Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

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

The feature extraction step plays major role for proper object classification and recognition, this step depends mainly on correct object detection in the given scene, the object detection algorithms may result with some noises that affect the final object shape, a novel approach is introduced in this paper for filling the holes in that object for better object detection and for correct feature extraction, this method is based on the hole definition which is the black pixel surrounded by a connected boundary region, and hence trying to find a connected contour region that surrounds the background pixel using roadmap racing algorithm, the method shows a good results in 2D space objects.
Keywords: object filling, object detection, objec

In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

In this paper a comparison of the experimental of evacuated tube solar water heater systems with and without mirror flat reflector. The aim of using the reflector to improve thermal efficiency, and the data gathered which are (temperature, solar irradiation and time) for three days were compared. the results from compared data the temperature lower increase in evacuated tube solar water heater system without reflector than the temperature increase in evacuated tube solar water heater system with reflector .The results show (53, 39, 35) % for three days respectively that the evacuated tube solar water heater system with reflector has higher thermal efficiencies than the results (47, 28, 30) % for three days respectively thermal efficiencies

This investigation was designed to determine the occurrence of intestinal parasites in fresh
vegetables(Apium graveolense, Lepidium aucheri and Allium porrum), from different markets
as a primary effort in Iraq. Eight genera and species of intestinal parasites appear in
vegetables, they were as follow: Echinococcus sp. 50%,Oxyuris equi 45%,Habronema sp.
45%,Parascaris equroum 31.6%,Strongyloides westrei 30%,Toxocara sp. 18.3%,Ascaris
lumbricoides 11.6% and Hymenolepis sp. 8.3% .The scarcity of fresh water has meant that
urban gardeners are increasingly irrigating their plots with wastewater. This poses a threat to
public health in addition of roaming dogs in open farms. All studied areas showed high rates
of eggs

The first aim of the present study was performed to assay the activity of arginase in sera of women with uterine fibroid.. This study consisted of(50) women with uterine fibroid as patient's group and (30) healthy women as control group. The age ranged between (30-55) years for the two groups. The results showed that highly significant increase (P< 0.0001) in the arginase activity in sera of women with uterine fibroid (7.99± 0.23) I.U/L is found when compared with healthy group (0.52±0.02) I.U/L. The second aim was performed to isolate arginase from sera of women with uterine fibroids. The purification is done by addition of ammonium sulfate, dialysis, gel filtration chromatography by using sephadex G-50 and ion exchange chromatography