In the last years, new non-invasively laser methods were used to detect breast tumors for pre- and postmenopausal females. The methods based on using laser radiation are safer than the other daily used methods for breast tumor detection like X-ray mammography, CT-scanner, and nuclear medicine.  

      One of these new methods is called FDPM (Frequency Domain Photon Migration). It is based on the modulation of laser beam by variable frequency sinusoidal waves. The modulated laser radiations illuminate the breast tissue and received from opposite side.

      In this paper the amplitude and the phase shift of the received signal were calculated according to the orig

From 1979 to 1999 several theatricl groups had produced (Mackbeth) by shakespear which were directed by different director and the role being played by different actors. So the questions are: How did those a Iraqi actors approach that character by their performance? Did they interpret the character Truelly as the poet wanted to be. The researcher aims to find out the true performance by the actor who impersonate (mackbeth) as a wicked personality, who had un rational ambition. The researcher also aims to expose the style of acting fallowed by the Iraqi actors in that play. In chapter of review of literature, The researcher discusses the weaning and procedure of the actor performance which include characterization and transformation. He a

The excellence and uniqueness is what makes the artwork creative or not, and the School of Op. Art in Iraq came to reveal new phenomena distinct style, unique in units built, although a few worked in this aspect of the art, but they left their mark distinct, in the research, construction and installation of what binds them in heritage and civilization, it is a new vision of linking the past with the present, they adopt and engineering units may be architectural sometimes in composition, concluded a researcher at the end of the research to the main findings and conclusions, which is that more business was a square-shaped or semi-square, which is commensurate painting with visual, which is a set of vocabulary or repeat units, we do not fin

This study included isolation and characterization of extremely halophilic bacteria from Al-Massab Al-Aam region in South of Iraq Fifty isolates were identified by using numerical taxonomy 40 strains belonged to the genus Halobacterium which inclucted Hb. halobium Hb. cutirubrum Hb. salinarium Hb. saccharovorum Hb. valismortis and Hb. volcanii. Ten strains belonged to the genus Halococcus which included Hc. morrhuae Hc. saccharolyticus. Growth curves were sensitive mutants determined for wild type and salt Generation time in logarthmic phase was measured and found to be (10.37 2hr 7 0.59) for Hb. salinarium / 18 (6.490 hr 0.24) for Hb. cutirubrum / 32, (6.700 hr + 0.488) for Hb. valismortis / 20, (11.243 hr + 0.96) for Hb. volcanii / 7. (7

Sixty four local isolated of Klebsiella spp. have been isolated from environment samples (soil and water). These isolates were identified and diagnosis according to phenotype and biochemical tests. These isolates were subjected to primary and secondary screening, to select the isolate with the highest laccase activity. Fifteen isolates chosen from primary screening for screening their enzyme activity in secondary screening. It has been found the Klebsiella(K7) has the highest productivity of the enzyme (12 Unit/ml).Klebsiella(K7) isolate was diagnosis by Vitak 2 system, it was identified asK. pneumonia. The laccase purified was characterization, the experiments showed that: The molecular weight of laccase was 120KD and the optimum pH for th

This study aimed to conduct a comparative analysis of seven calliphorid species of third- instar larvae that were collected from central Iraq. The purpose was to morphologically characterize these species and develop an identification key to differentiate them from closely related species. Scanning Electron Microscope (SEM) graphical images and high-resolution traditional optical microscopes were used to analyze the morphological characteristics of the species Calliphora vomitoria (Linnaeus, 1758), C. vicina Robineau-Desvoidy, 1830, Chrysomya albiceps (Widemann, 1819), Ch. rufifacies (Macquart, 1844), Ch. megacephala (Fabricius, 1794), Lucilia cuprina (Wiedemann, 1830), and L. sericata (Meigen, 1826). An identification key was const

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le