Spergularia iraqensis sp. nov. is described as a new species from Iraq. This species has been collected from Diyala Province in the central east of Iraq; it is closely related to Spergularia rubra (L.) J. Presl & C. Presl, 1819 and Spergularia bocconei (Scheele) Graebn., 1919.
The distinguishing of the morphological characteristics of the new species alongside the two similar species are discussed with photographs, and an identification key is given for Spergularia iraqensis and other closely related species.
Modern communication and media technology has pioneered new horizons and curried out deep changes in the various fields of social life, It effected enormously human communication as well.
Content one Who late the developments which have effected the social relations ،due to the new media ،especially Face book ,will certainly notice the far cry changes of the social relation net which has been effected ,in a way or another ،the accelerated development ،under the appearance of the so called the virtual society .
Face book has embodied the means – communication ,which has become an important turn point in the social communication .
It is the point the present paper tries to expose an discuss by a field study curried on a sam
The mucilage was isolated from mustard seeds and identification by some different methods like, thermo gravimetric, FTlR., X-ray powdered, proton NMR, FTIR spectra of the three gums contain different functional group in the gums, major peaks bands noticed were belong to OH (3410.15 – 3010.88) group from hydroxyl group, CH aliphatic (2925-2343.51), C-O (1072.42-1060.85) group and C=O 1743.65, Thermo chemical parameters of mucilage was evaluated and compared with the standard gums, Results indicated the mucilage was decomposed in 392°C and mass loss 55%, The X ray process found the mucilage had single not sharp peak
... Show MoreWith the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
... Show MoreThe current research was ataxonomic study for the species Pyrus pyraster L. that belong to the subfamily Pomoideae from the family Rosaceae which growing wildely in Iraqi Kurdistan .The macro and micro morphology and pollen grain were studied .A wide field servay for the districts of Iraqi Kurdistan was done . According to the taxonomic references adetail study for the morphology of the leaves ,color of the corolla,calyx , the fruits diameters, color and shapes,also the seed were studied From the study of pollen grains it appeared that the pollen grains areTricolporate ,their shape in the Equatorial view was ovoid but in the pollar view they are triangular. The species Pyrus pyraster L.was recor
... Show MoreThe CdS quantum dots were prepared by chemical reaction
of cadmium oleylamine (Cd –oleylamine complex) with the
sulfite-oleylamine (S-oleylamine) with 1:6 mole ratios. The
optical properties structure and spectroscopy of the product
quantum dot were studied. The results show the dependence of the
optical properties on the crystal dimension and the formation of
the trap states in the energy band gap.
The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed
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