Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Background: Squamous cell carcinoma is a disease of elderly peopleand it is uncommon in people with less than 40 years old; however many literatures revealed that tumor developing in patients younger than forty years appears more aggressive at the time of diagnosis. The purpose of the present study was to focus on the clincopathological features of the oral SCC in different age groups. Material and methods: In this study thirty five cases of paraffin embedded tissue blocks of oral squamous cell carcinoma were studied. The age range was from 16 to 80 years. The clinicopathological data were recorded for evaluating the tumor characters according to age of patients. Results : The age was not significantly correlated to the clinicopathological

   The modified Hummers method was applied to prepare graphene oxide (GO) from the graphite powder. Tin oxide nanoparticles with different loading (10-20 wt.%) supported on reduced graphene oxide were synthesized to evaluate the oxidative desulfurization efficiency. The catalyst was synthesized by the incipient wetness impregnation (IWI) technique. Different analysis methods like FT-IR, XRD, FESEM, AFM, and Brunauer-Emmett-Teller (BET) were utilized to characterize graphene oxide and catalysts. The XRD analysis showed that the average crystal size of graphene oxide was 6.05 nm. In addition, the FESEM results showed high metal oxide dispersions on the rGO. The EDX analysis shows the weight ratio of Sn is close to its theoretical weight.

Background: Doxorubicin is considered one of the most effective anticancer drugs, yet it is use is limited by its side effect mediated by the generation of reactive oxygen species. Omega-7, an antioxidant has shown to have a cardioprotective effect.

Aim of the study: evaluate a possible protective effect of omega-7 against doxorubicin-induced cardiotoxicity in male rats.

Methods: twenty-eight male rats were divided into 4 groups (7 for each group).  Group 1 (Negative control): healthy animals received normal saline orally as the vehicle for eight successive days and were sacrificed on day 9. Group 2 (positive control): animals that r