In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di

          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

Cryptography is a major concern in communication systems. IoE technology is a new trend of smart systems based on various constrained devices. Lightweight cryptographic algorithms are mainly solved the most security concern of constrained devices and IoE systems. On the other hand, most lightweight algorithms are suffering from the trade-off between complexity and performance. Moreover, the strength of the cryptosystems, including the speed of the algorithm and the complexity of the system against the cryptanalysis. A chaotic system is based on nonlinear dynamic equations that are sensitive to initial conditions and produce high randomness which is a good choice for cryptosystems. In this work, we proposed a new five-dimensional of a chaoti

Biometrics is widely used with security systems nowadays; each biometric modality can be useful and has distinctive properties that provide uniqueness and ambiguity for security systems especially in communication and network technologies. This paper is about using biometric features of fingerprint, which is called (minutiae) to cipher a text message and ensure safe arrival of data at receiver end. The classical cryptosystems (Caesar, Vigenère, etc.) became obsolete methods for encryption because of the high-performance machines which focusing on repetition of the key in their attacks to break the cipher. Several Researchers of cryptography give efforts to modify and develop Vigenère cipher by enhancing its weaknesses.

Type 2 diabetes mellitus(T2DM) is a metabolic disease that is associated with an increased risk for atherosclerosis by 2-4 folds than in non- diabetics. In general population, low IGF-1 has been associated with higher prevalence of cardiovascular disease and mortality .This study aims to find out the relationship between IGF-1 level and other biochemical markers such as Homeostasis Model Assessment insulin resistance(HOMAIR) and Body Mass Index(BMI) in type 2 diabetic patients . This study includes (82) patients (40 females and 42 males) with age range (40-75) years,(34) non obese diabetic patients and (48) obese diabetic patients. The non obese individuals considered

Enterococci species (spp.) are naturally found in the gastrointestinal tract (GIT), oral cavity of both human and animals causing several infections including bacteremia, meningitis, endocarditis, intra-abdominal infections, wound infections, urinary tract infections (UTI), atherosclerosis and play a critical role in the riskiness or development of periodontitis, particularly in a suitable mouth environment (Comerlato et al., 2020; Mendes et al., 2020; Xiong et al., 2021; H Elaywe, 2007). Recurrent and continues antimicrobial resistance (AMR) of opportunistic microorganisms is one of the serious public health risk, enterococci spp are often intrinsic resistant to antibiotics class routinly used in treatment such as Cephalosporins, Macrolids