Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signa

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Dans le roman moderne, le type du héros est depuis longtemps devenu suspect.  Il risque même de disparaitre dans ce qu´on désigne le Nouveau Roman qui, se concentrant plutôt sur les objets, décrits minutieusement, refuse la fonction épistémologique traditionnelle de la littérature. Cette conception se manifeste, sur le plan formel, par certains traits typiques, comme la relativisation des points de vue, la décomposition de l´action, la destruction du temps, la décomposition de l´espace et la désintégration du personnage romanesque dont les liens avec la société sont coupés.

Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota

Background: Diabetes is a metabolic disorder characterized by chronic hyperglycemia due to an inability to produce insulin. Uncontrolled or poorly controlled diabetes is clinically associated with increased susceptibility to delay healing. Many recent researches have shown that stem cell therapy can be the best choice for treatment of this disease. The aims of this research were investigating regeneration of pancreatic beta cells of diabetic induced rabbits after stem cell transplantation. Materials and Methods: 64 rabbits weighting an average of (2.5 - 3 kg) were used in this experimental study, and divided into 4 groups as follows; group A ( contains 16 healthy rabbits regarded as control group ) , Group B ( contains 16 diabetic rabbits

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

Background: Dimensional changes of acrylic denture bases after polymerization results in need for further adjustments or even ends with technical failure of the finished dentures. The purpose of this study was to estimate the linear dimensional changes for different palatal depths when using multiple investment materials and polymerization techniques. Materials and methods: Ninety upper complete denture bases were constructed for this study. They were divided into two main groups according to the polymerization methods: conventional water bath and experimental autoclave (short and long cycles). Each main group was further subdivided into three subgroups according to the palatal depth (shallow, medium and deep). Furthermore, for each palatal