Classification is a learning function that maps a given data item into one of several predefined classes. It is a data analysis technique that extracts models describing important data classes and predicts future values. Basically, classification techniques have better capability to handle a wider variety of datasets than regression. It can also be described as a supervised learning algorithm i...

Topic models can be used to improve classification of protein-protein interactions (PPIs) by condensing lexical knowledge available in unannotated biomedical text into a semantically-informed kernel smoothing matrix. Detection of sentences that describe PPIs is difficult due to lack of annotated data. Furthermore, sentences generally contain a small percentage of the features, thus leading to s...

We consider the problem of clustering incomplete data drawn from a union of subspaces. Classical subspace clustering methods are not applicable to this problem because the data are incomplete, while classical low-rank matrix completion methods may not be applicable because data in multiple subspaces may not be low rank. This paper proposes and evaluates two new approaches for subspace clusterin...

It is relatively easy to obtain sets of images that are known to contain objects of a certain category, such as “face”, or “bicycle”. There has been promising work on using such data sets — without any manual labeling of object features — to learn generative models for object categories [4, 1]. These models can then be used to detect instances of the categories in other images. However, these g...

Indole-3-acetyl-myo-inositol esters have been demonstrated to be endogenous components of etiolated Zea mays shoots tissue. This was accomplished by comparison of the putative compounds with authentic, synthetic esters. The properties compared were liquid and gas-liquid chromatographic retention times and the 70-ev mass spectral fragmentation pattern of the pentaacetyl derivative. The amount...

A universal approach by Laplace transform to the variational iteration method for fractional derivatives with the nonsingular kernel is presented; in particular, the Caputo-Fabrizio fractional derivative and the Atangana-Baleanu fractional derivative with the non-singular kernel is considered. The analysis elaborated for both non-singular kernel derivatives is shown the necessity of considering...

This study was conducted to identify Mincane cv clones with superior physical traits in the Trabzon province, Maçka district, Esiro?lu region between 2014 and 2019. Selection research area based on objective revealed 14 traits. In these selected clones, yield, number of nuts per cluster, nut characteristics, kernel weight, shell thickness, percentage, shriveled kernel, cavity, blank split sutur...

X-ray scatter is a major cause of nonlinearity in densitometry measurements using digital mammography. Previous scatter correction techniques have primarily used a single scatter point spread function to estimate x-ray scatter. In this study, a new algorithm to correct x-ray scatter based on image convolution was implemented using a spatially variant scatter point spread function which is energ...

BACKGROUND The high prevalence of obesity (defined by body mass index) among children and adolescents in the United States and elsewhere has prompted increased attention to body fat in childhood and adolescence. OBJECTIVE This report provides smoothed estimates of major percentiles of percentage body fat for boys and girls aged 8-19 years in the United States. METHODS Percentage body fat wa...