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

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 work ,medical zinc oxide was produced from zinc scraps instead of traditional method which used for medical applications such as skin diseases, Iraq is importing around 50 ton/year for samarra plant the producted powder has apartical size less than 5 micron and the purity was more than 99.98%,also apilot plant of yield capacitiy 15 kg/8hours wsa designed and manufactured .

Increasing the variety of products that are being designed with sculptured surfaces, efficient machining of these surfaces has become more important in many manufacturing industries. The objective of the present work is the investigation of milling parameters for the sculptured surfacesthat effecting of surface roughness during machining of Al-alloy. The machining operation implemented on C-TEK CNC milling machine. The influence of the selected variables on the chosen characteristics have been accomplished using Taguchi design approach, also ANOVA had been utilized to evaluate the contributionsof each parameter on proc

Over the past few decades, the surveying fieldworks were usually carried out based on classical positioning methods for establishing horizontal and vertical geodetic networks. However, these conventional positioning techniques have many drawbacks such as time-consuming, too costly, and require massive effort. Thus, the Global Navigation Satellite System (GNSS) has been invented to fulfill the quickness, increase the accuracy, and overcome all the difficulties inherent in almost every surveying fieldwork. This research assesses the accuracy of local geodetic networks using different Global Navigation Satellite System (GNSS) techniques, such as Static, Precise Point Positioning, Post Processing Kinematic, Session method, a

A descriptive study, which was using an assessment approach, was conducted for the
determination of the impact of rheumatoid arthritis and osteoarthritis patient’s functional disability
upon their life style. The study was carried out at the Rheumatology and outpatients clinics of ALKarama
Teaching Hospital, Baghdad Teaching Hospital AL-Kindey Teaching Hospital and Specialized
surgeries Teaching Hospital for the period of October 15th 2003 through May 13th 2004 in Baghdad
City. A purposive (non-probability) sample of (245) arthritis patients which was comprised (111)
rheumatoid arthritis patients and (134) osteoarthritis patients, was selected out of the early stated
settings. The questionnaire was comprised of

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are