This work presents semi-blind acoustic model adaptation based on a piece-wise energy decay curve. The dual slope representation of the piece-wise curve accurately captures the early and late reflection decay that helps in precisely modeling the smearing effect caused due to reverberation. The slopes are estimated in a semi-blind fashion, late reflection slope is estimated blindly by finding the...

This paper presents a method for extraction and analysis of curve–type structures which consist of disconnected components. Such structures are found in electron–microscopy (EM) images of metal nanograins, which are widely used in the field of nanosensor technology. The topography of metal nanograins in compound nanomaterials is crucial to nanosensor characteristics. The method of completing su...

This paper presents a new approach for short-term load forecasting (STLF). Curve fitting prediction and time series models are used for hourly loads forecasting of the week days. The curve fitting prediction (CFP) technique combined with genetic algorithms (GAs) is used for obtaining the optimum parameters of Gaussian model to obtain a minimum error between actual and forecasted load. A new tec...

We propose a method for computation of the Hessian of axially symmetric functions on the roto-translation group SE(3). Eigendecomposition of the resulting Hessian is then used for curvature estimation of tubular structures, similar to how the Hessian matrix of 2D or 3D image data can be used for orientation estimation. This paper focuses on a new implementation of a Gaussian regularized Hessian...

Assuming axial symmetry, we introduce a surface of revolution approach to model the membrane at equilibrium. We consider a generating curve γ parameterized by arc length s lying in the x− z plane. The curve γ is expressed as γ(0, s1) → R γ(s) = (R(s), 0, z(s)) (S1.1) where s1 is the total arc-length. This generating curve leads to a global parametrization of the membrane expressed as X : (0, s1...

We present a statistical path loss model derived from 1.9 GHz experimental data collected across the United States in 95 existing macrocells. The model is for suburban areas, and it distinguishes between different terrain categories. Moreover, it applies to distances and base antenna heights not well-covered by existing models. The characterization used is a linear curve fitting the decibel pat...

In this article we discuss Markovian term structure models in discrete time and with continuous state space. More precisely, we are concerned with the structural properties of such models if one has the Markov property for a part of the forward curve. We investigate the two cases where these parts are either a true subset of the forward curve, including the short rate, or the entire forward cur...

The distribution of in vivo average firing rates within local cortical networks has been reported to be highly skewed and long tailed. The distribution of average single-cell inputs, conversely, is expected to be Gaussian by the central limit theorem. This raises the issue of how a skewed distribution of firing rates might result from a symmetric distribution of inputs. We argue that skewed rat...

Here in this paper, we investigate the performance of a diagnostic test based on mixture Gaussian Copula which incorporates Markov Chain. Suppose that context an infectious disease, there are three states; Susceptible (S), Infected (I), or Recovered (R). We compare approach with ROC (Receiver Operating Characteristic) Curve is usually used studies.

 Spatial generalized linear mixed models are used commonly for modelling non-Gaussian discrete spatial responses. We present an algorithm for parameter estimation of the models using Laplace approximation of likelihood function. In these models, the spatial correlation structure of data is carried out by random effects or latent variables. In most spatial analysis, it is assumed that rando...