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

In this paper the modified trapezoidal rule is presented for solving Volterra linear Integral Equations (V.I.E) of the second kind and we noticed that this procedure is effective in solving the equations. Two examples are given with their comparison tables to answer the validity of the procedure.

Based on the diazotization reaction of 4-aminoacetophenone with sodium nitrite in acid medium to form diazonium salt, which was coupled with Methyldopa to form a violet reddish soluble azo dye with maximum absorbance at 560 nm,a batch procedure had been developed for the estamination of Methyldopa. Under optimum experimental parameters affecting on the development and stability of the colored product, Beer´s law obeyed in the range (0.5-45) ?g.ml-1 with a correlation coefficient (0.9979).The proposed method was successfully applied to the determination of Methyldopa in either pure form and in commercial brands of pharmaceuticals, no interference was observed from common excipients in the formulations. The analytical results obtained by app

Research included the preparation of medicinal substances ( propyl thiouracil). Which is the rule thiourea and related compounds a fundamental rule in preparation fall within the range of drugs of anti-thyroid activity (Antithyroid Drug ) , this drug prevents the thyroid hormone production against excessive activity of the thyroid gland .That the formation of iodine is important for their impact on hormone secretion thyroid , the two types, thyroxin or T4 is the main hormone ,Triiodothyronine or T3, and these hormones released by hormone regulator called (TSH) . Article attend thiourea treatment with an alcohol- soluble sodium and added to the interaction rule b- oxo ester after adjusting the PH=4 output ( propylthiouracil ) the

Different additives are used in drilling fluids when the demanded properties cannot be gotten with clays. Drilling muds needs several additives and materials to give good characteristics. There are local alternatives more suitable for enhancing the rheology and filtration of drilling fluids. An experimental work had been conducted to assess the suitability of using potato starch to enhance rheological properties and filtration in drilling mud. This study investigated the potato starch as a viscosifier and fluid losses agent in drilling fluid. Results from this study proved that rheological properties of potato starch mud increased when pH of drilling fluid is increased.  Potato starch could be used to enhance gel strength at low pH

In this research, we have added nano anatase TiO₂ as a partial replacement of Portland cement by a weight percentage of (0.25 to 1%) for the development of properties for protection against bacteria. The control mix was made by using "the cement to sand" proportion about (1: 2.75) with the "water to cement" proportion of (0.5) to study the structure, porosity, water absorption, density, mechanical properties, as well as anti-bacterial behavior. Inspections have been done such as scanning electron microscopy (SEM), and atomic force microscope (AFM) for mortar. Experimental results showed that after the addition of Nano powders in cement mortar, the structural properties improved significantly with the development of hydration o

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl