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

Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

Recently emerging pandemic SARS CoV-2 conquered our world since December 2019. Continuous efforts have been done to find out effective immunization and precise treatment stetratigies A way from therapeutic options that were tried in SARS CoV-2, an increased attention is directed to predict natural products and mainly phytochemicals as collaborative measures for this crisis. In this review, most of the mentioned compounds specially flavonoids (biacalin, hesperidin, quercetin, luteolin,, and phenolic (resveratrol, curcumin, and theaflavin) exert their effect through interfering with the action of one or more of this proteins (spike protein, papain like protease, 3 chymotrypsin like cysteine protease, and RNA dependent RNA 

Background: Chronic periodontitis is an inflammatory disease of tissues supporting the teeth. Salivary compositions have been most intensely studied as a potential marker for periodontal disease. In this study, analysis of saliva provides a simple and non-invasive method of evaluating the role of salivary IgA (s-IgA) levels in periodontal disease by detecting the level of (s-IgA) in patients with chronic periodontitis smokers and non smokers patients and correlate the mean (s-IgA) levels with clinical periodontal parameters Plaque index (PLI) gingival index (GI), probing pocket depth (PPD) and clinical attachment level (CAL). Materials and Methods: The study samples consists of (15) patients with chronic periodontitis who were non smokers (

Objective: The study aims to determine the effect of Toxoplasma gondii infection on the
genetic sequence of breast cancer patients in the Medical City Hospital – Tumor Unit /
Iraq-Baghdad.
Methodology: A study was carried out in the City of Medicine / Oncology Unit / Baghdad,
during the period 1st June 2016 to 15
th March 2017. Forty samples of tissue and serum
were collected from patients who complaining from Breast cancer and infected with
Toxoplasmosis. Forty sera samples were taken from patients complaining from parasitic
infection only; without breast cancer as control group. Data is analyzed by using of
descriptive and inferential data analysis methods.
Results: The results show that there is an effe

The research problem can be summarized through focusing on the environment that surrounds students and class congestion, how these factors affect directly or indirectly the academic achievement of students, how these factors affect understanding the scientific material that the student receives in this physical environment, how classroom’s components such as seats, space With which the student can move, the number of students in the same class,  the lighting, whether natural or artificial, and is this lighting sufficient or not enough, the nature of the wall paint old or modern, is it comfortable for sight, the blackboard if it is Good or exhausted,  In addition to air-conditioning sets in summer and winter, this is on the on