Background: Tumors of the oral cavity are under
estimated in general dental and medical practice,
some authors describe it as the forgetting disease,
others wondering if the attention paid to this disease
compared to its fatality (The 5-year survival rate is
about 50%) is enough for disease control? However;
this disease deserves a comprehensive assessment by
all dental and medical fields assumed to examine the
oral cavity regularly, especially otolaryngologist.
Objectives: To find out the sensitivity and specificity
of clinical examination in diagnosing oral tumors and
premalignant conditions by otolaryngologist.
Methods: Across sectional retrospective study was
conducted in the:
-study design:

In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

  This research aims to harmonize contemporary and traditional clothes, also expenses and savings. It is done by recycling evening clothes into Clothes with traditional features. The study followed descriptive explanatory approach. The sample consisted of seven dresses, as well as 208 female participants from Makkah Al-Mukarramah province, the age range was between 21 and 65 years old. An electronic questionnaire was distributed and the stability and reliability of the internal consistency were measured.
The research resulted in the ability to recycle evening dresses into modern clothes with traditional characteristics. It also confirmed that the reason of wearing traditional clothes is spirituality of the month of Ramadan. Addi

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Out of 180 children, 60 (33.3%) have Amoebiasis infection as diagnosed by direct wet smear and Saturated Salt Solution (SSS). SSS method is more significant (P=0.001) in diagnosis of the disease. Number of children infected with Amoebiasis infection is higher in infants aged 1-6 months, but without any significant difference to ages 6-12 or 12-18 months. In contrast, infants aged 18-24 months are significantly differant (P=0.01) as the infection rate is 16.6%. Gender also is seen to be reduced in significance (P= 0.001) for females aged 18-24 months. Blood profile of the involved infants has shown a significant variation (P=0. 01) for all blood profile parameters (RBC (P=0.05), WBC (P=0.001), Lymphocytes (P=0.05), Granulated WBC (P=0.05),

This research examines the factors which influence pedestrian's walking speed in Baghdad. the variations in walking speed of pedestrians are related to pedestrian characteristics such as gender, age group, and clothing traditions. Using the established methodology, the counts of pedestrians were performed using manual and video counting. The case study was performed in two streets located in a highly crowded commercial zone at the city center of Baghdad: Al-Karada Dakhel and Al- Sina’a Street. Data were subjected to statistical analysis using IBM SPSS Statistics 19 software. It has been found that Iraqi pedestrians walk slower than other pedestrians in the developed countries or in the region with minimum walking speed of 29.85 m/min.

A water crisis is a circumstance in which a region accessible potable, unpolluted water is less than the requirement of that country. Two converging trends cause water scarcity, that are expanded use of irrigation, and loss of available freshwater supplies. Water scarcity can arise from two mechanisms, the physical water scarcity because of deficient natural water supply to fulfil the country demand, and economic water scarcity due to bad management for sufficient available water resources. This research examines data set as multispectral Landsat 8 satellite images that are detected for Basrah city, located in southern Iraq, and positioned between Kuwait and Iran on the Shatt al-Arab. Such raw data are satellite images. Using ENVI 5.3 softw