The present study is an attempt to throw light on the nature of the US policy regarding the Middle East region as portrayed by AI-Sabah, Al-Mashriq and Tariq Al-Shaab papers over a period of three months from 1st of July to 30th of September 2013.

In writing this study, a number of goals have been set by the researcher. These goals may include but in no way limited to the nature of the US image as carried by the above three papers, the nature of the topics tackled by them and the nature of the Arab countries which received more and extensive coverage than others.

A qualitative research approach is proposed for the study. This approach has allowed the researcher to arrive at definite answers for the possible questions rais

     The most common artifacts in ultrasound (US) imaging are reverberation and comet-tail. These are multiple reflection echoing the interface that causing them, and result in ghost echoes in the ultrasound image. A method to reduce these unwanted artifacts using a Otsu thresholding to find region of interest (reflection echoes) and output applied to median filter to remove noise. The developed method significantly reduced the magnitude of the reverberation and comet-tail artifacts. Support Vector Machine (SVM) algorithm is most suitable for hyperplane differentiate. For that, we use image enhancement, extraction of feature, region of interest, Otsu thresholding, and finally classification image datasets to normal or abnormal image.

Recently there has been an urgent need to identify the ages from their personal pictures and to be used in the field of security of personal and biometric, interaction between human and computer, security of information, law enforcement. However, in spite of advances in age estimation, it stills a difficult problem. This is because the face old age process is determined not only by radical factors, e.g. genetic factors, but also by external factors, e.g. lifestyle, expression, and environment. This paper utilized machine learning technique to intelligent age estimation from facial images using support vector machine (SVM) on FG_NET dataset. The proposed work consists of three phases: the first phase is image preprocessing include four st

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

In this paper we investigate the use of two types of local search methods (LSM), the Simulated Annealing (SA) and Particle Swarm Optimization (PSO), to solve the problems ( ) and . The results of the two LSMs are compared with the Branch and Bound method and good heuristic methods. This work shows the good performance of SA and PSO compared with the exact and heuristic methods in terms of best solutions and CPU time.

This research analyzes the level of the short circuit effect of the Iraqi super network and decides the suitable location for the High Voltage Direct Current (HVDC) connections in order to obtain the best short circuit reduction of the total currents of the buses in the network. The proposed method depends on choosing the transmission lines for Alternating current (AC) system that suffers from high Short Circuit Levels (SCLs) in order to reduce its impact on the transmission system and on the lines adjacent to it and this after replacing the alternating current (AC) line by direct current (DC) line. In this paper, Power System Simulator for Engineering (PSS/E) is used to model two types of HVDC lines in an effective regi

           Satire is genre of the literary arts that has always been the source of human interest. Because  it is difficult to accept direct criticism, Satire appears as a literary tool in which vices, follies, abuses and shortcomings are held up to ridicule, with the intent of shaming individuals, corporations, government, or society itself into improvement. A satirical critic usually employs irony to attain this goal. Although satire is usually meant to be humorous, its greater purpose is often profitable social criticism, using wit to draw at

The science of jurisprudence is one of the legal sciences that scholars have been interested in since the first centuries of Islam, and they wrote many books about it, and the science of manuscripts is considered one of the scientific achievements in which many scholars emerged, including Imam Al-Samaani, so I chose this manuscript related to Istism to clarify its concept and meaning for all people, The student (Ali Ahmed Abdel-Aziz Sheikh Hamad) preceded me in the investigation of part of the book, and it was facilitated for me, by the grace of God Almighty, to investigate the issue (if one of the Muslim spouses apostatized and one of the infidel spouses converted to Islam until the end of the issue of if the two spouses were taken capt

In this study, the relationship between the bare soil temperature with respect to its salinity is presented, the bare soil feature is considered only by eliminating all other land features by classifying the site location by using the support vector machine algorithm, in the same time the salinity index that calculated from the spectral response from the satellite bands is calibrated using empirical salinity value calculated from field soil samples. A 2D probability density function is used to analyze the relationship between the temperature rising from the minimum temperature (from the sunrise time) due to the solar radiation duration tell the time of the satellite capturing the scene image and the calibrated salinity index is presented. T

Three isolated bacteria were examined to remove heavy metals from the industrial wastewater of the Diala State Company of Electrical Industries, Diyala-Iraq. The isolated bacteria were identified as Pseudomonas aeruginosa, Escherichia coli and Sulfate Reducing Bacteria (SRB). The three isolates were used as an adsorption factor for different concentrations of Lead and Copper (100, 150, and 200 ppm.), in order to examine the adsorption efficiency of these isolates. In addition, the effect of three factors on heavy metals adsorption were examined; temperature (25, 30, and 37 ?C), pH (3 and 4.5) and contact time (2 and 24 hrs). The results showed that the highest level of lead adsorption was obtained at 37 ?C by E. coli, P, aerugenosa and