The subject of the Internet of Things is very important, especially at present, which is why it has attracted the attention of researchers and scientists due to its importance in human life. Through it, a person can do several things easily, accurately, and in an organized manner. The research addressed important topics, the most important of which are the concept of the Internet of Things, the history of its emergence and development, the reasons for its interest and importance, and its most prominent advantages and characteristics. The research sheds light on the structure of the Internet of Things, its structural components, and its most important components. The research dealt with the most important search engines in the Intern

This research investigates the subject of the impact of wars (as a manifestation of crisis) on architecture, and the extent of continuing wars physical and moral results of wars, even after the end of the cause of the crisis. The impact of different rebuilding which exposed to the effects of the war seems different in crisis regions.

The problem of research is about the uncertainty of the impact of the way chooses for reconstructing the buildings after wars in the continuity of the crisis of war. The goals of this research are to clarify the influence of methods of reconstruction of buildings in a city chosen which is Beirut, on the continuation of the war crisis with the argument of demolishing and rebuilding newly or keeping tr

The study was conducted to show the effect of using dried rumen powder as a source of animal protein in the diets of common carp (Cyprinus carpio L.) on its performance, in the fish laboratory/College of Agricultural Engineering Sciences/University of Baghdad/ for a period of 70 d, 70 fingerlings were used with an average starting weight of 30±3 g, with a live mass rate of 202±2 g, randomly distributed among five treatments, two replicates for each treatment and seven fish for each replicate. Five diets of almost identical protein content and different percentages of addition of dried rumen powder were added. 25% was added to treatment T2 and 50% to treatment T3 and 75% of the treatment T4 and 100% of the treatment T5

In this article the nanoparticles synthesis of ZnO (Nps) by using the precipitation method at concentrations range (0.5, 0.25, 0.125, 0.0625, 0.03125) mg/mL and then activity was examined against Streptococcus spp that causing dental caries in vitro by well diffusion method, find these concentrations effected in these bacteria and better concentration is 0.03125. ZnO Nps were characterization by EDS to prove this particles are ZnO, and also characterized by atomic force microscope (AFM), X-ray Diffraction (XRD) and TEM, from these technic found that the average size about 30.52 nm and hexagonal shape. The UV-visible result reveals that the large band is observed at 340.8 nm, Zeta potential show that the surface charge is 30.19 mv an

Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.