Introduction: Hidden curriculum plays a main role in professionallearning, formation of professional identity, socialization,moral development and learning values, attitudes, beliefs, andknowledge in learners, so it needs to be managed. Althoughthe majority of the theorists believe in the existence of a hiddencurriculum and its greater effect and sustainability com...

New large deviations results that characterize the asymptotic information rates for general d-dimensional (d-D) stationary Gaussian fields are obtained. By applying the general results to sensor nodes on a twodimensional (2-D) lattice, the asymptotic behavior of ad hoc sensor networks deployed over correlated random fields for statistical inference is investigated. Under a 2-D hidden Gauss-Mark...

Radial Basis Function neural network (RBFNN) is a combination of learning vector quantizer LVQ-I and gradient descent. RBFNN is first proposed by (Broomhead & Lowe, 1988), and their interpolation and generalization properties are thoroughly investigated in (Lowe, 1989), (Freeman & Saad, 1995). Since the mid-1980s, RBFNN has been used to apply on many applications, such as pattern classification...

in this paper two nodes to model isotropic and anisotropic media in transmission line matrix method (tlm) are presented. by using these two nodes, the permeability and permittivity of an anisotropic media can be modeled simultaneously. another application of these nodes is in modeling media with permittivity and permeability less than one. in the conventional 2 dimensional tlm, the stubs repres...

The depth of the deep neural network (DNN) refers to number hidden layers between input and output an artificial network. It usually indicates a certain degree complexity computational cost (parameters floating point operations per second) expressiveness once structure is settled. In this study, we experimentally investigate effectiveness using ordinary differential equations (NODEs) as compone...

Neural Ordinary Differential Equations (NODE) have emerged as a novel approach to deep learning, where instead of specifying discrete sequence hidden layers, it parameterizes the derivative state using neural network [1]. The solution underlying dynamical system is flow, and various works explored universality flows, in sense being able approximate any analytical function. In this paper we pres...

In this paper, we meta-analyzed nine of our own studies to examine gender effects in decision-making when information is asymmetrically distributed among group members a hidden profile (HP). particular, examined the influence individual preferences on outcomes and how, or whether, they differed by gender. The meta-analysis studies, which focused decision-making, suggested that preference effect...