We examined the statistical performance of clustering single particle molecular images by bottom-up clustering, a hierarchical algorithm, using simulated protein images with a low signal-to-noise ratio. Using covariance for the measure of similarity together with the iterative alignment, our method was found to be fairly robust against noise. Clustering tests of four known protein structures we...

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an improved illumination normalization method for face recognition. Illumination normalization algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates th...

Nonparametric regression makes it possible to visualize and describe spatial trends without requiring the specification of a parametric model, but appropriate choice of smoothing parameters is important to avoid misinterpreting the nonparametric fits. Because spatial data are often correlated, currently available data-driven smoothing parameter selection methods often fail to provide useful res...

Three wavelet-based spectral smoothing techniques are presented in this paper as a pre-processing stage for headrelated transfer function (HRTF) filter design. These wavelet-based methods include wavelet denoising, wavelet approximation, and redundant wavelet transform. These methods are used with time-domain parametric filter design methods to reduce the order of the IIR filters which is usefu...

The practice of income smoothing is a common phenomenon that occurs as management effort to reduce reported profit fluctuations. This study aims determine the effect managerial ownership, institutional Net Profit Margin, Cash Holding, Bonus Plan, and dividend payout ratio on practices. sample this research non-financial companies are listed Indonesia Stock Exchange in 2018-2020. Data obtained f...

Abstract. The naive Bayes text classifier has long been a core technique in information retrieval and, more recently, it has emerged as a focus of research itself in machine learning. This paper is concerned with the naive Bayes text classifier in its multinomial model instantiation. This model and an “equivalent” reversed version proposed here are interpreted under the statistical framework of...

We examined the statistical performance of clustering single particle molecular images by bottom-up clustering, a hierarchical algorithm, using simulated protein images with a low signalto-noise ratio. Using covariance for the measure of similarity together with the iterative alignment, our method was found to be fairly robust against noise. Clustering tests of four known protein structures wer...

ABSTRACT A new fast-CAD imaging model for buried extreme ultra violet (EUV) mask defects is presented that exploits the smoothing process used to mitigate buried EUV multilayer defects. Since the characteristics of the smoothing process dictate nearly identical surface shapes for all defects a single parameter, the peak height of the final profile, is sufficient to predict the projection printe...

The novelty task consists of finding relevant and novel sentences in a ranking of documents given a query. In the literature, different techniques have been applied to address this problem. Nevertheless, little is known about Language Models for novelty detection and, especially, the effect of smoothing on the selection of novel sentences. Language Models can be used to study novelty and releva...

In this paper, the effect of spatial smoothing on performance of widely used stochastic narrowband multiple-input multiple-output (MIMO) radio channel model, namely the Kronecker model, is investigated based on data measured in urban microcellular environment at 5.3 GHz carrier frequency. Results from non-line of sight (NLOS) and line of sight (LOS) traveling routes are analyzed. It is noticed ...