Basic Functions for Computational Implementation of the Box-Cox Symmetric Class of Distributions

A class of distributions called Box-Cox symmetric was proposed for random variables with asymmetric distributions. This class allows through its structure an interpretation of the parameters in terms of quantiles (in particular, the median), relative dispersion and skewness. This study presents the initial results of the computational development of basic functions of each of the distributions that make up the Box-Cox symmetric class. Four functions have been developed to compose a routine in software R up to now. These functions are related to random numbers generation, probability density function, cumulative distribution function, and quantile function associated to a given probability. Examples of implemented functions were presented. The gamlss routine was used to check the performance of developed functions.

Function of pioneer neurons specified by the basic helix-loop-helix transcription factor atonal in neural development

Basic helix-loop-helix （bHLH） transcription factors regulate the differentiation of various tissues in a vast diversity of species. The bHLH protein Atonal was first identified as a proneural gene involved in the formation of mechanosensory cells and photoreceptor cells in Drosophila （larman et al., 1993, 1994）. Atonal is expressed in sensory organ precursors and is required and sufficient for the development of chordotonal organs （Jar- man et al., 1993）. Moreover, Atonal expression is observed in the developing eye and is essential for the differentiation of R8 photoreceptors, which are the first photoreceptors that appear during development. Atonal is not involved in the formation of other photoreceptors （R1-R7） directly. However, R8 photore- ceptors recruit other photoreceptors from the surrounding cells （Jarman et al., 1994）.

A Deep Web Query Interfaces Classification Method Based on RBF Neural Network

This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial basic function neural network （RBFNN） algorithm to classify the query interfaces. The applied RBFNN is a kind of effective feed-forward artificial neural network, which has a simple networking structure but features with strength of excellent nonlinear approximation, fast convergence and global convergence. A TEL_8 query interfaces＇ data set from UIUC on-line database is used in our experiments, which consists of 477 query interfaces in 8 typical domains. Experimental results proved that the proposed approach can efficiently classify the query interfaces with an accuracy of 95.67%.

On-line evaluating on quality of mild steel joints in resistance spot welding

A method was developed to realize quality evaluation on every weld-spot in resistance spot welding based on information processing of artificial intelligent. Firstly, the signals of welding current and welding voltage, as information source, were synchronously collected. Input power and dynamic resistance were selected as monitoring waveforms. Eight characteristic parameters relating to weld quality were extracted from the monitoring waveforms. Secondly, tensile-shear strength of the spot-welded joint was employed as evaluating target of weld quality. Through correlation analysis between every two parameters of characteristic vector, five characteristic parameters were reasonably selected to found a mapping model of weld quality estimation. At last, the model was realized by means of the algorithms of Radial Basic Function neural network and sample matrixes. The results showed validations by a satisfaction in evaluating weld quality of mild steel joint on-line in spot welding process.

The research on relationship between wavelet transform on vertical deformation and moderate earthquakes in Hexi region,Gansu Province

n this paper, the possibility of wavelet transform applied to compute the vertical deformation is discussed. Both two dimension plane equation of wavelet transform and B-wavelet based on basic spline function are deduced. According to the equation and B-wavelet, multi-periods vertical deformation data which were measured from 1971 to 1995 in Hexi-Qilian Mountain region, Gansu Province are calculated. The results are: ① The multi-resolution analysis of wavelet transform can filter the different spatial wavelength in vertical deformation information on different scales effectively and let us to see the heterogeneous in distribution of vertical deformation clearly, therefore, it is an important tool in investigating the relationship between the vertical deformation and the seismicity; ② The main variation of both the first and second results in wavelet transform mainly takes place along the main faults which explains that the short wave variation of vertical deformation is caused by the faults activities; ③ The wavelet transform of vertical deformation in Hexi-Qilian Mountain area shows that the vertical deformation in southeast parts of Hexi region was larger than that in other parts and there were several moderate earthquakes such as Menyuan Ms=6.4 earthquake in 1986, Jingtai Ms=6.2 earthquake in 1990, Yongdeng Ms=5.8 earthquake in 1995. The vertical deformation in the northwest part of the region was not so large as that in southeast part where ware no strong earthquakes.

A Local Sparse Screening Identification Algorithm with Applications

Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SINDy)rule to restore nonlinear equations,there also exist obstacles.One is the excessive dependence on empirical parameters,which increases the difficulty of data pre-processing.Another one is the coexistence of multiple coefficient vectors,which causes the optimal solution to be drowned in multiple solutions.The third one is the composition of basic function,which is exclusively applicable to specific equations.In this article,a local sparse screening identification algorithm(LSSI)is proposed to identify nonlinear systems.First,we present the k-neighbor parameter to replace all empirical parameters in data filtering.Second,we combine the mean error screening method with the SINDy algorithm to select the optimal one from multiple solutions.Third,the time variable t is introduced to expand the scope of the SINDy algorithm.Finally,the LSSI algorithm is applied to recover a classic ODE and a bi-stable energy harvester system.The results show that the new algorithm improves the ability of noise immunity and optimal parameters identification provides a desired foundation for nonlinear analyses.

A generalized evidence distance

How to efficiently measure the distance between two basic probability assignments（BPAs） is an open issue. In this paper, a new method to measure the distance between two BPAs is proposed, based on two existing measures of evidence distance. The new proposed method is comprehensive and generalized. Numerical examples are used to illustrate the effectiveness of the proposed method.

A Generalization of the Concept of q-fractional Integrals

In this paper, we consider the fractional q-integral with variable lower limit of integration. We prove the semigroup property of these integrals, and a formula of Leibniz type. Finally, we evaluate fractional q-integrals of some functions. The consideration of q-exponential function in that sense leads to q-analogs of Mittag-Leffier function.

A RECTANGULAR SHELL ELEMENT FORMULATION WITH A NEW MULTI-RESOLUTION ANALYSIS

A multi-resolution rectangular shell element with membrane-bending based on the Kirchhoff-Love theory is proposed. The multi-resolution analysis （MRA） framework is formulated out of a mutually nesting displacement subspace sequence, whose basis functions are constructed of scaling and shifting on the element domain of basic node shape functions. The basic node shape functions are constructed from shifting to other three quadrants around a specific node of a basic element in one quadrant and joining the corresponding node shape functions of four elements at the specific node. The MRA endows the proposed element with the resolution level （RL） to adjust the element node number, thus modulating structural analysis accuracy accordingly. The node shape functions of Kronecker delta property make the treatment of element boundary condition quite convenient and enable the stiffness matrix and the loading column vectors of the proposed element to be automatically acquired through quadraturing around nodes in RL adjusting. As a result, the traditional 4-node rectangular shell element is a mono-resolution one and also a special case of the proposed element. The accuracy of a structural analysis is actually determined by the RL, not by the mesh. The simplicity and clarity of node shape function formulation with the Kronecker delta property, and the rational MRA enable the proposed element method to be implemented more rationally, easily and efficiently than the conventional mono-resolution rectangular shell element method or other corresponding MRA methods.