Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

God Almighty put in his great book secrets that do not end, and wonders that do not expire, for he is the one from which the scholars are not satisfied, and he does not create due to the multitude of response, and it is the comprehensive and inhibitory book that God conceals to the worlds, and he challenged the two heavyweights to come up with something like it.

At all times, issues arise in the Noble Qur’an that fit the needs of the people of that time and their culture, for it is an eternal book, characterized by the ability to give, extend and respond to addressing the problems of the age and its variables, when the Arabs had little luck at the time of the message’s descent from the scientific culture, and their proficienc

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

Extractive multi-document text summarization – a summarization with the aim of removing redundant information in a document collection while preserving its salient sentences – has recently enjoyed a large interest in proposing automatic models. This paper proposes an extractive multi-document text summarization model based on genetic algorithm (GA). First, the problem is modeled as a discrete optimization problem and a specific fitness function is designed to effectively cope with the proposed model. Then, a binary-encoded representation together with a heuristic mutation and a local repair operators are proposed to characterize the adopted GA. Experiments are applied to ten topics from Document Understanding Conference DUC2002 datas

The aim of this study is to design a proposed model for a document to insure the mistakes of the medical profession in estimating the compensation for medical errors. The medical profession is an honest profession aimed primarily at serving human and human beings. In this case, the doctor may be subject to error and error , And the research has adopted the descriptive approach and the research reached several conclusions, the most prominent of which is no one to bear the responsibility of medical error, although the responsibility shared and the doctor contributes to them, doctors do not deal with patients according to their educational level and cultural and there are some doctors do not inform patients The absence of a document to insu

 Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The

Abstract:

The aim of the research is to demonstrate the impact of the professional specialization of the audit companies in the detection of fraud in the financial statements of the economic units listed in the Iraqi market for securities for the period 2014-2015 through the application of the model (Carcello) to test the hypothesis of research on the impact of professional specialization of audit companies in the detection of fraud in lists The effect of the variables was revealed through the use of statistical models of logistic regression model and correlation coefficient. After testing the hypotheses of the research, a number of conclusions were reached. The most important was the existence of a signi

Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump