yt and Pt replaced by any variables that affect supply but not demand. In the 1970s econometricians began to recognize that how the supply or demand equation is normalized affects the estimator of the supply or demand elasticity (¡M or ¬R ) when the two-stage least squares (2SLS) approach is employed. The quality of this estimator is sensitive to the strength of instruments used in the 2SLS est...

The random waypoint model (RWP) is one of the most widely used mobility models in performance analysis of ad hoc networks. We analyze two key properties of the RWP model in a given convex area: the stationary spatial distribution for the location of the node and the mean length of a leg (line between two waypoints). A general expression is given for the spatial node distribution in the form of ...

Two techniques for speaker adaptation based on frequency scale modifications are described and evaluated. In one method, minimum mean square error matching is performed between a spectral template for each speaker to a "typical speaker" spectral template. One parameter, a warping factor, is used to control the spectral matching. In the second method, a neural network classifier is used to adjus...

The study evaluated all patients undergoing permanent pacemaker and ICD implantation over a 4-year period to determine if anticoagulated patients required normalization of coagulation factors in the periprocedural period. The study included 1,025 (597 men, 428 women, age 24-100 years, mean 72 years) consecutive patients who underwent device implantation using mostly a percutaneous subclavian ap...

In a microphone array system, feature combination in the MFCC domain can improve speech recognition accuracy. Multiple microphones provide different feature parameters such as MFCCs even if they have similar speech and noise signals, because of the phase difference and transmission characteristics. In this paper, we investigate how the recognition performance changes when we average multiple MF...

We introduce an approach to fMRI analysis based on the Lattice Associative Memory (LAM) Endmember Induction Heuristic Algorithm (EIHA). Induced endmembers are used to compute the activation levels of voxels as result of an unmixing process. The endmembers correspond to diverse activation patterns, one of these activation patterns corresponds to the rest state of the neuronal tissue. We introduc...

In voice conversion, a simple frame-level mean and variance normalization is typically used for fundamental frequency (F0) transformation, which is text-independent and requires no parallel training data. Some advanced methods transform pitch contours instead, but require either parallel training data or syllabic annotations. We propose a method which retains the simplicity and text-independenc...

In this research, the normalization performance of proposed adjusted min-max methods was compared to statistical column, decimal scaling, and methods, in terms accuracy mean square error final classification outcomes. The evaluation process employed an artificial neural network on a large variety widely used datasets. best method normalization, providing 84.0187% average ranking 0.1097 across a...

Analysis of epigenetic mechanisms, particularly DNA methylation, is of increasing interest for epidemiologic studies examining disease etiology and impacts of environmental exposures. The Infinium HumanMethylation450 BeadChip(®) (450K), which interrogates over 480,000 CpG sites and is relatively cost effective, has become a popular tool to characterize the DNA methylome. For large-scale studies...

Deep learning based image steganalysis has attracted increasing attentions in recent years. Several Convolutional Neural Network (CNN) models have been proposed and achieved state-of-the-art performances on detecting steganography. In this paper, we explore an important technique in deep learning, the batch normalization, for the task of image steganalysis. Different from natural image classifi...