In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

Currently, with the huge increase in modern communication and network applications, the speed of transformation and storing data in compact forms are pressing issues. Daily an enormous amount of images are stored and shared among people every moment, especially in the social media realm, but unfortunately, even with these marvelous applications, the limited size of sent data is still the main restriction's, where essentially all these applications utilized the well-known Joint Photographic Experts Group (JPEG) standard techniques, in the same way, the need for construction of universally accepted standard compression systems urgently required to play a key role in the immense revolution. This review is concerned with Different

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.

Objectives: To explore the correlation between maternal and cord blood prolactin, the correlation between cord prolactin and birth weight, and to compare cord blood prolactin in new-borns of women with normal pregnancy and women with pregnancy complications namely; gestational hypertension, gestational diabetes and preterm labour.Methods: This study was performed from September to December 2018. Thirty-two women, delivered at Baghdad teaching hospital, and their newborns (32) were included. Maternal blood (5 ml) was taken before labour and cord blood (5 ml) was collected after placenta expulsion. Maternal and cord blood prolactin were analysed using fluorescence immunoassay. Results: Cord blood prolactin was higher in babies b

Background: disturbed physiological rhythm of blood pressure in preeclampsia is a common finding. The role of oxidative stress in pathogenesis of preeclampsia is well accepted. Melatonin is a powerful free radical scavenger so it's rapidly consumed by enhanced reactive oxygen species in preeclampsia causing non-dipping in blood pressure.Objective: To evaluate the change in plasma melatonin levels in patients with preeclampsia and its relationship with blood pressure.Patients and methods: In this prospective case control study a total of 40 primigravidae pregnant women were recruited during the period of 11 months between August 2015 and August 2016 in Baghdad teaching hospital, medical city, Iraq, divided into two groups:First group