Image classification takes a large area in computer vision in term of quality or type or data sharing and so on Iraqi Anber Rice in they need this kind of work, where few in the field of computer science that deal with the types of Iraqi Anber rice, and because of the Anber Rice are grown and produced in Iraq only, and because of the importance of rice around the world and especially in Iraq. In this paper a proposed system distinguishes between the classes of Iraqi Anber Rice that Grown in different parts of Iraq, and have their own specifications for each class by using moment invariant and KNN algorithm. Iraqi Anber Rice that is more than Fiftieth class Cultivated and irrigated in different parts of Iraq, and because of the different

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

Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

This study was carried out for direct detection of typhi and some of its multidrug resistance genes(tem,capt,gyrA&sul2)which encode for resistance to (Ampicillin, Chloramphenicol,Ciprofioxacin,Co-trimoxazole)by using Polymerase Chain Reaction technique .(71)blood samples for people suffering from typhoid fever symptoms depending on the clinical examination and (25)for control were collected. The results investigation for flic gene which encode for flagellin protein indicated that only (19)with percentage of (26,76%)gave appositive results while all control had a negative ones. Investigation for antibiotic resistance drug in samples which show positive results for flic gene showed that there is a multidrug for all antibiotics with (94.7

        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based

Background Immunological gene and serum level for interleukin- 9 rs 17317275 have been established to have linked to predisposition systemic lupus erythematosus (SLE) and its severity. SLE is a severe, systemic autoimmune disease characterized by autoantibody generation, complement activation, and immune complex deposition. In the pathophysiology of SLE, cytokines have a pleiotropic function. Recently, IL-9 was discovered to mediate strong anti-inflammatory effects in numerous cells or experimental autoimmune models. Objective This study aimed to determine the role of age, IL-9 serum level and genetic polymorphism, C-reactive protein (CRP), Anti-nuclear antibody (ANA) and Anti- double-stranded DNA (anti-dsDNA) to recognize SLE pathogenesis.

The present study introduces description of new species of leafhopper Cicadella latreilla nov. External morphological characters particularly female genitalia were discussed and illustrated, shape of male abdominal apodeme, chaetotaxy of genital style and genital plate of male genitalia, shape of Aedeagus and connective . The external morphological characters were: spotting patterns of vertex, face, pronotum of prothorax, and metothorax, and of lower and upper valves of ovipositors,shape of female seventh abdominasternum.

Detection of pathogenic bacteria, such as Listeria  monocytogenes, in food is crucial for safeguarding public health in Iraq.  Forty five samples of frozen meat (15 samples of each of minced red meat, chicken, and fish) were collected from different markets in Baghdad city. Molecular (RT-PCR) and culturing (conventional microbiological examination) methods were used to determine the level of contamination of L. monocytogenes in these types of meat.

For the culturing method, TSYEB broth was used as an enrichment medium, whereas BALCAM medium (HiMedia) with the listeria selective supplement FD061 was used as a selective medium, for the isolation and identification of this bacterium. The isolates were con