Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Lower Bounds of Decay Rates for Solution to the Single-Layer Quasi-Geostrophic Model

In this paper, we study the long-time behavior of solutions of the single-layer quasi-geostrophic model arising from geophysical fluid dynamics. We obtain the lower bound of the decay estimate of the solution. Utilizing the Fourier splitting method, under suitable assumptions on the initial data, for any multi-index α, we show that the solution Ψ satisfies .

Recommendation System Based on Perceptron and Graph Convolution Network

The relationship between users and items,which cannot be recovered by traditional techniques,can be extracted by the recommendation algorithm based on the graph convolution network.The current simple linear combination of these algorithms may not be sufficient to extract the complex structure of user interaction data.This paper presents a new approach to address such issues,utilizing the graph convolution network to extract association relations.The proposed approach mainly includes three modules:Embedding layer,forward propagation layer,and score prediction layer.The embedding layer models users and items according to their interaction information and generates initial feature vectors as input for the forward propagation layer.The forward propagation layer designs two parallel graph convolution networks with self-connections,which extract higher-order association relevance from users and items separately by multi-layer graph convolution.Furthermore,the forward propagation layer integrates the attention factor to assign different weights among the hop neighbors of the graph convolution network fusion,capturing more comprehensive association relevance between users and items as input for the score prediction layer.The score prediction layer introduces MLP(multi-layer perceptron)to conduct non-linear feature interaction between users and items,respectively.Finally,the prediction score of users to items is obtained.The recall rate and normalized discounted cumulative gain were used as evaluation indexes.The proposed approach effectively integrates higher-order information in user entries,and experimental analysis demonstrates its superiority over the existing algorithms.

Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process.

Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems

The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for patients.Consequently,Machine Learning methods are widely utilized in Smart Healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient activities.These methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful consideration.Hence,this paper proposes a crossover-based Multilayer Perceptron(CMLP)model.The collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of patients.Once an attack is detected,healthcare professionals are promptly alerted to prevent data leakage.The paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are collected.Experimental results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient activities.Comparing the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and F1-score.Specifically,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.

基于Perceptron建立某车型焊钉及白车身在线检测体系

以北京奔驰汽车有限公司206车型为基础,基于Perceptron就螺柱焊钉位置尺寸、车身尺寸和覆盖件尺寸在线自动检测以及相应的精度控制进行了研究,规划并建立焊钉位置尺寸在线测量点76个,普通测量特征1373个测量点;规划并实施焊钉在线测量方案以及后端、Z1和Z2.3在线测量方案;完成在线检测工位测量工装优化改进,达成了基于Perceptron的V206焊钉及白车身在线检测体系建设,并实现了工时和成本的节约。

Superconducting Single-Layer T-Graphene and Novel Synthesis Routes

Single-layer superconductors are ideal materials for fabricating superconducting nano devices.However,up to date,very few single-layer elemental superconductors have been predicted and especially no one has been successfully synthesized yet.Here,using crystal structure search techniques and ab initio calculations,we predict that a single-layer planar carbon sheet with 4-and 8-membered rings called T-graphene is a new intrinsic elemental superconductor with superconducting critical temperature(Tc)up to around 20.8 K.More importantly,we propose a synthesis route to obtain such a single-layer T-graphene,that is,a T-graphene potassium intercalation compound(C4 K with P4/mmm symmetry)is firstly synthesized at high pressure(>11.5 GPa)and then quenched to ambient condition;and finally,the single-layer T-graphene can be either exfoliated using the electrochemical method from the bulk C4 K,or peeled off from bulk T-graphite C4,where C4 can be obtained from C4 K by evaporating the K atoms.Interestingly,we find that the calculated Tc of C4 K is about 30.4 K at 0 GPa,which sets a new record for layered carbon-based superconductors.The present findings add a new class of carbon-based superconductors.In particular,once the single-layer T-graphene is synthesized,it can pave the way for fabricating superconducting devices together with other 2 D materials using the layer-by-layer growth techniques.

Dynamic behavior of single-layer latticed cylindrical shells subjected to seismic loading

The single-layer latticed cylindrical shell is one of the most widely adopted space-fl'amed structures.In this paper,free vibration properties and dynamic response to horizontal and vertical seismic waves of single-layer latticed cylindrical shells are analyzed by the finite element method using ANSYS software.In the numerical study,where hundreds of cases were analyzed,the parameters considered included rise-span ratio,length-span ratio,surface load and member section size.Moreover,to better define the actual behavior of single-layer latticed shells,the study is focused on the dynamic stress response to both axial forces and bending moments.Based on the numerical results,the effects of the parameters considered on the stresses are discussed and a modified seismic force coefficient method is suggested.In addition,some advice based on these research results is presented to help in the future design of such structures.

Ultra-thin circularly polarized lens antenna based on single-layered transparent metasurface

Circularly polarized （CP） lens antenna has been applied to numerous wireless communication systems based on its unique advantages such as high antenna gain, low manufacturing cost, especially stable data transmission between the transmitter and the receiver. Unfortunately, current available CP lens antennas mostly suffer from high profile, low aperture efficiency as well as complex design. In this paper, we propose an ultra-thin CP lens antenna based on the designed single- layered Pancharatnam-Berry （PB） transparent metasurface with focusing property. The PB metasurface exhibits a high transmissivity, which ensures a high efficiency of the focusing property. Launched the metasurface with a CP patch antenna at its focal point, a low-profile lens antenna is simulated and measured. The experimental results show that our lens antenna exhibits a series of advantages including high radiation gain of 20.7 dB, aperture efficiency better than 41.3%, and also narrow half power beam width （HPBW） of 13°at about 14GHz. Our finding opens a door to realize ultra-thin transparent metasurface with other functionalities or at other working frequencies.

Single-layer graphene as a highly selective barrier for vanadium crossover with high proton selectivity

We report near-zero crossover for vanadium cross-permeation through single-layer graphene immobilized at the interface of two Nafion?polymer electrolyte membranes.Vanadium ion diffusion and migration,including proton mobility through membrane composites,were studied with and without graphene under diffusion and migration conditions.Single-layer graphene was found to effectively inhibit vanadium ion diffusion and migration under specific conditions.The single-layer graphene composites also enabled remarkable ion transmission selectivity improvements over pure Nafion membranes,with proton transport being four orders of magnitude faster than vanadium ion transport.Resistivity values of 0.02±0.005Ωcm^(2) for proton and 223±4Ωcm^(2) for vanadium ion through single atomic layer graphene are reported.This high selectivity may have significant impact on flow battery applications or for other electrochemical devices where proton conductivity is required,and transport of other species is detrimental.Our results emphasize that crossover may be essentially completely eliminated in some cases,enabling for greatly improved operational viability.

Gap opening and tuning in single-layer graphene with combined electric and magnetic field modulation

The energy band structure of single-layer graphene under one-dimensional electric and magnetic field modulation is theoretically investigated. The criterion for bandgap opening at the Dirac point is analytically derived with a two-fold degeneracy second-order perturbation method. It is shown that a direct or an indirect bandgap semiconductor could be realized in a single-layer graphene under some specific configurations of the electric and magnetic field arrangement. Due to the bandgap generated in the single-layer graphene, the Klein tunneling observed in pristine graphene is completely suppressed.

Nanoscale mass sensing based on vibration of single-layered graphene sheet in thermal environments

Based on vibration analysis, single-layered graphene sheet （SLGS） with multiple attached nanoparticles is developed as nanoscale mass sensor in thermal environments. Graphene sensors are assumed to be in simplysupported configuration. Based on the nonlocal plate the- ory which incorporates size effects into the classical theory, closed-form expressions lot the frequencies and relative fre- quency shills of SLGS-based mass sensor are derived using the Galerkin method. The suggested model is justified by a good agreement between the results given by the present model and available data in literature. The effects of tem- perature difference, nonlocal parameter, the location of the nanoparticle and the number of nanoparticles on the relative frequency shift of the mass sensor are also elucidated. The obtained results show that the sensitivity of the SLGS- based mass sensor increases with increasing temperature difference.

Theoretical Proposal for a Planar Single-Layer Carbon That Shows a Potential in Superconductivity

Single-layer superconductors[1]have been the subject of considerable interests as they are ideal systems for the fundamental understanding of two-dimensional(2D)physics and for device applications.A few singlelayer superconductors are experimentally achieved(e.g.,FeSe,MoS2,and NbSe2[2-4]in the field where either charge doping or tensile strain is often required to promote the superconductivity.

Pseudohalide induced tunable electronic and excitonic properties in two-dimensional single-layer perovskite for photovoltaics and photoelectronic applications

Two-dimensional(2D) layered organic-inorganic hybrid perovskites have attracted much more attention for some applications than their three-dimensional(3D) perovskite counterparts due to their promising thermal and moisture stabilities.In particular, the 2D perovskite devices have shown better promise for optoelectronic applications.However, tunability of optoelectronic properties is often demanded to improve the device performance.Herein, we adopt a newly method to tune the electronic properties of 2D perovskite by introducing pseudohalide into the structure.In this work, we designed a pseudohalidesubstituted 2D perovskite by substituting the out-of-plane halide with pseudohalide and studied the electronic and excitonic properties of 2D-BA2MX4 and 2D-BA2MX2Ps2(M=Ge^(2+), Sn^(2+), and Pb^(2+);X=I;Ps=NCO, NCS, OCN, SCN, Se CN).We revealed the dependence of electronic properties including band gaps, composition of band edges, bonding characteristics, work functions, effective masses, and exciton binding energies on different pseudohalides substituted in 2D perovskite.Our results indicate that the substitution of pseudohalide in 2D perovskites is energetically favorable and can significantly affect the bonding characteristics as well as the CBM and VBM that often play major role in determining their performance in optoelectronic devices.It is expected that the pseudohalide substitution will be helpful in developing more advanced optoelectronic device based on 2D perovskite by optimizing band alignment and promoting charge extraction.

Electronic Structures and Optical Properties of Ga Doped Single-Layer Indium Nitride

Electronic structures and optical properties of single-layer In1-xGaxN are studied by employ-ing Heyd-Scuseria-Ernzerh(HSE)method based on the first-principles.The band structure and density of states(DOS)of single-layer In1-xGaxN are calculated,and the band gap ranges from 1.8 eV to 3.8 eV as the ratio x changes,illustrating the potential for the tun-ability of band gap values via Ga doped.We also have investigated optical properties of single-layer In1-xGaxN such as dielectric function,refractive index and absorption coeficient,the main peak of dielectric function spectrum and the absorption edge are found to have a remarkable blue-shift as the concentration of Ga increases.Furthermore,the optical properties of single-layer In1-xGaxN are analyzed based on the band structures and DOS analysis.Such unique optical properties have profound application in nanoelectronics and optical devices.

Deposition mechanism of nano-structured single-layered C_(36) film on a diamond (100) crystal plane

The Brenner-LJ potential is adopted to describe the interaction between C36 clusters and diamond surface, and the deposition mechanism of multi-C36 clusters on the diamond surface is also studied by using the method of molecular dynamics simulation. The simulation results show that the competition effects of two interactions, i.e. the interaction between cluster and cluster and the interaction between cluster and crystal plane, are studied, and then the influence of these competition effects on C36 cluster deposition is analysed. The finding is that when an incident energy is appropriately chosen, C36 clusters can be chemically adsorbed and deposited steadily on the diamond surface in the form of single-layer, and in the deposition process the multi-C36 clusters present a phenomenon of energy transmission. The experimental result shows that at a temperature of 300K, in order to deposit C36 clusters into a steady nanostructured single-layered film, the optimal incident energy is between 10 and 18 eV, if the incident energy is larger than 18 eV, the C36 clusters will be deposited into an island nano-structured film.

On hydraulic falls of single-layer flow

Hydraulic falls of single-layer now are determined theoretically in terms of a time-dependent averaged fKdV equation(AfKdV equation)in phase coordinate. From the theory of the present paper it was known that difference of the asymptotic mean levels upstream and downsream at the subcritical cutoff points is just equal to a subcritical value of the AfKdV equation An experiment is carried out to examine the theoretical results. From comparison between theoreticaland experimental results, it was shown that they are in good agreement.At the same time, it should be pointed out that the theory of the present paper is agreement with the experimental and numerical results of Forbes and can be employed to find the generating properties of the precursor solitons at near-resonance.

Magnetic phase diagram of single-layer CrBr_(3)

We theoretically provide a magnetic phase diagram for the single-layer(SL)CrBr_(3),which could be effectively tuned by both strain engineering and charge doping in SL-CrBr_(3).Through systematical first-principles calculations and Heisenberg model Hamiltonian simulations,three different magnetic phases in SL-CrBr_(3),which are off-plane ferromagnetic,in-plane ferromagnetic and in-plane Neél-antiferromagnetic phases,are found in the strain and charge doping regimes we studied.Furthermore,our results show that higher order Heisenberg exchange parameters and anisotropy exchange parameters should be taken into account for accurately illustrating the magnetic phase transition in SL-CrBr_(3).As a result,we find from the SpinW simulation that the Curie temperature is about T_(c)=38.4 K,which is well consistent with the experimental result 34 K[Nano Lett.193138(2019)].The findings here may be confirmed in future experiments,and may be useful for the potential applications of SL-CrBr_(3)in spintronics field.

Lowering the Operational Voltage of Single-Layer Polymer Electroluminescent Devices by Using CuO_x Modifying Indium-Tin Oxide Electrode

In this study it is demonstrated that oxygen-plasma-generated CuOx can enhance the holes injection from ITO anode into polymer layer in single-layer polymer EL devices. The possible reason for this enhancement is because the ITO anode modified with CuOx possesses much higher work function than pure ITO anode, which reduces the barrier for hole-injection and further lowers the operational voltage of the polymer EL devices. The work function shift is probable due to the oxygen-plasma-generated CuOx can store more releasable oxygen, and the releasable oxygen in turn changes the oxygen concentration just near ITO surface, which will shift the work function of ITO anode.

Automatic Sentimental Analysis by Firefly with Levy and Multilayer Perceptron

The field of sentiment analysis(SA)has grown in tandem with the aid of social networking platforms to exchange opinions and ideas.Many people share their views and ideas around the world through social media like Facebook and Twitter.The goal of opinion mining,commonly referred to as sentiment analysis,is to categorise and forecast a target’s opinion.Depending on if they provide a positive or negative perspective on a given topic,text documents or sentences can be classified.When compared to sentiment analysis,text categorization may appear to be a simple process,but number of challenges have prompted numerous studies in this area.A feature selection-based classification algorithm in conjunction with the firefly with levy and multilayer perceptron(MLP)techniques has been proposed as a way to automate sentiment analysis(SA).In this study,online product reviews can be enhanced by integrating classification and feature election.The firefly(FF)algorithm was used to extract features from online product reviews,and a multi-layer perceptron was used to classify sentiment(MLP).The experiment employs two datasets,and the results are assessed using a variety of criteria.On account of these tests,it is possible to conclude that the FFL-MLP algorithm has the better classification performance for Canon(98%accuracy)and iPod(99%accuracy).