رسل محمد حسون الخفاجي

Social media provided a successful management of human societies in light of global crises. Social media platforms have been considered the central authority in guiding society, receiving information and conducting business in many countries during the COVID-19 pandemic period in March 2020. The social platform has seen an increase in use of 45% for public platforms and 35% for the use of messages. This study suggests An AI-based model for predicting the likelihood of infection with COVID-19 through sentiment analysis and early detection using a Natural Language Processing library with deep learning techniques CNN. The model performed improved the distinction between patients who are 'positive' and patients who are 'natural' and unaffected are 'negative'. The performance of the model was tested using publicly available databases on Twitter for the period from March 16, 2020 to April 14, 2020.The achieved accuracy percentage was (~99.8% )) and based on the four measures Accuracy, Recall, Precision and F1-score.

Environmental improvement steps are important factors in relation to technological progress in the world, and it is considered one of the fierce enemies of the environment, one of its tools is carbon dioxide (CO2) emissions as it is an indicator of environmental pollution with its high rates in the atmosphere, and predicting its emissions and future expectations contribute greatly to drawing up a sustainable environmental policy. On this basis, this study used one of the most important artificial intelligence (AI) tools, which is the multilayer nonlinear autoregressive exogenous model (ML-NARX), to predict and forecast annual CO2 emissions and their quantities in Iraq until 2032. The measured CO2 emissions data were collected for the purpose of studying from the «Our World in Data» website from 1950 to 2022 because some previous measurements were missing, as the database consisted of 73 samples that were divided into a training set, a test set, and a validation set at a ratio of 70:15:15, respectively. The proposed model was designed to consist of two hidden layers and the effect of modifying the number of nodes in each of the two hidden layers on the accuracy of the prediction was studied. As for the inputs used, one set was formed to predict the next value from the past value based on the time sequence of CO2 emission years. Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) were adopted as performance measures in evaluating the model, as the network was trained to reach the lowest value of MSE and RMSE which were 6.46E-04 and 2.54E-02 respectively, and the best structure used for the model was determined to be (10) nodes in first layer and (25) nodes in second layer. The output of the model's prediction curve for ten years for CO2 emission for the period from 2023 to 2032 showed an increase at a rate of 1.7820 million tons/year. Therefore, the results of this work will help local government and decision-makers to take the necessary and wise measures to address the environmental reality for the near and distant future as well.

The study of radioactive nuclei concentrations in soils is a very important topic due to the contribution of some factors in increasing these concentrations. Where the nucleus transition to food and then the human and endanger his life. Where taken 15 samples of soils from Al Rahmah district, where a gamma-ray spectrometer system connected with the NaI(TI) detector was used to measure the specific activity of the 226Ra, 232Th and 40K nuclei, the specific activity values were varied from (0.526 -5.385) Bq.kg-1 with mean (2.193 Bq.kg-1) for 226Ra,(0.56 -5.29) Bq.kg-1 with average (2.95 Bq.kg-1) for 232Th and (209.239-990.387) Bq.kg-1 with mean (598.714 Bq.kg-1) for 40K, respectively. Specific activity values showed that there was only a significant increase in 40K concentrations, while that the difference between the rate of Thorium and Radium concentrations was little .External and internal hazard indices, outdoor and indoor absorbed doses and Radium equivalent activity and total annual effective dose which were below the internationally recommended limits. The excess life-time cancer risk (ELCR) was ( 0.717*10-3 ) which compare with the worldwide value(1.45*10-3), this is the first study in this region and can be considered as a baseline for future studies in this region.

Eleven samples of salt were collected from local markets in Iraq for the purpose of identifying which types were more radioactive and the radiation efficacy of the external hazard index, outdoor absorbent dose, internal hazard index and indoor absorbed dose and Radium equivalent activity (Raeq) also finding an effective dose due to ingestion where the maximum value of a specific uranium activity was recorded in sample S4, which was (32.138Bq/kg). The lowest value was recorded in sample S8, which was (4.432 Bq/kg). It should be noted that sample S8 is Turkish origin specific activity of 232Th, the highest value was (12.456Bq/kg) recorded in sample S9, while the lowest value was (1.426 Bq/kg) and recorded in sample S7. Also calculate Effective dose Dose(Sv/y) by using equation (7) for 40K was 10.088 Sv/y , 226Ra was 1.152 Sv/y and 232Th was 1.660 Sv/y.