The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemi

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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

In order to have an idea about what happens in Iraqi food establishments in relation to implement quality management system ISO 9001, this study was performed to show the actual situation of Iraqi food establishments concerning quality management system (ISO 9001:2015), reasons of implementing, factors that hinder implementing and problems faced high administration for getting establishments certification ISO 9001:2015. The study demonstrated from the questionnaire some difficulties to implement ISO 9001 for both of establishments that implemented the quality system or which in implementing of this international standard. The most important problems during implementing were business culture and costs and the most important proble

In the present work, radon gas concentrations in different surface soil samples in Baghdad governorate were measured using RAD-7 detector. The results have been shown that, the Radon gas concentrations ranged between (41.67±1.78Bq/m3), to (185.67±4.22Bq/m3), a map showing the distribution of the concentration of radon in selected areas was defined to identify areas with high pollution level. The reason for the high concentration of radon is that these surface soil samples are taken from agricultural areas. It is also known that fertilizers contain uranium levels as well as areas bombed in wars in the country. It is worth noting that all radon concentrations in Baghdad governorate are below the recommended minimum of 200-300Bq/m3) (Inte

Back ground: Visceral leishmaniasis is endemic in the
middle and south of Iraq, it involves mostly infants. The
disease is observed mainly among rural areas that are far
from equipped medical centers. Therefore, there is a need
for anon- invasive, cost- effective, reliable, easily
available and fast method of diagnosis of this dngerous
disease.
Objective: The aim was to compare the validity and
predictive values of the recombinant K39 antigen (rK39)
test with that of the indirect fluorescent antibody test
(IFAT) test (the usual laboratory method) in the detection
of visceral leishmaniasis.
Methods: A Cross-sectional study was done in ALMansour Pediatric Hospital (in AL-Rusafa), and Central
Pediatric