This work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m

This paper proposes and tests a computerized approach for constructing a 3D model of blood vessels from angiogram images. The approach is divided into two steps, image features extraction and solid model formation. In the first step, image morphological operations and post-processing techniques are used for extracting geometrical entities from the angiogram image. These entities are the middle curve and outer edges of the blood vessel, which are then passed to a computer-aided graphical system for the second phase of processing. The system has embedded programming capabilities and pre-programmed libraries for automating a sequence of events that are exploited to create a solid model of the blood vessel. The gradient of the middle c

The automatic liquid filling system is used in different applications such as production of detergents, liquid soaps, fruit juices, milk products, bottled water, etc. The automatic bottle filling system is highly expensive. Where, the common filling systems required to complex changes in hardware and software in order to modify volume of liquid. There are many important variables in the filling process such as volume of liquid, the filling time, etc. This paper presents a new approach to develop an automatic liquid filling system. The new proposed system consists of a conveyor subsystem, filling stations, and camera to detect the level of the liquid at any instant during the filling process. The camera can detect accurately the leve

     Diabetes is considered by the World Health Organization (WHO) as a main health problem globally. In recent years, the incidence of Type II diabetes mellitus was increased significantly due to metabolic disorders caused by malfunction in insulin secretion. It might result in various diseases, such as kidney failure, stroke, heart attacks, nerve damage, and damage in eye retina. Therefore, early diagnosis and classification of Type II diabetes is significant to help physician assessments.

The proposed model is based on Multilayer Neural Network using a dataset of Iraqi diabetes patients obtained from the Specialized Center for Endocrine Glands and Diabetes Diseases. The investigation includes 282 samples, o

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

     The conventional procedures of clustering algorithms are incapable of overcoming the difficulty of managing and analyzing the rapid growth of generated data from different sources. Using the concept of parallel clustering is one of the robust solutions to this problem. Apache Hadoop architecture is one of the assortment ecosystems that provide the capability to store and process the data in a distributed and parallel fashion. In this paper, a parallel model is designed to process the k-means clustering algorithm in the Apache Hadoop ecosystem by connecting three nodes, one is for server (name) nodes and the other two are for clients (data) nodes. The aim is to speed up the time of managing the massive sc

Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border