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

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.

The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

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

As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,

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.

            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

In this work, the preparation of new multidentate Schiff-base lig and and its metal complexes are described. The formation of the lig and{ 2,2`((5-methyl-1,3-phenylene)-bis-(oxy))-bis-N`(E`)-2- hydroxybenzylideneacetohydrazide}[H2L] was prepared from the reaction {2,2-((5-methyl-1,3-phenylene)-bis-(oxy))- di-(acetohydrazide)}[M]precursor and salicylaldehyde in a 1:2 mole ratio, respectively. The reaction of the lig and [H2L] with (Cr+3 , Mn+2 and Fe+2 )metal ions in a 1:2 (L:M) mole ratio. Ligand and complexes were characterised via spectroscopic analyses; [FT-IR, UV-Vis spectroscopy,(C.H.N) microanalysis, chloride content, thermal analysis(TG), electrospray mass, magnetic susceptibility and conductivity measurements. The characterisation d

The Paleocene benthic foraminiferal zonation of the Umm Er Rhadhuma Formation from the borehole (K.H 12/7), South Anah City (Western Iraq), has been re-studied and re-analyzed precisely based on the large benthic foraminifera (LBF). They are represented by two biozone Rotorbinella hensoni Partial Range Zone, recorded from the Lower and middle parts of the Umm Er Rhadhuma Formation and Lockhartia praehaimei Partial Range Zone determined Uppermost of this unit, and dated to be the Selandian – Thanetian stage. Almost all the biogenic (micro and macro) and non-biogenic constituents, including large benthic foraminifera, Algae, Echinoderm, Bryozoans, Oyster, Gastropod fragments, and peloids, in addition to lithofacies types, indicate t

Commercial graphite (CGT) powder was used as an adsorbent surface for cationic dye, Janus green (JG), from aqueous solutions. This study aims to highlight the practical significance of using inexpensive CGT as an efficient adsorbent for the removal of JG dye from industrial wastewater. CGT was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and X-ray diffraction. The adsorption process was investigated by examining parameters like the weight of the adsorbent, contact time, and temperature. Pseudo-second-order kinetic (PSO), pseudo-first-order, and intraparticle diffusion were used for analyzing the kinetic data. JG dye's adsorption kinetics fit the PSO kinetic model well (R2= 0.999). Furthermo