Multi-Label Feature Selection Based on Improved Ant Colony Optimization Algorithm with Dynamic Redundancy and Label Dependence

The world produces vast quantities of high-dimensional multi-semantic data.However,extracting valuable information from such a large amount of high-dimensional and multi-label data is undoubtedly arduous and challenging.Feature selection aims to mitigate the adverse impacts of high dimensionality in multi-label data by eliminating redundant and irrelevant features.The ant colony optimization algorithm has demonstrated encouraging outcomes in multi-label feature selection,because of its simplicity,efficiency,and similarity to reinforcement learning.Nevertheless,existing methods do not consider crucial correlation information,such as dynamic redundancy and label correlation.To tackle these concerns,the paper proposes a multi-label feature selection technique based on ant colony optimization algorithm(MFACO),focusing on dynamic redundancy and label correlation.Initially,the dynamic redundancy is assessed between the selected feature subset and potential features.Meanwhile,the ant colony optimization algorithm extracts label correlation from the label set,which is then combined into the heuristic factor as label weights.Experimental results demonstrate that our proposed strategies can effectively enhance the optimal search ability of ant colony,outperforming the other algorithms involved in the paper.

Microstructural evolution and dynamic recrystallization mechanisms of additively manufactured TiAl alloy with heterogeneous microstructure during hot compression

Microstructural evolution and dynamic recrystallization(DRX)mechanisms of a Ti-48Al-2Cr-2Nb(at.%)alloy prepared by selective electron beam melting(SEBM)during hot deformation at 1150℃and 0.1 s^(-1)were investigated by hot compression tests,optical microscope(OM),scanning electron microscope(SEM),electron back-scattered diffraction(EBSD)and transmission electron microscope(TEM).The results show that the initial microstructure of the as-SEBMed alloy exhibits layers of coarseγgrains and fineγ+α_(2)+(α_(2)/γ)lamellar mixture grains alternately along the building direction.During the early stage of hot deformation,deformation twins tend to form within the coarse grains,facilitating subsequent deformation,and a small number of DRX grains appear in the fine-grained regions.With the increase of strain,extensive DRX grains are formed through different DRX mechanisms in both coarse and fine-grained regions,involving discontinuous dynamic recrystallization mechanism(DDRX)in the fine-grained regions and a coexistence of DDRX and continuous dynamic recrystallization(CDRX)in the coarsegrained regions.

Joint User Association and Satellite Selection for Satellite-Terrestrial Integrated networks

In this paper, we investigate a cooperation mechanism for satellite-terrestrial integrated networks. The terrestrial relays act as the supplement of traditional small cells and cooperatively provide seamless coverage for users in the densely populated areas.To deal with the dynamic satellite backhaul links and backhaul capacity caused by the satellite mobility, severe co-channel interference in both satellite backhaul links and user links introduced by spectrum sharing,and the difference demands of users as well as heterogeneous characteristics of terrestrial backhaul and satellite backhaul, we propose a joint user association and satellite selection scheme to maximize the total sum rate. The optimization problem is formulated via jointly considering the influence of dynamic backhaul links, individual requirements and targeted interference management strategies, which is decomposed into two subproblems: user association and satellite selection. The user association is formulated as a nonconvex optimization problem, and solved through a low-complexity heuristic scheme to find the most suitable access point serving each user. Then, the satellite selection is resolved based on the cooperation among terrestrial relays to maximize the total backhaul capacity with the minimum date rate constraints. Finally,simulation results show the effectiveness of the proposed scheme in terms of total sum rate and power efficiency of TRs' backhaul.

Tensile stress enhanced dynamic oxygen vacancies on interlayer stretched Bi_(2)O_(2)CO_(3) as pivotal knobs to promote sustainable selective CO_(2) photoreduction

Surface oxygen vacancies(OVs) with abundant localized electrons on bismuth-oxygen based photocatalysts are proved to have the ability to capture and activate CO_(2).However,the surface OVs are easily filled with oxygen-containing species and destroyed,losing their effects as active sites and hindering the subsequent CO_(2)photoreduction.For realistic and sustainable CO_(2)photoreduction,constructing sustainable and stable surface OVs as active sites on photocatalysts is essential.This work shows the synthesis of interlayer stretched Bi_(2)O_(2)CO_(3) ultrathin nanosheets with tensile stress,which are beneficial to continuously generating light-induced dynamic OVs.With sufficient active sites,excellent,stable,and selective photoreduction of CO_(2)to CO under simulated solar light is achieved.The light-induced OVs can reduce the energy barrier of rate-determining step,resulting in the 100% product selectivity.The results presented herein demonstrate the effect of dynamic OVs induced by interlayer tensile strain on catalysts for the enhanced selective CO_(2)photoreduction process.

A dynamic programming algorithm for network selection in 3G/WLAN

An essential characteristic of the 4th Generation(4G) wireless networks is integrating various heterogeneous wireless access networks.This paper considers the network selection for both admission and handoff strategy problems in heterogeneous network of 3G/WLAN.A novel dynamic programming algorithm is proposed by taking heterogeneous network characteristics,user mobility and different service types into account.The specificity of our approach is that it puts the situations in a new model and makes decisions in stages of different states.Simulation results validate that the proposed scheme can obtain better new call blocking and handoff dropping probability performance than traditional schemes while ensuring quality-of-services(QoS) for both real-time and data connections.

Dynamic Relay Selection Method for Distributed MIMO Relay System

The research on distributed MIMO relay system has been attracting much attention. In this paper, a decode-and-forward scheme distributed MIMO relay system is examined. For upper bound of channel capacity, the distance between transceivers is optimized when the propagation loss is brought close to actuality. Additionally, the number of relay is optimized whether total antenna element is fixed or not. When the number of relay is assumed to be infinite, the dynamic relay selection method based on the transmission rate is proposed. We represent that with the proposed method, the transmit power and the number of relays are saving.

Dynamic selection scheme for cooperative relay under high mobility environment

The mobility of relay has great influence on the performance of a cooperative relay system.This paper proposes a dynamic selection scheme under the amplify-and-forward communication mode in high mobility environment,based on the estimation of channels and the power allocation for each relay node by comparing it with the pre-set threshold.This scheme is used to choose the cooperative relay dynamically for a multiple relay scenario.Simulation results show that this proposed relay selection scheme decreases the outage probability effectively,maintains system capacity well,and improves the performance of the relay system.

A Multi-Hop Dynamic Path-Selection (MHDP) Algorithm for the Augmented Lifetime of Wireless Sensor Networks

In Wireless Sensor Networks (WSN), the lifetime of sensors is the crucial issue. Numerous schemes are proposed to augment the life time of sensors based on the wide range of parameters. In majority of the cases, the center of attraction will be the nodes’ lifetime enhancement and routing. In the scenario of cluster based WSN, multi-hop mode of communication reduces the communication cast by increasing average delay and also increases the routing overhead. In this proposed scheme, two ideas are introduced to overcome the delay and routing overhead. To achieve the higher degree in the lifetime of the nodes, the residual energy (remaining energy) of the nodes for multi-hop node choice is taken into consideration first. Then the modification in the routing protocol is evolved (Multi-Hop Dynamic Path-Selection Algorithm—MHDP). A dynamic path updating is initiated in frequent interval based on nodes residual energy to avoid the data loss due to path extrication and also to avoid the early dying of nodes due to elevation of data forwarding. The proposed method improves network’s lifetime significantly. The diminution in the average delay and increment in the lifetime of network are also accomplished. The MHDP offers 50% delay lesser than clustering. The average residual energy is 20% higher than clustering and 10% higher than multi-hop clustering. The proposed method improves network lifetime by 40% than clustering and 30% than multi-hop clustering which is considerably much better than the preceding methods.

Learning-Based Dynamic Connectivity Maintenance for UAV-Assisted D2D Multicast Communication

Unmanned aerial vehicles(UAVs) enable flexible networking functions in emergency scenarios.However,due to the movement characteristic of ground users(GUs),it is challenging to capture the interactions among GUs.Thus,we propose a learningbased dynamic connectivity maintenance architecture to reduce the delay for the UAV-assisted device-todevice(D2D) multicast communication.In this paper,each UAV transmits information to a selected GU,and then other GUs receive the information in a multi-hop manner.To minimize the total delay while ensuring that all GUs receive the information,we decouple it into three subproblems according to the time division on the topology:For the cluster-head selection,we adopt the Whale Optimization Algorithm(WOA) to imitate the hunting behavior of whales by abstracting the UAVs and cluster-heads into whales and preys,respectively;For the D2D multi-hop link establishment,we make the best of social relationships between GUs,and propose a node mapping algorithm based on the balanced spanning tree(BST) with reconfiguration to minimize the number of hops;For the dynamic connectivity maintenance,Restricted Q-learning(RQL) is utilized to learn the optimal multicast timeslot.Finally,the simulation results show that our proposed algorithms perfor better than other benchmark algorithms in the dynamic scenario.

Dynamic model for predicting nitrogen oxide concentration at outlet of selective catalytic reduction denitrification system based on kernel extreme learning machine

To solve the increasing model complexity due to several input variables and large correlations under variable load conditions,a dynamic modeling method combining a kernel extreme learning machine(KELM)and principal component analysis(PCA)was proposed and applied to the prediction of nitrogen oxide(NO_(x))concentration at the outlet of a selective catalytic reduction(SCR)denitrification system.First,PCA is applied to the feature information extraction of input data,and the current and previous sequence values of the extracted information are used as the inputs of the KELM model to reflect the dynamic characteristics of the NO_(x)concentration at the SCR outlet.Then,the model takes the historical data of the NO_(x)concentration at the SCR outlet as the model input to improve its accuracy.Finally,an optimization algorithm is used to determine the optimal parameters of the model.Compared with the Gaussian process regression,long short-term memory,and convolutional neural network models,the prediction errors are reduced by approximately 78.4%,67.6%,and 59.3%,respectively.The results indicate that the proposed dynamic model structure is reliable and can accurately predict NO_(x)concentrations at the outlet of the SCR system.

A novel multi-channel porous structure facilitating mass transport towards highly efficient alkaline water electrolysis

An advantageous porous architecture of electrodes is pivotal in significantly enhancing alkaline water electrolysis(AWE)efficiency by optimizing the mass transport mechanisms.This effect becomes even more pronounced when aiming to achieve elevated current densities.Herein,we employed a rapid and scalable laser texturing process to craft novel multi-channel porous electrodes.Particularly,the obtained electrodes exhibit the lowest Tafel slope of 79 mV dec^(-1)(HER)and 49 mV dec^(-1)(OER).As anticipated,the alkaline electrolyzer(AEL)cell incorporating multi-channel porous electrodes(NP-LT30)exhibited a remarkable improvement in cell efficiency,with voltage drops(from 2.28 to 1.97 V)exceeding 300 mV under 1 A cm^(-1),compared to conventional perforated Ni plate electrodes.This enhancement mainly stemmed from the employed multi-channel porous structure,facilitating mass transport and bubble dynamics through an innovative convection mode,surpassing the traditional convection mode.Furthermore,the NP-LT30-based AEL cell demonstrated exceptional durability for 300 h under 1.0 A cm^(-2).This study underscores the capability of the novel multi-channel porous electrodes to expedite mass transport in practical AWE applications.

Molecular dynamics simulation of ion selectivity traits of nickel hexacyanoferrate thin films

The ion selectivity of nickel hexacyanoferrate thin film to alkali cations in ESIX (electrochemically switched ion exchange) processes was investigated using molecular dynamics(MD) techniques; water and cation (Na+ and Cs+) intercalation, configuration, and dynamics in reduced nickel hexacyanoferrate structures with different cation combinations were studied and compared with the experimental results. In the simulations, water was represented by an extended simple point-charge(SPC/E) model, and all other atomic interactions were represented by a universal force field(UFF). The potential energies of various cations combination (Cs+ and Na+) in reduced i-NiHCF and 1 mol/L Cs/NaCl mixed solution were obtained. In most cases, the total potential energy of the solid is reduced when water is intercalated into the various reduced NiHCF structures. Combining the solid and the solution simulation results, it is shown that the solid composition of 3Cs+/1Na+ is the stablest structure form (NaCs3Ni4[Fe(CN)6]3) over a range of solution compositions.

Spectral observation of symmetry-protected selection rules for dynamical high-dimensional parity in alignment magnetic resonance

Multidimensional Floquet-driven alignment systems with dynamical symmetry present various exotic phenomena and applications.However,there are challenges in directly characterizing large-spin dynamical symmetry from spectra.Here,we first observe the symmetry-protected selection rules of dynamical high-dimensional parity in a large-spin(F=4)system.We theoretically construct a Floquet-driven alignment system that can be used to reveal high-dimensional spatiotemporal symmetry.In the experiment,the system is implemented in Cs atomic gas subjected to two-dimensional Floquet-modulated magnetic resonance driving.By developing Floquet detection protocols of alignment double-sided spectra,we directly verify symmetry-protected selection rules of dynamical high-dimensional parity for large-spin systems.This work advances the exploration of dynamical symmetry to large spins,and unravels a universal Floquet scheme for the investigation of symmetry-protected selection rules.

Cooling rate dependence of polymorph selection during rapid solidification of liquid metal zinc

The polymorph selection during rapid solidification of zinc melt was investigated by molecular dynamics simulation. Several methods including g（r）, energy, CNS, basic cluster and visualization were used to analyze the results. The results reveal that the cooling rate has no observable effect on the microstructure as TTc（Tc is the onset temperature of crystallization）; and at the first stage of crystallization, although microstructures are different, the morphologies of nucleus are similar, which are composed of HCP and FCC layers; the polymorph selection of cooling rate finally takes place at the second stage of crystallization： at a high cooling rate, the rapid increase of FCC atoms leads to a FCC crystal mixed with less HCP structures; while at a low cooling rate, HCP atoms grow at the expense of FCC atoms, resulting in an almost perfect HCP phase. The results reveal that the cooling rate is one of the important factors for polymorph selection.

Influence of site selection on natural ventilation in Chinese traditional folk house

The relationship between the site selection of a hilly terrain and the natural ventilation of the Dangdamen building complex,which is a traditional folk house,is revealed by a computational fluid dynamics（CFD）simulation.The wind press and speed distributions around the building in four cases with different weather conditions and topographies are simulated.The simulation results show that a hill can reduce the absolute values of the wind pressure at the windward and leeward sides of the building.The encouraging effect of the patio on the natural ventilation in a terrain with a hill is greater than that without a hill.The same situation occurs when comparing the patio effects between summer and winter.The wind speed around the building can be reduced by the hill as it is an obstacle and the degrees of the influence of the hill in summer and in winter are quite different because of different wind directions.The analysis results show that this kind of site selection,with the hill to the north,is a suitable way to settle the conflict of the natural ventilation requirements in summer and in winter under subtropical climate conditions,especially in houses with patios.

Molecular Dynamic Simulation on the Absorbing Process of Isolating and Coating of α-olefin Drag Reducing Polymer

The absorbing process in isolating and coating process of α-olefin drag reducing polymer was studied by molecular dynamic simulation method, on basis of coating theory of α-olefin drag reducing polymer particles with polyurethane as coating material. The distributions of sodium laurate, sodium dodeeyl sulfate, and sodium dodeeyl benzene sulfonate on the surface of α-olefin drag reducing polymer particles were almost the same, but the bending degrees of them were obviously different. The bending degree of SLA molecules was greater than those of the other two surfactant molecules. Simulation results of absorbing and accumulating structure showed that, though hydrophobie properties of surfactant molecules were almost the same, water density around long chain sulfonate sodium was bigger than that around alkyl sulfate sodium. This property goes against useful absorbing and accumulating on the surface of α-olefin drag reducing polymer particles; simulation results of interactions of different surfactant and multiple hydroxyl compounds on surface of particles showed that, interactions of different surfaetant and one kind of multiple hydroxyl compound were similar to those of one kind of surfaetant and different multiple hydroxyl compounds. These two contrast types of interactions also exhibited the differences of absorbing distribution and closing degrees to surface of particles. The sequence of closing degrees was derived from simulation; control step of addition polymerization interaction in coating process was absorbing mass transfer process, so the more closed to surface of particle the multiple hydroxyl compounds were, the easier interactions With isoeyanate were. Simulation results represented the compatibility relationship between surfactant and multiple hydroxyl compounds. The isolating and coating processes of α-olefin drag reducing polymer were further understood on molecule and atom level through above simulation research, and based on the simulation, a referenced theoretical basis was provided for practical optimal selection and experimental preparation of α-olefin drag reducing polymer particles suspension isolation agent.

Depression recognition using functional connectivity based on dynamic causal model

Dynamic casual modeling of functional magnetic resonance imaging（fMRI） signals is employed to explore critical emotional neurocircuitry under sad stimuli. The intrinsic model of emotional loops is built on the basis of Papez＇s circuit and related prior knowledge, and then three modulatory connection models are established. In these models, stimuli are placed at different points, which represents they affect the neural activities between brain regions, and these activities are modulated in different ways. Then, the optimal model is selected by Bayesian model comparison. From group analysis, patients＇ intrinsic and modulatory connections from the anterior cingulate cortex （ACC） to the right inferior frontal gyrus （rlFG） are significantly higher than those of the control group. Then the functional connection parameters of the model are selected as classifier features. The classification accuracy rate from the support vector machine（SVM） classifier is 80.73%, which, to some extent, validates the effectiveness of the regional connectivity parameters for depression recognition and provides a new approach for the clinical diagnosis of depression.

A review of extractive distillation from an azeotropic phenomenon for dynamic control

Extractive distillation is an effective method for separating azeotropic or close boiling point mixtures by adding a third component.Various technologies for performing the extractive distillation process have been explored to protect the environment and save resources.This paper focuses on the improvement of these advanced technologies in recent years.Extractive distillation is retrieved and analyzed from the view of phase equilibrium,selection of solvent in extractive distillation,process design,energy conservation,and dynamic control.The quantitative structure–property relationship used in extractive distillation is discussed,and the future development of extractive distillation is proposed to determine how the solvent affects the relative volatility of the separated mixture.In the steady state design,the relationship between the curvature of the residue curve and parameters of the optimal steady state is also highlighted as another field worthy of further study to simplify the distillation process.

Exit selection strategy in pedestrian evacuation simulation with multi-exits

A mixed strategy of the exit selection in a pedestrian evacuation simulation with multi-exits is constructed by fusing the distance-based and time-based strategies through a cognitive coefficient, in order to reduce the evacuation imbalance caused by the asymmetry of exits or pedestrian layout, to find a critical density to distinguish whether the strategy of exit selection takes effect or not, and to analyze the exit selection results with different cognitive coefficients. The strategy of exit selection is embedded in the computation of the shortest estimated distance in a dynamic parameter model, in which the concept of a jam area layer and the procedure of step-by-step expending are introduced. Simulation results indicate the characteristics of evacuation time gradually varying against cognitive coefficient and the effectiveness of reducing evacuation imbalance caused by the asymmetry of pedestrian or exit layout. It is found that there is a critical density to distinguish whether a pedestrian jam occurs in the evacuation and whether an exit selection strategy is in effect. It is also shown that the strategy of exit selection has no effect on the evacuation process in the no-effect phase with a low density, and that evacuation time and exit selection are dependent on the cognitive coefficient and pedestrian initial density in the in-effect phase with a high density.

Dynamic programming methodology for multi-criteria group decision-making under ordinal preferences

A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making （MCGDM） and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.