Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

Background: Fetal macrosomia represent a
continuing challenge in obstetrics and increasing in
it's occurrence as well as it is associated with maternal
and perinatal complications.
Objective : To determine the maternal and perinatal
outcome related to fetal macrosomia.
Design: A prospective case control study.
Patients and methods) :10th March-31st May, 2006
A prospective case control study had done over the
period from 10th March to 31st May, 2006 in Al-Batool
maternity teaching hospital in Mosul city .The study
group consisted from 633 singleton alive newborns
with gestational age ≥37weeks weighing 4000 grams
and heavier and mothers of these newborns compared
with control group which consiste

Background: Bone cutter is widely used in the
Middle east area to cut the prepuce during circumcision.

Results :One hundred twenty one male neonates
were included in this study.The mean operative
time (MOT) was 6 minutes, mean time of
healing (MTH) was 5 days, 7 cases (5.9%)
developed early & late complications, 2 (1.7%)
had bleeding, 3 (2.5%) developed infection, 2
(1.7%) developed late complications in the form
of meatal stenosis.
Settings:Al-Yarmouk Teaching Hospital and a
private surgical clinic.
Aim of the study: To assess the safety of
circumcision using bone cutter.
Methods: Over 6 years period from Jan. 2000
till Dec. 2005, one hundred twenty one male
neonates were circumci

Back ground: In Iraq, after 2003 had more
accidents of the shell, bullet and stab abdominal
wounds, more over colon injuries.
Objective: The aim of this study is to evaluate
the most appropriate management of penetrating
colon injuries, comparing the primary repair with
the diversion.
Methods: Eighty patient series with shell, bullet
and stab colonic injuries during 4.5 years period
from June 2006-december 2010 at Al-Yarmouk
teaching hospital. The study compared the use of
primary repair versus diversion, analyzing
variables such as sex, age, severity of injury and
mortality rate.
Results: there were total 80 patients ,62 (77.5%)
male and 18(22.5%) female .male :female ratio
3.4:1. the most

Extracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone. Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment. The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on. Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or tousing another remedy technique. In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classi