Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

   Calcareous nannofossils were documented from the upper part of the Cretaceous Balambo Formation in northern Iraq with the aim of determining an evidence for the Oceanic Anoxic Event. A detailed investigation of the calcareous nannofossils led to the identification of twenty-four species. Regarding these data, Discolithus litterarius (Górka, 1957) was identified at the studied interval with the age of Early Aptian.

   Early Aptian assemblages are dominated by nannoconids that drop sharply within the D. litterarius nannofossil zone, which may be related to the nannoconid crisis recorded in the Early Aptian in the other parts of the world. This event is coincided by a decrease in CaCO_3<

The present work introduces, external morphological study of the leafhopper Neoalitarus
fenestratus Herrich-Schäeffer (Deltocephalinae:Oposiini), particularly the male genitalia
which were dissected and illustrated.

IA Ali, FK Emran, DF Salloom, Annals of the Romanian Society for Cell Biology, 2021

ABSTRACT Background: Bracket rebonding is a common problem in orthodontics which may result in many drawbacks. The aims of this study were to evaluate the effects of application of two enamel protective agents “Icon” and “ProSeal” on shear bond strength before and after rebonding of stainless steel orthodontic brackets using conventional orthodontic adhesive and to assess the site of bond failure. Materials and methods: Fifty sound extracted human upper first premolar teeth were selected and randomly divided into two equal groups; the first time bonding and the rebonding groups (n=30). Each group was subdivided into control, Icon and ProSeal subgroups. The enamel protective agents were applied after etching (precondi

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall