Image segmentation can be defined as a cutting or segmenting process of the digital image into many useful points which are called segmentation, that includes image elements contribute with certain attributes different form Pixel that constitute other parts. Two phases were followed in image processing by the researcher in this paper. At the beginning, pre-processing image on images was made before the segmentation process through statistical confidence intervals that can be used for estimate of unknown remarks suggested by Acho & Buenestado in 2018. Then, the second phase includes image segmentation process by using "Bernsen's Thresholding Technique" in the first phase. The researcher drew a conclusion that in case of utilizing

 The microdrilling and nanodrilling holes are produced by a Q-switched Nd :YAG laser (1064 nm) interaction with 8009 Al alloy using nanoparticles. Two kinds of nanoparticles were used with this alloy. These nanoparticles are tungsten carbide (WC) and silica carbide (SiC). In this work, the microholes and nanoholes have been investigated with different laser pulse energies (600, 700 and 800)mJ, different repetition rates (5Hz and 10Hz) and different concentration of nanoparticles (90%, 50% and 5% ). The results indicate that  the microholes and nanoholes have been achieved when the laser pulse energy is 600 mJ, laser repetition rate is 5Hz, and the concentration of the  nanoparticles (for the two types of n

This study was conducted to determine the ability of water treatment system (Vortisand) to reduce some chemical and physical properties for tigris river raw water, It consisted of turbidity, electrical conductivity, pH, total hardness, calcium Hardness as well as temperature in order to determine the unit`s efficiency for reducing their concentration as compared to those in the water produced by some classical potable water projects (Dora and Wathba) in Baghdad. Samples were collected during the cold months (December 2016 and January 2017) and during the hot months (May and June 2017). The results showed that this system has the ability to reduce some properties such as turbidity, the values were 215NTU in raw water and decreased to NTU

In cognitive radio networks, there are two important probabilities; the first probability is important to primary users called probability of detection as it indicates their protection level from secondary users, and the second probability is important to the secondary users called probability of false alarm which is used for determining their using of unoccupied channel. Cooperation sensing can improve the probabilities of detection and false alarm. A new approach of determine optimal value for these probabilities, is supposed and considered to face multi secondary users through discovering an optimal threshold value for each unique detection curve then jointly find the optimal thresholds. To get the aggregated throughput over transmission

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

S Ali…, Journal of Physical Education, 2019 - Cited by 1

This research include design and implementation of an Iraqi cities database using spatial data structure for storing data in two or more dimension called k-d tree .The proposed system should allow records to be inserted, deleted and searched by name or coordinate. All the programming of the proposed system written using Delphi ver. 7 and performed on personal computer (Intel core i3).

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

This study investigated the treatment of dairy wastewater using the electrocoagulation method with iron filings as electrodes. The study dealt with real samples collected from local factory for dairy products in Baghdad. The Response Surface Methodology (RSM) was used to optimize five experimental variables at six levels for each variable, for estimating chemical oxygen demand (COD) removal efficiency. These variables were the distance between electrodes, detention time, dosage of NaCl as electrolyte, initial COD concentration, and current density. RSM was investigated the direct and complex interaction effects between parameters to estimate the optimum values. The respective optimum value was 1 cm for the distance between electrodes, (6