Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c

     Plagiarism is described as using someone else's ideas or work without their permission. Using lexical and semantic text similarity notions, this paper presents a plagiarism detection system for examining suspicious texts against available sources on the Web. The user can upload suspicious files in pdf or docx formats. The system will search three popular search engines for the source text (Google, Bing, and Yahoo) and try to identify the top five results for each search engine on the first retrieved page. The corpus is made up of the downloaded files and scraped web page text of the search engines' results. The corpus text and suspicious documents will then be encoded as vectors. For lexical plagiarism detection, the system will

Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

Foreground object detection is one of the major important tasks in the field of computer vision which attempt to discover important objects in still image or image sequences or locate related targets from the scene. Foreground objects detection is very important for several approaches like object recognition, surveillance, image annotation, and image retrieval, etc. In this work, a proposed method has been presented for detection and separation foreground object from image or video in both of moving and stable targets. Comparisons with general foreground detectors such as background subtraction techniques our approach are able to detect important target for case the target is moving or not and can separate foreground object with high det

Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

In this rescrch,new mixed ligand Schiff base complexes of Mn(II),Co(II),Ni(II),Cu(II), Cd(II), and Hg(II) are formulated from the Schiff base( L)resulting from  o-phathalaldehyde(o-PA) with p-nitroaniline(p-NA)as a primary ligand and anthranilic acid as a subordinate ligand. Diagnosis of prepared Ligand and its complexes is done by spectral methods mass spectrometer;1H -NMR for ligand Schiff base FTIR, UV-Vis, molar conductance, elemental microanalyses, atomic absoption and magnetic susceptibility. The analytical studies for the all new complexes have shown octahedral geometries. The study of organicperformance  of ligand Schiff base and its complexes show various activity agansit four type of bactria two gram (+) and two gram (-) .

On the basis of known coumarin-based prodrug system, a novel coumarin-based mutual prodrug of 5-fluorouracil and dichloroacetic acid was designed, synthesized and evaluated as a promising oral chemotherapeutic agent basing on in vitro stability study in HCl buffer (pH 1.2) and in phosphate buffer (pH 7.4), as well as in vitro release study in human serum. The chemical structure of prodrug was confirmed by analyzing its FTIR, ¹H NMR, ¹³C NMR and MS-ESI spectra. The results of in vitro kinetic study indicated that the prodrug was significantly stable in HCl and in phosphate buffers, and was hydrolyzed in human serum followed pseudo first order kinetics.

Keywords: Coumarin-bas