deposition,has been carried out.The sample was exposed to ambient air for one month for oxidation.Macroscopically,the exposed specimen lost its superconductivity due to oxidation.The specimen was subjected to in situ synchrotron radiation photoelectron spectroscopy（PES） and x-ray absorption spectroscopy（XAS） measurements following cycles of annealing and argon ion etching treatments to unravel what happened in the electronic structure and composition after exposure to air.By the spectroscopic measurements,we found that the as-grown FeTe_（0.5）Se_（0.5）superconductive thin film experienced an element selective substitution reaction.The oxidation preferentially proceeds through pumping out the Te and forming Fe–O bonds by O substitution of Te.In addition,our results certify that in situ vacuum annealing and low-energy argon ion etching methods combined with spectroscopy are suitable for depth element and valence analysis of layered structure superconductor materials.展开更多
In recent years,decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios.In these algorithms,the reference vectors of the Penalty-Based bou...In recent years,decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios.In these algorithms,the reference vectors of the Penalty-Based boundary intersection(PBI)are distributed parallelly while those based on the normal boundary intersection(NBI)are distributed radially in a conical shape in the objective space.To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications,this paper addresses the improvement of the Collaborative Decomposition(CoD)method,a multi-objective decomposition technique that integrates PBI and NBI,and combines it with the Elephant Clan Optimization Algorithm,introducing the Collaborative Decomposition Multi-objective Improved Elephant Clan Optimization Algorithm(CoDMOIECO).Specifically,a novel subpopulation construction method with adaptive changes following the number of iterations and a novel individual merit ranking based onNBI and angle are proposed.,enabling the creation of subpopulations closely linked to weight vectors and the identification of diverse individuals within them.Additionally,new update strategies for the clan leader,male elephants,and juvenile elephants are introduced to boost individual exploitation capabilities and further enhance the algorithm’s convergence.Finally,a new CoD-based environmental selection method is proposed,introducing adaptive dynamically adjusted angle coefficients and individual angles on corresponding weight vectors,significantly improving both the convergence and distribution of the algorithm.Experimental comparisons on the ZDT,DTLZ,and WFG function sets with four benchmark multi-objective algorithms—MOEA/D,CAMOEA,VaEA,and MOEA/D-UR—demonstrate that CoDMOIECO achieves superior performance in both convergence and distribution.展开更多
The brain’s selective visual attention mechanism(SVAM)enables robust visual recognition in noisy environment through diverse neural action potential peaks acting as filters.Spiking neural networks(SNNs)mimic this par...The brain’s selective visual attention mechanism(SVAM)enables robust visual recognition in noisy environment through diverse neural action potential peaks acting as filters.Spiking neural networks(SNNs)mimic this paradigm but limited noise immunity and high write current density hinder brain-like efficiency.Hardware implementing SVAM necessitates spiking spintronic devices with noise-resistant and low operation current densities;such devices remain unreported.Here,we report an orbit-torque(OT)actuated ferromagnetic spiking synapse and neuron featuring a tunable peak action potential.These are more akin to the biological neurons with varying sensitivities to external sensory stimuli,thereby augmenting the perception aptitude of the system in complex surroundings.Capitalizing on the high-efficient OT,the ferromagnetic device demands a write current density of 5×10^(6) A/cm^(2),which is an order of magnitude lower than other spiking devices actuated by spin-orbit torque.Leveraging these neuromorphic devices,an all-spin SNN with low current density and tunable action potential peak has been fabricated,successfully mimicking the SVAM.In complex noise environment,the SNN achieves 92%on Cifar-10 and 95%on MNIST dataset,surpassing state-of-the-art spin-based SNNs by 5%.Our work provides a promising avenue for exploring the SVAM-inspired spiking neuromorphic devices,enhancing the bionic performance of the SNNs.展开更多
The membrane,one of the key components of flow batteries,ideally has high selectivity,conductivity,and stability.However,porous membranes prepared by conventional non-solvent-induced phase separation(NIPS)commonly suf...The membrane,one of the key components of flow batteries,ideally has high selectivity,conductivity,and stability.However,porous membranes prepared by conventional non-solvent-induced phase separation(NIPS)commonly suffer from low selectivity and poor mechanical stability.Here,we used rigid naphthalene-containing polybenzimidazole(NPBI)to prepare a porous membrane with unique egg-shaped pores by adjusting solvent/non-solvent exchange in NIPS.The dense pores with a size of 3.6Åarranged dispersedly between egg-shaped pores.The rigid NPBI and 3.6-Åsmall pores enabled the membrane high mechanical strength.The thickness was thus decreased to 1.4μm,which exhibited an ultrahigh tensile strength of 463.54 MPa.The dense pores were also smaller than hydrated vanadium ions,achieving a low permeability of 2.28×10^(-7)cm^(2)/h,indicating high selectivity.This is the first time to prepare such a highly selective and mechanically stable ultrathin porous membrane by NIPS.Importantly,the ion-transport pathways in the 1.4μm membrane were shortened,decreasing the area resistance to as low as 0.015Ωcm 2.Demonstrated in a vanadium flow battery,its coulombic efficiency was 98.57%and energy efficiency reached 81.72%at 200 mA/cm 2.This study proposes an effective strategy to prepare highperformance ultrathin porous membranes for flow batteries.展开更多
The WSN(wireless sensor network)node optimization problem faces the challenge of efficient deployment and adaptation under limited resources and a dynamically changing environment.The complex and changing deployment e...The WSN(wireless sensor network)node optimization problem faces the challenge of efficient deployment and adaptation under limited resources and a dynamically changing environment.The complex and changing deployment environment puts higher requirements on the search space,computational cost,and optimization efficiency of the algorithms.For this reason,a slime mould algorithm called SCA-SMA is proposed to solve the above problem.In SCA-SMA,a reverse Sobol sequence is used to initialize the population to increase the population diversity and improve the probability of approaching the optimal solution.To better balance local exploitation and global exploration,a dynamic selection of sine cosine update mechanism is proposed:using an optimal position selection mechanism in the global exploration phase to avoid local optima,and integrating the sine cosine algorithm in the local exploitation phase to improve the mucilage position update method,enrich the optimization search process and enhance the development capability of the algorithm.Finally,an adaptive mutation strategy can be proposed to increase the search range of the algorithm and motivate SCA-SMA to explore more promising regions.To evaluate the performance of the algorithm,SCA-SMA is experimentally validated in five different aspects.The results show that SCA-SMA is significantly competitive compared to advanced MAs.In particular,in facing the WSN node coverage problem,SCA-SMA has more obvious advantages in both average coverage and optimal coverage,which makes it possible to fully utilize the sensing range of each sensor node,while avoiding the waste of resources and the generation of monitoring blind zones.展开更多
To solve the problem of mismatching features in an experimental database, which is a key technique in the field of cross-corpus speech emotion recognition, an auditory attention model based on Chirplet is proposed for...To solve the problem of mismatching features in an experimental database, which is a key technique in the field of cross-corpus speech emotion recognition, an auditory attention model based on Chirplet is proposed for feature extraction.First, in order to extract the spectra features, the auditory attention model is employed for variational emotion features detection. Then, the selective attention mechanism model is proposed to extract the salient gist features which showtheir relation to the expected performance in cross-corpus testing.Furthermore, the Chirplet time-frequency atoms are introduced to the model. By forming a complete atom database, the Chirplet can improve the spectrum feature extraction including the amount of information. Samples from multiple databases have the characteristics of multiple components. Hereby, the Chirplet expands the scale of the feature vector in the timefrequency domain. Experimental results show that, compared to the traditional feature model, the proposed feature extraction approach with the prototypical classifier has significant improvement in cross-corpus speech recognition. In addition, the proposed method has better robustness to the inconsistent sources of the training set and the testing set.展开更多
Wireless Sensor Network(WSN)based applications has been extraordinarily helpful in monitoring interested area.Only information of surrounding environment with meaningful geometric information is useful.How to design t...Wireless Sensor Network(WSN)based applications has been extraordinarily helpful in monitoring interested area.Only information of surrounding environment with meaningful geometric information is useful.How to design the localization algorithm that can effectively extract unknown node position has been a challenge in WSN.Among all localization technologies,the Distance Vector-Hop(DV-Hop)algorithm has been most popular because it simply utilizes the hop counts as connectivity measurements.This paper proposes an improved DV-Hop based algorithm,a centroid DV-hop localization with selected anchors and inverse distance weighting schemes(SIC-DV-Hop).We adopt an inverse distance weighting method for average distance amelioration to improve accuracy.Also in this paper,we propose an inclusive checking rule to select proper anchors to avoid the inconsistency existing in centroid localization schemes.Finally,an improved multilateration centroid method is presented for the localization.Simulations are conducted on two different network topologies and experiments results show that compared with existing DV-Hop based algorithms,our algorithm can significantly improve the performance meanwhile cost less network resource.展开更多
Effective constrained optimization algorithms have been proposed for engineering problems recently.It is common to consider constraint violation and optimization algorithm as two separate parts.In this study,a pbest s...Effective constrained optimization algorithms have been proposed for engineering problems recently.It is common to consider constraint violation and optimization algorithm as two separate parts.In this study,a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems.Based on the improved pbest selection method,an adaptive differential evolution approach is proposed,which helps the population jump out of the infeasible region.If all the individuals are infeasible,the top 5%of infeasible individuals are selected.In addition,a modified truncatedε-level method is proposed to avoid trapping in infeasible regions.The proposed adaptive differential evolution approach with an improvedεconstraint processmechanism(IεJADE)is examined on CEC 2006 and CEC 2010 constrained benchmark function series.Besides,a standard IEEE-30 bus test system is studied on the efficiency of the IεJADE.The numerical analysis verifies the IεJADE algorithm is effective in comparisonwith other effective algorithms.展开更多
The artificial bee colony (ABC) algorithm is a swarm-based metaheuristic optimization technique, developed by inspiring foraging and dance behaviors of honey bee colonies. ABC consists of four phases named as initiali...The artificial bee colony (ABC) algorithm is a swarm-based metaheuristic optimization technique, developed by inspiring foraging and dance behaviors of honey bee colonies. ABC consists of four phases named as initialization, employed bee, onlooker bee and scout bee. The employed bees try to improve their solution in employed bees phase. If an employed bee cannot improve self-solution in a certain time, it becomes a scout bee. This alteration is done in the scout bee phase. The onlooker bee phase is placed where information sharing is done. Although a candidate solution improved by onlookers is chosen among the employed bee population according to fitness values of the employed bees, neighbor of candidate solution is randomly selected. In this paper, we propose a selection mechanism for neighborhood of the candidate solutions in the onlooker bee phase. The proposed selection mechanism was based on information shared by the employed bees. Average fitness value obtained by the employed bees is calculated and those better than the aver- age fitness value are written to memory board. Therefore, the onlooker bees select a neighbor from the memory board. In this paper, the proposed ABC-based method called as iABC were applied to both five numerical benchmark functions and an estimation of energy demand problem. Obtained results for the problems show that iABC is better than the basic ABC in terms of solution quality.展开更多
Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. ...Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. A variety of automated negotiation mechanisms have been proposed in the literature. The effectiveness of those mechanisms, however, may depend on the charaeteristics of the underlying negotiation problem （e.g. on the complexity of participant＇s utility functions, as well as the degree of conflict between participants）. While one mechanism may be a good choice for a negotiation problem, it may be a poor choice for another. In this paper, we pursue the problem of selecting the most effective negotiation mechanism given a particular problem by （1） defining a set of scenario metrics to capture the relevant features of negotiation problems, （2） evaluating the performance of a range of negotiation mechanisms on a diverse test suite of negotiation scenarios, （3） applying machine learning techniques to identify which mechanisms work best with which scenarios, and （4） demonstrating that using these classification rules for mechanism selection enables significantly better negotiation performance than any single mechanism alone.展开更多
A maritime target saliency detection method inspired by the stimulation competition and selection mechanism of raptor vision is presented for the airborne vision system of unmanned aerial vehicle(UAV)in an unknown mar...A maritime target saliency detection method inspired by the stimulation competition and selection mechanism of raptor vision is presented for the airborne vision system of unmanned aerial vehicle(UAV)in an unknown maritime environment.The stimulation competition and selection mechanism in the visual pathway of raptor vision based on the phenomenon of raptor capturing prey in complex scenes are studied.Then,the mathematical model of the stimulation competition and selection mechanism of raptor vision is established and employed for the salient object detection.Popular image datasets and practical scene datasets are applied to verify the effectiveness of the presented method.Results show that the detection performance of the proposed method is better than that of other comparison methods.The proposed algorithm provides an idea for maritime target salient detection and cross-domain joint mission for UAV or other unmanned equipment.展开更多
In order to solve the problems of road traffic congestion and the increasing parking time caused by the imbalance of parking lot supply and demand,this paper proposes an asymptotically optimal public parking lot locat...In order to solve the problems of road traffic congestion and the increasing parking time caused by the imbalance of parking lot supply and demand,this paper proposes an asymptotically optimal public parking lot location algorithm based on intuitive reasoning to optimize the parking lot location problem.Guided by the idea of intuitive reasoning,we use walking distance as indicator to measure the variability among location data and build a combinatorial optimization model aimed at guiding search decisions in the solution space of complex problems to find optimal solutions.First,Selective Attention Mechanism(SAM)is introduced to reduce the search space by adaptively focusing on the important information in the features.Then,Quantum Annealing(QA)algorithm with quantum tunneling effect is used to jump out of the local extremum in the search space with high probability and further approach the global optimal solution.Experiments on the parking lot location dataset in Luohu District,Shenzhen,show that the proposed method has improved the accuracy and running speed of the solution,and the asymptotic optimality of the algorithm and its effectiveness in solving the public parking lot location problem are verified.展开更多
基金supported by the Australian Research Council’s Projects Funding Scheme (No. DP110101653)the European Commission (BioTiNet-ITN G.A. No.264635)the Deutsche Forschungsgemeinschaft (SFB/Transregio 79, Project M1)
文摘This work studied the preparation of starting powder mixture influenced by milling time and its effect on the particle morphology （especially the shape） and, consequently, density and compression properties of in situ Ti-TiB composite materials produced by selective laser melting （SLM） technology. Starting powder composite system was prepared by mixing 95 wt% commercially pure titanium （CP-Ti） and 5 wt% titanium diboride （TiB2） powders and subsequently milled for two different times （i.e. 2 h and 4 h）. The milled powder mixtures after 2 h and 4 h show nearly spherical and irregular shape, respectively. Subsequently, the resultant Ti-5 wt% TiB2 powder mixtures were used for SLM processing. Scanning electron microscopy image of the SLM-processed Ti-TiB composite samples show needle-shape TiB phase distributed across the Ti matrix, which is the product of an in-situ chemical reaction between Ti and TiB2 during SLM. The Ti-TiB composite samples prepared from 2 h and 4 h milled Ti-TiB2 powders show different relative densities of 99.5% and 95.1%, respectively. Also, the compression properties such as ultimate strength and compression strain for the 99.5% dense composite samples is 1421 MPa and 17.8%, respectively, which are superior to those （883 MPa and 5.5%, respectively） for the 95.1% dense sample. The results indicate that once Ti and TiB2 powders are connected firmly to each other and powder mixture of nearly spherical shape is obtained, there is no additional benefit in increasing the milling time and, instead, it has a negative effect on the density （i.e. increasing porosity level） of the Ti-TiB composite materials and their mechanical properties.
基金Project supported by the National Natural Science Foundation of China(52004252)Natural Science Foundation ofHenan Province(222300420548)Strategic Research and Consulting Project of Chinese Academy of Engineering(2022-XBZD-07)。
文摘The loss of rare earths(REs)takes place during the pre-decalcification process of mixed rare earth concentrate.In an effort to reduce such RE loss,a novel idea to improve the leaching selectivity of Ca to REs by applying selective mechanical activation was proposed.First,regarding the key minerals affecting the leaching selectivity of Ca to REs,the differences in the mechanical activation behaviors of CaF_(2) and REFCO_(3) were studied,and we find that the lattice strain of CaF_(2) increases from 0.21%to 0.42%,whereas that of REFCO_(3) increases from 0.31%to 0.40%.Notably,CaF_(2) demonstrates a larger lattice strain than REFCO_(3),indicating greater mechanical activation energy storage and higher leaching activity.Next,the HCl leaching process was studied.A significant leaching selectivity of Ca to REs,from 21.6 to 35.1,is achieved through mechanical activation.The Ca leaching rate reaches 80.7%when the RE loss is 2.3%in the activated sample.This study provides an novel approach for achieving selective extraction of specific components via mechanical activation pretreatment.
基金This research was a part of the project titled“Development of the wide-area underwater mobile communication systems”funded by the Ministry of Oceans and Fisheries,Korea.
文摘For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater surveillance,location tracking system,etc.Most of the IoUT applications rely on acoustic medium.The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate,attenuation,limited bandwidth,limited battery,limited memory,connectivity problem,etc.One of the significant applications of IoUT include monitoring underwater diver networks.In order to perform a reliable and energy-efficient communication system in the underwater diver networks,a smart underwater hybrid softwaredefined modem(UHSDM)for the mobile ad-hoc network was developed that is used for selecting the best channel/medium among acoustic,visible light communication(VLC),and infrared(IR)based on the criteria established within the system.However,due to the mobility of underwater divers,the developed UHSDMmeets the challenges such as connectivity errors,frequent link failure,transmission delay caused by re-routing,etc.During emergency,the divers are most at the risk of survival.To deal with diver mobility,connectivity,energy efficiency,and reducing the latency in ADN,a handover mechanism based on pre-built UHSDM is proposed in this paper.This paper focuses on(1)design of UHSDM for ADN(2)propose the channel selection mechanism in UHSDM for selecting the best medium for handover and(3)propose handover protocol inADN.The implementation result shows that the proposed mechanism can be used to find the new route for divers in advance and the latency can be reduced significantly.Additionally,this paper shows the real field experiment of air tests and underwater tests with various distances.This research will contribute much to the profit of researchers in underwater diver networks and underwater networks,for improving the quality of services(QoS)of underwater applications.
基金Sponsored by the Chinese National Foundation of Science Na 59875058.
文摘Firstly data standardization technology and combined classification method have been applied to carry out classification of kinematic behaviors and mechanisms in the mapping field between the kinematic behavior level and the mechanism level of conceptual design.The principle of computer coding and storing have been built to give a fast and broad selection of mechanisms that meets the requirements of basic motion characters.Then on the basis of mentioned above,the heuristic matching propagation principle (HMPP) of kinematic behaviors and its true table serves as a guide to perform mechanism types selection.Finally an application is given to indicate its practicability and effectiveness.
文摘In order to improve the reliability of the mechanical movement of the rotary electronic dobby, the kinematics analysis of the heald selection mechanism is carried out and the simulation is carried out with Matlab. Firstly, the operation mechanism of the heald selection mechanism is analyzed in detail. The conjugate cam is mapped. The cam profile curve is fitted with cubic spline interpolation. Secondly, based on the overall analysis method and the complex vector method, the kinematics analysis of the key components after the high pair low generation is performed, and the angular displacement and angular velocity of each component are calculated with the rotation of the active cam. Finally, the movement curve diagram is drawn with Matlab, which lays the foundation for the dynamic analysis and in-depth study of the selection mechanism in the future.
基金Project supported by the Chinese Academy of Sciences(Grant No.1G2009312311750101)the National Natural Science Foundation of China(Grant Nos.11375228,11204303,and U1332105)
文摘A systematic investigation of oxidation on a superconductive Fe Te_（0.5）Se_（0.5）thin film,which was grown on Nb-doped SrTiO_3（001） by pulsed laser deposition,has been carried out.The sample was exposed to ambient air for one month for oxidation.Macroscopically,the exposed specimen lost its superconductivity due to oxidation.The specimen was subjected to in situ synchrotron radiation photoelectron spectroscopy（PES） and x-ray absorption spectroscopy（XAS） measurements following cycles of annealing and argon ion etching treatments to unravel what happened in the electronic structure and composition after exposure to air.By the spectroscopic measurements,we found that the as-grown FeTe_（0.5）Se_（0.5）superconductive thin film experienced an element selective substitution reaction.The oxidation preferentially proceeds through pumping out the Te and forming Fe–O bonds by O substitution of Te.In addition,our results certify that in situ vacuum annealing and low-energy argon ion etching methods combined with spectroscopy are suitable for depth element and valence analysis of layered structure superconductor materials.
文摘In recent years,decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios.In these algorithms,the reference vectors of the Penalty-Based boundary intersection(PBI)are distributed parallelly while those based on the normal boundary intersection(NBI)are distributed radially in a conical shape in the objective space.To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications,this paper addresses the improvement of the Collaborative Decomposition(CoD)method,a multi-objective decomposition technique that integrates PBI and NBI,and combines it with the Elephant Clan Optimization Algorithm,introducing the Collaborative Decomposition Multi-objective Improved Elephant Clan Optimization Algorithm(CoDMOIECO).Specifically,a novel subpopulation construction method with adaptive changes following the number of iterations and a novel individual merit ranking based onNBI and angle are proposed.,enabling the creation of subpopulations closely linked to weight vectors and the identification of diverse individuals within them.Additionally,new update strategies for the clan leader,male elephants,and juvenile elephants are introduced to boost individual exploitation capabilities and further enhance the algorithm’s convergence.Finally,a new CoD-based environmental selection method is proposed,introducing adaptive dynamically adjusted angle coefficients and individual angles on corresponding weight vectors,significantly improving both the convergence and distribution of the algorithm.Experimental comparisons on the ZDT,DTLZ,and WFG function sets with four benchmark multi-objective algorithms—MOEA/D,CAMOEA,VaEA,and MOEA/D-UR—demonstrate that CoDMOIECO achieves superior performance in both convergence and distribution.
基金supported by the National Natural Science Foundation of China(12304160,12304161,62172155,U22A2027,62274183,and 62301595)the Research Foundation from National University of Defense Technology(ZK24-18,23-ZZCX-ZZGC-01-02,and 22-ZZCX-046-02)。
文摘The brain’s selective visual attention mechanism(SVAM)enables robust visual recognition in noisy environment through diverse neural action potential peaks acting as filters.Spiking neural networks(SNNs)mimic this paradigm but limited noise immunity and high write current density hinder brain-like efficiency.Hardware implementing SVAM necessitates spiking spintronic devices with noise-resistant and low operation current densities;such devices remain unreported.Here,we report an orbit-torque(OT)actuated ferromagnetic spiking synapse and neuron featuring a tunable peak action potential.These are more akin to the biological neurons with varying sensitivities to external sensory stimuli,thereby augmenting the perception aptitude of the system in complex surroundings.Capitalizing on the high-efficient OT,the ferromagnetic device demands a write current density of 5×10^(6) A/cm^(2),which is an order of magnitude lower than other spiking devices actuated by spin-orbit torque.Leveraging these neuromorphic devices,an all-spin SNN with low current density and tunable action potential peak has been fabricated,successfully mimicking the SVAM.In complex noise environment,the SNN achieves 92%on Cifar-10 and 95%on MNIST dataset,surpassing state-of-the-art spin-based SNNs by 5%.Our work provides a promising avenue for exploring the SVAM-inspired spiking neuromorphic devices,enhancing the bionic performance of the SNNs.
基金supported by the National Key R&D Program of China(No.2022YFB3805302)the National Natural Science Foundation of China(No.22379141)+2 种基金CAS Strategic Leading Science&Technology Program(A)(No.XDA0400201)Dalian Science and Technology Star Program(No.2022RQ014)Youth Innovation Promotion Association CAS(No.2022184).
文摘The membrane,one of the key components of flow batteries,ideally has high selectivity,conductivity,and stability.However,porous membranes prepared by conventional non-solvent-induced phase separation(NIPS)commonly suffer from low selectivity and poor mechanical stability.Here,we used rigid naphthalene-containing polybenzimidazole(NPBI)to prepare a porous membrane with unique egg-shaped pores by adjusting solvent/non-solvent exchange in NIPS.The dense pores with a size of 3.6Åarranged dispersedly between egg-shaped pores.The rigid NPBI and 3.6-Åsmall pores enabled the membrane high mechanical strength.The thickness was thus decreased to 1.4μm,which exhibited an ultrahigh tensile strength of 463.54 MPa.The dense pores were also smaller than hydrated vanadium ions,achieving a low permeability of 2.28×10^(-7)cm^(2)/h,indicating high selectivity.This is the first time to prepare such a highly selective and mechanically stable ultrathin porous membrane by NIPS.Importantly,the ion-transport pathways in the 1.4μm membrane were shortened,decreasing the area resistance to as low as 0.015Ωcm 2.Demonstrated in a vanadium flow battery,its coulombic efficiency was 98.57%and energy efficiency reached 81.72%at 200 mA/cm 2.This study proposes an effective strategy to prepare highperformance ultrathin porous membranes for flow batteries.
基金supported by special project of the National Natural Science Foundation of China[No.42027806]special Fund of the National Natural Science Foundation of China[No.42041006]+3 种基金the National Key Research and Development Program Project of China[No.2018YFC1504705]the Key Program of the National Natural Science Foundation of China[No.61731015]the major instrument,the project of Natural Science Foundation in Shaanxi Province[No.2018JM6029]the Key Research and Development Program of Shaanxi[No.2022GY-331].
文摘The WSN(wireless sensor network)node optimization problem faces the challenge of efficient deployment and adaptation under limited resources and a dynamically changing environment.The complex and changing deployment environment puts higher requirements on the search space,computational cost,and optimization efficiency of the algorithms.For this reason,a slime mould algorithm called SCA-SMA is proposed to solve the above problem.In SCA-SMA,a reverse Sobol sequence is used to initialize the population to increase the population diversity and improve the probability of approaching the optimal solution.To better balance local exploitation and global exploration,a dynamic selection of sine cosine update mechanism is proposed:using an optimal position selection mechanism in the global exploration phase to avoid local optima,and integrating the sine cosine algorithm in the local exploitation phase to improve the mucilage position update method,enrich the optimization search process and enhance the development capability of the algorithm.Finally,an adaptive mutation strategy can be proposed to increase the search range of the algorithm and motivate SCA-SMA to explore more promising regions.To evaluate the performance of the algorithm,SCA-SMA is experimentally validated in five different aspects.The results show that SCA-SMA is significantly competitive compared to advanced MAs.In particular,in facing the WSN node coverage problem,SCA-SMA has more obvious advantages in both average coverage and optimal coverage,which makes it possible to fully utilize the sensing range of each sensor node,while avoiding the waste of resources and the generation of monitoring blind zones.
基金The National Natural Science Foundation of China(No.61273266,61231002,61301219,61375028)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092130004)the Natural Science Foundation of Shandong Province(No.ZR2014FQ016)
文摘To solve the problem of mismatching features in an experimental database, which is a key technique in the field of cross-corpus speech emotion recognition, an auditory attention model based on Chirplet is proposed for feature extraction.First, in order to extract the spectra features, the auditory attention model is employed for variational emotion features detection. Then, the selective attention mechanism model is proposed to extract the salient gist features which showtheir relation to the expected performance in cross-corpus testing.Furthermore, the Chirplet time-frequency atoms are introduced to the model. By forming a complete atom database, the Chirplet can improve the spectrum feature extraction including the amount of information. Samples from multiple databases have the characteristics of multiple components. Hereby, the Chirplet expands the scale of the feature vector in the timefrequency domain. Experimental results show that, compared to the traditional feature model, the proposed feature extraction approach with the prototypical classifier has significant improvement in cross-corpus speech recognition. In addition, the proposed method has better robustness to the inconsistent sources of the training set and the testing set.
基金This research is supported by Research Foundation for Returned Scholars,Nanjing Tech University[No.39809110].The author JW received the grant in 2017.
文摘Wireless Sensor Network(WSN)based applications has been extraordinarily helpful in monitoring interested area.Only information of surrounding environment with meaningful geometric information is useful.How to design the localization algorithm that can effectively extract unknown node position has been a challenge in WSN.Among all localization technologies,the Distance Vector-Hop(DV-Hop)algorithm has been most popular because it simply utilizes the hop counts as connectivity measurements.This paper proposes an improved DV-Hop based algorithm,a centroid DV-hop localization with selected anchors and inverse distance weighting schemes(SIC-DV-Hop).We adopt an inverse distance weighting method for average distance amelioration to improve accuracy.Also in this paper,we propose an inclusive checking rule to select proper anchors to avoid the inconsistency existing in centroid localization schemes.Finally,an improved multilateration centroid method is presented for the localization.Simulations are conducted on two different network topologies and experiments results show that compared with existing DV-Hop based algorithms,our algorithm can significantly improve the performance meanwhile cost less network resource.
基金supported by National Natural Science Foundation of China under Grant Nos.52005447,72271222,71371170,71871203,L1924063Zhejiang Provincial Natural Science Foundation of China underGrant No.LQ21E050014Foundation of Zhejiang Education Committee under Grant No.Y201840056.
文摘Effective constrained optimization algorithms have been proposed for engineering problems recently.It is common to consider constraint violation and optimization algorithm as two separate parts.In this study,a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems.Based on the improved pbest selection method,an adaptive differential evolution approach is proposed,which helps the population jump out of the infeasible region.If all the individuals are infeasible,the top 5%of infeasible individuals are selected.In addition,a modified truncatedε-level method is proposed to avoid trapping in infeasible regions.The proposed adaptive differential evolution approach with an improvedεconstraint processmechanism(IεJADE)is examined on CEC 2006 and CEC 2010 constrained benchmark function series.Besides,a standard IEEE-30 bus test system is studied on the efficiency of the IεJADE.The numerical analysis verifies the IεJADE algorithm is effective in comparisonwith other effective algorithms.
基金“Scientific Research Projects of Selcuk University”for the institutional support
文摘The artificial bee colony (ABC) algorithm is a swarm-based metaheuristic optimization technique, developed by inspiring foraging and dance behaviors of honey bee colonies. ABC consists of four phases named as initialization, employed bee, onlooker bee and scout bee. The employed bees try to improve their solution in employed bees phase. If an employed bee cannot improve self-solution in a certain time, it becomes a scout bee. This alteration is done in the scout bee phase. The onlooker bee phase is placed where information sharing is done. Although a candidate solution improved by onlookers is chosen among the employed bee population according to fitness values of the employed bees, neighbor of candidate solution is randomly selected. In this paper, we propose a selection mechanism for neighborhood of the candidate solutions in the onlooker bee phase. The proposed selection mechanism was based on information shared by the employed bees. Average fitness value obtained by the employed bees is calculated and those better than the aver- age fitness value are written to memory board. Therefore, the onlooker bees select a neighbor from the memory board. In this paper, the proposed ABC-based method called as iABC were applied to both five numerical benchmark functions and an estimation of energy demand problem. Obtained results for the problems show that iABC is better than the basic ABC in terms of solution quality.
文摘Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. A variety of automated negotiation mechanisms have been proposed in the literature. The effectiveness of those mechanisms, however, may depend on the charaeteristics of the underlying negotiation problem （e.g. on the complexity of participant＇s utility functions, as well as the degree of conflict between participants）. While one mechanism may be a good choice for a negotiation problem, it may be a poor choice for another. In this paper, we pursue the problem of selecting the most effective negotiation mechanism given a particular problem by （1） defining a set of scenario metrics to capture the relevant features of negotiation problems, （2） evaluating the performance of a range of negotiation mechanisms on a diverse test suite of negotiation scenarios, （3） applying machine learning techniques to identify which mechanisms work best with which scenarios, and （4） demonstrating that using these classification rules for mechanism selection enables significantly better negotiation performance than any single mechanism alone.
基金supported by the National Natural Science Foundation of China under grant#62103040,#U1913602,#T2121003,#91948204,#U20B2071,and#U19B2033 and Open Fund/Postdoctoral Fund of the Laboratory of Cognition and Decision Intelligence for Complex Systems,Institute of Automation,Chinese Academy of Sciences under grant CASIA-KFKT-08.
文摘A maritime target saliency detection method inspired by the stimulation competition and selection mechanism of raptor vision is presented for the airborne vision system of unmanned aerial vehicle(UAV)in an unknown maritime environment.The stimulation competition and selection mechanism in the visual pathway of raptor vision based on the phenomenon of raptor capturing prey in complex scenes are studied.Then,the mathematical model of the stimulation competition and selection mechanism of raptor vision is established and employed for the salient object detection.Popular image datasets and practical scene datasets are applied to verify the effectiveness of the presented method.Results show that the detection performance of the proposed method is better than that of other comparison methods.The proposed algorithm provides an idea for maritime target salient detection and cross-domain joint mission for UAV or other unmanned equipment.
基金supported by the Special Zone Project of National Defense Innovation and the Science and Technology Program of Education Department of Jiangxi Province(No.GJJ171503).
文摘In order to solve the problems of road traffic congestion and the increasing parking time caused by the imbalance of parking lot supply and demand,this paper proposes an asymptotically optimal public parking lot location algorithm based on intuitive reasoning to optimize the parking lot location problem.Guided by the idea of intuitive reasoning,we use walking distance as indicator to measure the variability among location data and build a combinatorial optimization model aimed at guiding search decisions in the solution space of complex problems to find optimal solutions.First,Selective Attention Mechanism(SAM)is introduced to reduce the search space by adaptively focusing on the important information in the features.Then,Quantum Annealing(QA)algorithm with quantum tunneling effect is used to jump out of the local extremum in the search space with high probability and further approach the global optimal solution.Experiments on the parking lot location dataset in Luohu District,Shenzhen,show that the proposed method has improved the accuracy and running speed of the solution,and the asymptotic optimality of the algorithm and its effectiveness in solving the public parking lot location problem are verified.
