In this paper solar radiation was studied over the Iraqi countary land. The best sun duration hours regions (maximum hours) in Iraq were estimated detected by using Geographic information system (GIS Ver. 9.2) program to apply the (Inverse distance weighting) IDW exact interpolation technique depending on the measured data of metrological stations were distributed on the land areas of Iraq. The total area of the best regions was calculated .Excel 2007 program is used in calculation, graphics and comparison the results.

Diyala Governorate has many unique and diverse geomorphological features that the region enjoys, which are among the attractions for natural tourism, as the natural environment is considered a maker of tourism. The importance of geomorphological aspects as components of natural tourism is due to their association with tourism and entertainment, as a result of the enjoyment of many geomorphological aspects of the beauty of its natural landscape on the one hand, and on the other hand, the association of these manifestations with different types of tourism activity. Any tourist area as it is the main factor for tourist attractions, such as the presence of the Hamrin hills, and sand dunes. Planning for the development of tourism activity in the

Ebastine (EBS) is a poorly water-soluble antihistaminic drug; it belongs to the class II group according to the biopharmaceutical classification system (BCS). The aim of the present work was to enhance the solubility, dissolution rate and micromeritic properties of the drug, by formulating it as spherical crystal agglomerates by Quasi Emulsion Solvent Diffusion (QESD) method.

Spherical crystal agglomerates (SCAs) were prepared in presence of three solvents dichloromethane (DCM), water and chloroform as a good solvent, poor solvent and bridging solvent respectively.  Agglomeration of EBS involved the use of some hydrophilic polymers like polyethylene glycol 4000 (PEG 4000), polyvinyl pyrrolidine K30 (PVP K30), D-?-tocopheryl

Titanium dioxide nanotubes were synthesized by anodizing Ti sheets in the ethylene glycol solution and were covered in Pt nanoparticles onto the surface of TiO₂NTs using electrodeposition method from using five derivatives of Mannich base Pt complexes which have been used as precursor of platinum. The mean size, shape, elemental composition of the titanium dioxide nanotubes and platinum deposited on the template were evaluated by different techniques such as field emission scanning electron microscope (FE-SEM), transmission electron microscopy (TEM), X-ray diffraction pattern (XRD), and energy dispersive X-ray (EDX) technique. From all these analyses, the TiO₂NTs prepared and Ptnanoparticles deposited on it were ide

Aim: The present study aims to improve the poor water solubility of zaltoprofen which is a non-steroidal anti-inflammatory drug (NSAIDs) with a potent analgesic effect using solid dispersion then formulate it as a hollow type suppository to be more convenient for geriatric patients. Materials and Method: Zaltoprofen solid dispersions were prepared by solvent evaporation technique in different zaltoprofen: Soluplus® ratios. Results: Among the formulations tested, zaltoprofen solid dispersion preparation using 1:5 (zaltoprofen: Soluplus®) ratio showed the highest solubility and selected for further investigation. Solid dispersion characterization was evaluated by differential scanning calorimetry (DSC), X-ray diffraction study (XRD) and Fou

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

   This research studies the rheological properties ( plastic viscosity, yield point and apparent viscosity) of Non-Newtonian fluids under the effect of temperature using different chemical additives, such as (xanthan gum (xc-polymer), carboxyl methyl cellulose ( High and low viscosity ) ,polyacrylamide, polyvinyl alcohol, starch, Quebracho and Chrome Lignosulfonate). The samples were prepared by mixing 22.5g of bentonite with 350 ml of water and adding the additives in four different concentrations (3, 6, 9, 13) g by using Hamilton Beach mixer. The rheological properties of prepared samples were measured by using Fan viscometer model 8-speeds. All the samples were subjected to Bingham plastic model. The temperature range studi