This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Oil is considered the most important source for providing the funds for the national economic sectors. The revenues of oil constitute %95 of the GPD. Therefore, the development of the remaining sectors depend on oil..

The Iraqi Oil Marketing Organization (SOMO) depended on the a unified price for all the buyers, That may not reflect the real value of market and did not contribute in marketing the type of heavy oil. Then, to what extent had SOMO been able to market the light and heavy crude oil in a way that contains the expected increase in the crude oil production.      

Numerous regions in the city of Baghdad experience the congestion and traffic problems. Due to the religious and economic significance, Al-Kadhimiya city (inside the metropolitan range of Baghdad) was chosen as study area. The data gathering stage was separated into two branches: the questionnaire method which is utilized to estimate the traffic volumes for the chosen roads and field data collection method which included video recording and manual counting for the volumes entering the selected signal intersections. The stage of analysis and evaluation for the seventeen urban roads, one highway, and three intersections was performed by HCS-2000 software.The presented work plots a system for assessing the level of service

The current investigation examines the combined impacts of ultrasonic radiation and hydrogen donors on the viscosity of heavy crude oil. The impact of exposure time, power, duty cycle, and temperature on the viscosity of Iraqi heavy crude oil with 20.32 API was studied. Also, the viscosity of the oil samples, which were mixed with a hydrogen donor (decalin) and subjected to ultrasonic treatment under optimal conditions, was examined to evaluate the combined impact of ultrasonic radiation and hydrogen donor on the viscosity of crude oil. The viscosity experienced a decrease of 52.34% at 2 min of irradiation, 360 W ultrasonic power, 0.8 duty cycle, 35 ⁰C, and 8vol% decalin. To validate the outcomes of the experiments, asphaltene content, s

In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

Water samples were collected from output of water for Al-Wahda plant where located in al-karrada area in Baghdad city to study water contamination with bacteria, fungi and Algae. The study lasted one year started on August, 2016 to July,2017.Results were acquired according to two tests performed, the first is biological test included total coliform,E.coli, pseudomonas aeruginosa, total fungi, Diatom and non Diatom Algae and the second is physiochemical test included temperature, turbidity and residual chlorine. The results of bacteria were within the permitted specification in the Iraqi standards no. 14/2270 for the year 2015 except August was exceeded the permitted standard for total coliform, it was 1.1< cell/100 ml.Total Fungi, Dia

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme