The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

Back ground: Diabetic nephropathy is rapidly becoming the leading cause of end-stage renal disease (ESRD). The onset and course of DN can be ameliorated to a very significant degree if intervention institutes at a point very early in the course of the development of this complication.
Objective: The aim of this study was to characterize risk factors associated with nephropathy in type I diabetes and construct a module for early prediction of diabetic nephropathy (DN) by analyzing their risk factors.
Methods: Case control design of 400 patients with type I diabetes mellitus (IDDM), aged 19-45 years. The cases were 200 diabetic patients with overt protein urea while the controls were 200 diabetic patients with no protein urea or micr

Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recogn

An idiom is a group of words whose meaning put together is different from the meaning of
individual words. English is a rich language when it comes to idioms, they represent variety. For
foreign learners, idioms are problematic because even if they know the meaning of individual
words that compose an idiom the meaning of it might be something completely different.
The present study investigates Iraqi third year college students’ recognition of idioms. To
achieve this, the researchers have conducted a test which comprises three questions. Certain
conclusions are reached here along with some suggestions and recommendations.

Purpose: To identify the size of the food gap for the main agricultural products and crops in Iraq, which reflects to us the extent to which agricultural production in particular and the agricultural sector in general have declined.Theoretical framework: The theoretical side of the research dealt with the definition of self-sufficiency and the food gap, as well as identifying the reality of agricultural production in Iraq during the study period, as well as the reality of the food gap for the most important agricultural, plant and animal products.Design/methodology/approach: In reviewing the research problem, the researcher adopted the method of deductive and descriptive analysis based on the presentation and detail of official data

The research deals with the subject of «ways to face rumors in the site of social networking Facebook», a research based on a doctoral thesis, as the research dealt with rumors in the most dangerous type of new media, which sites of social communication with the global community as spreading rumors of all kinds and afflicts everyone who has eyes on him Of the audience of these sites, and aims to identify the rumors on Facebook because it is one of the most popular sites in the world and the strategy of combating the rumors published by Facebook users in their personal pages and groups that organize them, as well as identify methods and methods that can be During which the face of the rumors in the said site and eliminate them t