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

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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

NiO nanoparticle synthesis by chemical method and characterized by XRD with crystal size 11.72
nm and grain size 13 nm from FESEM image also NiO micro used ,two NiO as an additive to evaluate the
possibility of producing photodegradable polymers, the practical application of solid-phase photocatalytic
degradation of polyvinyl chloride (PVC- NiO composite films) was investigated. PVC has a negative impact
on the environment since its polymer degrades slowly, yet it has a wide range of industrial applications and
the amount used shows no evidence of diminishing use. Thus, a synthesis of modified PVC- NiO micro and
nano has been studied with 0, 50, 100, 150, 200, 250, and 300 (hours) as irradiation time a

Visceral leishmaniasis is a neglected tropical disease on the rise in different regions of Iraq, especially in areas with poor hygiene and among refugee populations. The effectiveness of existing chemotherapy for leishmaniasis is constrained by its high toxicity, cost, and the development of drug resistance. The current research examined various concentrations (ranging from 125 to 1000 μM) of lupeol to evaluate its ability to boost the generation of nitric oxide, which has anti-leishmanial properties, in an ex-vivo macrophage model. Griess assay was used to detect the nitric oxide (NO) production in Leishmania donovani infected U937 cell-line macrophages along 24 and 48 hours post treated. The nitric oxide concentration was signifi

This study include design and synthesis of 2 derivatives of compounds consisting of mefenamic acid, glycine and organic nitrates (2-nitrooxy ethanol or 1,3-dinitrooxy-2-propanol). Nitric oxide NO has been reported to support many of the same mucosal protection mechanisms as prostaglandins and is sufficient for acute gastroprotection and ulcer healing. So we suppose these 2 compounds would reduce non-steroidal anti-inflammatory drugs NSAIDs gastrointestinal side effect.

Key words: Non-Steroidal anti-inflammatory dr

In this study, pure Co3O4 nano structure and doping with 4 %, and
6 % of Yttrium is successfully synthesized by hydrothermal method.
The XRD examination, optical, electrical and photo sensing
properties have been studied for pure and doped Co3O4 thin films.
The X-ray diffraction (XRD) analysis shows that all films are
polycrystalline in nature, having cubic structure.
The optical properties indication that the optical energy gap follows
allowed direct electronic transition calculated using Tauc equation
and it increases for doped Co3O4. The photo sensing properties of
thin films are studied as a function of time at different wavelengths to
find the sensitivity for these lights.
High photo sensitivity dope