Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

This study aimed to identify the changes in total protein in saliva and sera samples of patients with oral squamous cell carcinoma in comparison to those of healthy controls. These changes were followed using electrophoresis (PAGE). Meanwhile, determinations of albumin, globulin and albumin to globulin ratio were carried out on sera samples only.Two groups were the participants in the present study, 18 patients with Oral Squamous Cell Carcinoma (OSCC), and 20 ages and gender matched healthy controls.

This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

Background: The evaluation and staging of renal cell carcinoma (RCC) has dramatically changed with the introduction of cross-sectional imaging. Nowadays, small renal lesions are easily detected by computed tomography (CT) examination while missed by other modalities.

Objective: To determine whether ultrasound (US) or CT scan is the optimum imaging modality for the evaluation of the renal masses.

Patients and methods: This is a comparative study in which 30 patients with hematuria were attending the urological consulting clinic in Ghazzi Al-Harriry hospital, Baghdad, Iraq from May 2016 to July 2017 were subjected to abdominal US and CT scan.

Results:

The study aimed to evaluate educational programs efficiency in applying the best educational practices to educate students from the dangers of indecent behaviors, in line with higher education policy and the appropriateness of educational program dimensions to spread awareness among students to not fall into the indecent behaviors clutches. The study adopted the inductive exploratory approach through structural equation modeling and the descriptive analysis of the collected data from randomly selected sample (n=385) from educational academics at Northern Border University in the Saudi Arabia using a specially designed survey tool to meet study purposes to evaluate dimensions of teaching methods, evaluation tools, training courses, course

Background: Tumor associated tissue eosinophilia (TATE) has been described in a variety of neoplasms. In regard to squamous cell carcinoma, some studies worldwide done to assess stromal eosinophilia in oral and cervical squamous cell carcinoma. The objectives of this study is to evaluate the association of stromal eosinophilic infiltration of cutaneous squamous cell carcinoma and to detect the significance of this association.

Aim of the study

The aim of our study is to establish the relationship between the degree of stromal eosinophilia and the level of invasion and the histological grade in cutaneous squamous cell carcinoma.

Methods: In this retrospective study

Background: Tumor associated tissue eosinophilia (TATE) has been described in a variety of neoplasms. In regard to squamous cell carcinoma, some studies worldwide done to assess stromal eosinophilia in oral and cervical squamous cell carcinoma. The objectives of this study is to evaluate the association of stromal eosinophilic infiltration of cutaneous squamous cell carcinoma and to detect the significance of this association. Aim of the study The aim of our study is to establish the relationship between the degree of stromal eosinophilia and the level of invasion and the histological grade in cutaneous squamous cell carcinoma. Methods: In this retrospective study done at the histopathology department of al Wasity teaching hospital for orth