BCCLR:A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.

Nonuniform Dependence on the Initial Data for Solutions of Conservation Laws

In this paper,we study systems of conservation laws in one space dimension.We prove that for classical solutions in Sobolev spaces H^(s),with s>3/2,the data-to-solution map is not uniformly continuous.Our results apply to all nonlinear scalar conservation laws and to nonlinear hyperbolic systems of two equations.

Understand anisotropy dependence of damage evolution and material removal during nanoscratch of MgF_(2) single crystals

To understand the anisotropy dependence of the damage evolution and material removal during the machining process of MgF_(2) single crystals,nanoscratch tests of MgF_(2) single crystals with different crystal planes and directions were systematically performed,and surface morphologies of the scratched grooves under different conditions were analyzed.The experimental results indicated that anisotropy considerably affected the damage evolution in the machining process of MgF_(2) single crystals.A stress field model induced by the scratch was developed by considering the anisotropy,which indicated that during the loading process,median cracks induced by the tensile stress initiated and propagated at the front of the indenter.Lateral cracks induced by tensile stress initiated and propagated on the subsurface during the unloading process.In addition,surface radial cracks induced by the tensile stress were easily generated during the unloading process.The stress change led to the deflection of the propagation direction of lateral cracks.Therefore,the lateral cracks propagated to the workpiece surface,resulting in brittle removal in the form of chunk chips.The plastic deformation parameter indicated that the more the slip systems were activated,the more easily the plastic deformation occurred.The cleavage fracture parameter indicated that the cracks propagated along the activated cleavage planes,and the brittle chunk removal was owing to the subsurface cleavage cracks propagating to the crystal surface.Under the same processing parameters,the scratch of the(001)crystal plane along the[100]crystal-orientation was found to be the most conducive to achieving plastic machining of MgF_(2) single crystals.The theoretical results agreed well with the experimental results,which will not only enhance the understanding of the anisotropy dependence of the damage evolution and removal process during the machining of MgF_(2) crystals,but also provide a theoretical foundation for achieving the high-efficiency and low-damage processing of anisotropic single crystals.

Trees species’ dispersal mode and habitat heterogeneity shape negative density dependence in a temperate forest

Conspecific negative density dependence(CNDD)is a potentially important mechanism in maintaining species diversity.While previous evidence showed habitat heterogeneity and species’dispersal modes affect the strength of CNDD at early life stages of trees(e.g.,seedlings),it remains unclear how they affect the strength of CNDD at later life stages.We examined the degree of spatial aggregation between saplings and trees for species dispersed by wind and gravity in four topographic habitats within a 25-ha temperate forest dynamic plot in the Qinling Mountains of central China.We used the replicated spatial point pattern(RSPP)analysis and bivariate paircorrelation function(PCF)to detect the spatial distribution of saplings around trees at two scales,15 and 50 m,respectively.Although the signal was not apparent across the whole study region(or 25-ha),it is distinct on isolated areas with specific characteristics,suggesting that these characteristics could be important factors in CNDD.Further,we found that the gravity-dispersed tree species experienced CNDD across habitats,while for wind-dispersed species CNDD was found in gully,terrace and low-ridge habitats.Our study suggests that neglecting the habitat heterogeneity and dispersal mode can distort the signal of CNDD and community assembly in temperate forests.

Optimization of extended warranty cost for multi-component systems with economic dependence based on group maintenance

During extended warranty(EW)period,maintenance events play a key role in controlling the product systems within normal operations.However,the modelling of failure process and maintenance optimization is complicated owing to the complex features of the product system,namely,components of the multi-component system are interdependent with each other in some form.For the purpose of optimizing the EW pricing decision of the multi-component system scientifically and rationally,taking the series multi-component system with economic dependence sold with EW policy as a research object,this paper optimizes the imperfect preventive maintenance(PM)strategy from the standpoint of EW cost.Taking into consideration adjusting the PM moments of the components in the system,a group maintenance model is developed,in which the system is repaired preventively in accordance with a specified PM base interval.In order to compare with the system EW cost before group maintenance,the system EW cost model before group maintenance is developed.Numerical example demonstrates that offering group maintenance programs can reduce EW cost of the system to a great extent,thereby reducing the EW price,which proves to be a win-win strategy to manufacturers and users.

A Hybrid Spatial Dependence Model Based on Radial Basis Function Neural Networks (RBFNN) and Random Forest (RF)

The majority of spatial data reveal some degree of spatial dependence. The term “spatial dependence” refers to the tendency for phenomena to be more similar when they occur close together than when they occur far apart in space. This property is ignored in machine learning (ML) for spatial domains of application. Most classical machine learning algorithms are generally inappropriate unless modified in some way to account for it. In this study, we proposed an approach that aimed to improve a ML model to detect the dependence without incorporating any spatial features in the learning process. To detect this dependence while also improving performance, a hybrid model was used based on two representative algorithms. In addition, cross-validation method was used to make the model stable. Furthermore, global moran’s I and local moran were used to capture the spatial dependence in the residuals. The results show that the HM has significant with a R2 of 99.91% performance compared to RBFNN and RF that have 74.22% and 82.26% as R2 respectively. With lower errors, the HM was able to achieve an average test error of 0.033% and a positive global moran’s of 0.12. We concluded that as the R2 value increases, the models become weaker in terms of capturing the dependence.

Molecular dynamics study on temperature and strain rate dependences of mechanical tensile properties of ultrathin nickel nanowires

Based on the EAM potential, a molecular dynamics study on the tensile properties of ultrathin nickel nanowires in the （100〉 orientation with diameters of 3.94, 4.95 and 5.99 nm was presented at different temperatures and strain rates. The temperature and strain rate dependences of tensile properties were investigated. The simulation results show that the elastic modulus and the yield strength are gradually decreasing with the increase of temperature, while with the increase of the strain rate, the stress--strain curves fluctuate more intensely and the ultrathin nickel nanowires rupture at one smaller and smaller strain. At an ideal temperature of 0.01 K, the yield strength of the nanowires drops rapidly with the increase of strain rate, and at other temperatures the strain rate has a little influence on the elastic modulus and the yield strength. Finally, the effects of size on the tensile properties of ultrathin nickel nanowires were briefly discussed.

Estimating the Components of a Mixture of Extremal Distributions under Strong Dependence

In this paper, we provide a method based on quantiles to estimate the parameters of a finite mixture of Fréchet distributions, for a large sample of strongly dependent data. This is a situation that appears when dealing with environmental data and there was a real need of such method. We validate our approach by means of estimation and goodness-of-fit testing over simulated data, showing an accurate performance.

Temperature and drain bias dependence of single event transient in 25-nm FinFET technology

In this paper, we investigate the temperature and drain bias dependency of single event transient （SET） in 25-nm fin field-effect-transistor （FinFET） technology in a temperature range of 0-135 ℃ and supply voltage range of 0.4 V- 1.6 V. Technology computer-aided design （TCAD） three-dimensional simulation results show that the drain current pulse duration increases from 0.6 ns to 3.4 ns when the temperature increases from 0 to 135 ℃. The charge collected increases from 45.5 ℃ to 436.9 fC and the voltage pulse width decreases from 0.54 ns to 0.18 ns when supply voltage increases from 0.4 V to 1.6 V. Furthermore, simulation results and the mechanism of temperature and bias dependency are discussed.

Hiding dependence-discovery of F-hiding laws and system laws

Function one direction S-rough sets have dynamic characteristics and law characteristics. By using the function one direction S-rough sets, this article presents the concepts of the f-hiding law, F-hiding law, f-hiding law dependence and F-hiding law dependence. Based on the concepts above, this article proposes the hidingdependence theorem of f-hiding laws, the hiding-dependence theorem of F-hiding laws, the hiding-dependence separation theorem, the hiding dependence-discovery principle of unknown laws. Finally, the application of the hiding dependence of hiding laws in the discovery of system laws is given.

Tensile mechanical analysis of anisotropy and velocity dependence of the spinal cord white matter:a biomechanical study

In spinal cord injuries,external forces from various directions occur at various velocities.Therefore,it is important to physically evaluate whether the spinal cord is susceptible to damage and an increase in internal stress for external forces.We hypothesized that the spinal cord has mechanical features that vary under stress depending on the direction and velocity of injury.However,it is difficult to perform experiment because the spinal cord is very soft.There are no reports on the effects of multiple external forces.In this study,we used bovine spinal cord white matter to test and analyze the anisotropy and velocity dependence of the spinal cord.Tensile-vertical,tensile-parallel,shear-vertical,and shear-parallel tests were performed on the white matter in the fibrous direction(cranial to caudal).Strain rate in the experiment was 0.1,1,10,and 100/s.We calculated the Young’s modulus of the spinal cord.Results of the tensile and shear tests revealed that stress tended to increase when external forces were applied parallel to the direction of axon fibers,such as in tensile-vertical and shear-vertical tests.However,external forces those tear against the fibrous direction and vertically,such as in tensile-parallel and shear-parallel tests,were less likely to increase stress even with increased velocity.We found that the spinal cord was prone to external forces,especially in the direction of the fibers,and to be under increased stress levels when the velocity of external forces increased.From these results,we confirmed that the spinal cord has velocity dependence and anisotropy.The Institutional Animal Care and Use Committee of Yamaguchi University waived the requirement for ethical approval.

Temperature Dependence of the Energy-Band Structure for the Holstein Molecular-Crystal Model

We study the influences of the temperature on the energy-band structure for the Holstein molecular-crystal model. We show that the energy-band width and the energy-gap width of a solid are relevant to both the interaction between an electron and thermal phonons and to thermal expansion. For a one-dimensional Li atom lattice chain, under the chosen parameters,the width of the ls and 2s energy bands narrows as the temperature increases and the energy-gap width between the two bands widens. These results agree qualitatively with those observed experimentally. Studying temperature dependence of the energy-band structure is of great importance for understanding optical and transporting characteristics of a solid.

Panel data models with cross-sectional dependence: a selective review

In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.

Temperature Dependence of Performance of 6H-SiC Unipolar Power Devices

The temperature dependence of some performance of 6H SiC unipolar power devices is analyzed theoretically.By employing the temperature dependent ionization coefficient and mobility of a silicon carbide,the analytical expressions of the temperature dependent performance,such as breakdown characteristics and on resistance of 6H SiC unipolar power devices are derived in a closed form.The analytical results are compared with the experimental results,with good accordance found in the breakdown characteristics.

Orientation and ellipticity dependence of high-order harmonic generation in nanowires

It has been predicted that high-order harmonic generation(HHG) in nanowires has the potential to scale up photon energy and harmonic yield.However,studies on HHG in nanowires are still theoretical and no relevant experimental results have been reported as yet.Our experimental observation of the high-order harmonic in cadmium sulfide nanowires(CdS NWs) excited by a mid-infrared laser is,to our knowledge,the first of such study,and it verifies some of the theoretical results.Our experimental results show that the observed harmonics are strongest when a pump laser is parallel to the nanowires.Therefore,the theoretical prediction that harmonics are strongest under the nanowires parallel to the laser field is confirmed experimentally,and this can be used to determine the orientation of the nanowire.In addition,harmonics are sensitive to the variation of pump light ellipticities.This orientation dependence opens new opportunities to access the ultrafast and strong-field physics of nanowires.

P-sets and Its Dependence Characteristic

P-sets is a set pair, it is composed of internal P-set and outer P-set, it has dynamic characteristic. By using structure of P-sets, dependence theorem and identification theorem are proposed in this paper.

The Dependence Problem for a Class of Polynomial Maps in Dimension Four

Let h be a polynomial in four variables with the singular Hessian Hh and the gradient ▽h and R be a nonzero relation of ▽h. Set H = ▽R（▽h）. We prove that the components of H are linearly dependent when rkHh ≤ 2 and give a necessary and sufficient condition for the components of H to be linearly dependent when rkHh = 3.

THE Z SPECIFICATION DEPENDENCE GRAPH

The lack of existing solutions makes it really hard to understand formal specification languages since the application domain for representations is useful for the purpose of carrying out certain software engineering operations such as slicing and the computation of program metrics.A Z specification dependence graph is presented in this letter. It draws on the strengths of a range of earlier works and adapts them, if necessary, to the Z language.

Development of Japanese Version of Smartphone Dependence Scale

We designed a Japanese version of the Smartphone Dependence Scale (J-SDS) for university students, and assessed its validity and reliability. For development of this scale, we initially selected 43 preliminary items based on previous studies of Internet and mobile phone dependence. Each response was scored using a Likert scale (0, 1, 2, 3), with higher scores indicating greater dependence. After administering the preliminary scale to 149 university students, the final 29 items were selected according to exploratory factor analysis. The final scale consisted of 5 factors: 1) craving and withdrawal, 2) overuse and tolerance, 3) virtual life orientation, 4) disturbance of concentration in class, and 5) physical symptoms. Reliability coefficient (Cronbach’s alpha) values for the 5 factors and total J-SDS were 0.87, 0.87, 0.76, 0.77, 0.69, and 0.92, respectively. We then summed the Likert scores for each item to provide a quantitative overall smartphone dependence score, with higher scores indicating greater dependence. The J-SDS score became significantly higher with longer hours of smartphone use (p < 0.001). Our results suggest that the J-SDS is a reliable and valid scale for screening university students who may be at risk of developing smartphone dependence.

Relationship of Smartphone Dependence to General Health Status and Personality Traits among University Students

We investigated associations between smartphone dependence and general health status or personality traits. To 197 medical university students, we administered a set of self-reporting questionnaires designed to evaluate these parameters. For males, smartphone dependence positively correlated with somatic symptoms, anxiety and insomnia, and emotional instability, and negatively correlated with agreeableness. For females, smartphone dependence positively correlated with somatic symptoms, severe depression, and extraversion, and negatively correlated with social dysfunction. These findings suggest that smartphone dependence may be associated with general health status or personality traits and that there may be a gender difference in these associations.