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In the beginning of 21st Century, Social Media developed and influenced on all aspects of modern lifestyle. Nowadays, Social Media is not only an entertainment and social networking tool, but also can be supposed as a way of linking different businesses, marketing, management, construction industry. Furthermore, it provides a framework for people around the world to interconnect, share information, and interrelate with each other. This study includes an investigation about the effects of Social Media on engineering related tasks, for this purpose, a questionnaire survey was performed for engineers with different gender, ages, and engineering status. Kurdistan Region-Iraq is the case study of this survey, the results of this study reveal that Social Media is one of the mostly used by engineers. It is also illustrated that Google, YouTube and Facebook are the mostly used platforms.

Reliable and precise estimation of solar energy as one of the green, clean, renewable and inexhaustible types of energies can play a vital role in energy management, especially in developing countries. Also, solar energy has less impact on the earth’s atmosphere and environment and can help to lessen the negative effects of climate change by lowering the level of emissions of greenhouse gas. This study developed thirteen different artificial intelligence models, including multivariate adaptive regression splines (MARS), extreme learning machine (ELM), Kernel extreme learning machine (KELM), online sequential extreme learning machine (OSELM), optimally pruned extreme learning machine (OPELM), outlier robust extreme learning machine (ORELM), deep extreme learning machine (DELM), and their versions combined with variational mode decomposition (VMD) as integrated models (VMD-DELM, VMD-ORELM, VMD-OPELM, VMD-OSELM, VMD-KELM, and VMD-ELM), for solar radiation estimation in Kurdistan region, Iraq. The daily meteorological data from 2017 to 2018 were used to implement suggested artificial models at Darbandikhan and Dukan stations, Iraq. The input parameters included daily data for maximum temperature (MAXTEMP), minimum temperature (MINTEMP), maximum relative humidity (MAXRH), minimum relative humidity (MINRH), sunshine duration (SUNDUR), wind speed (WINSPD), evaporation (EVAP), and cloud cover (CLOUDCOV). The results show that the proposed VMD-DELM algorithm considerably enhanced the simulation accuracy of standalone models’ daily solar radiation prediction, with average improvement in terms of RMSE of 13.3%, 20.36%, 25.1%, 27.1%, 34.17%, 38.64%, and 48.25% for Darbandikhan station and 5.22%, 10.01%, 10.26%, 21.01%, 29.7%, 35.8%, and 40.33% for Dukan station, respectively. The outcomes of this study reveal that the VMD-DELM two-stage model performed superiorly to the other approaches in predicting daily solar radiation by considering climatic predictors at both stations.

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Environmental problems can be the public’s concern, and they also feel the ratio of dangerousness. Consequently, collecting their opinions and trying to get to know the way of their thinking regarding their environmental problem and solving them was an attractive case study for the authors of this article. In this research, the authors found the public’s opinion and attitude regarding environmental situations and issues in Kurdistan Region-Iraq throughout a public questionnaire/survey. Around 450 people randomly participated from various geographical locations/cities of the region proportioned to the population rate regarding different demography, gender, age, and academic background. The statistical Package for the Social Sciences (SPSS) program was used to analyze their opinion. Also, the cross-tabulation method was used to understand the relationship between two or more variables. Gender, age, and educational background had effects on the participants’ attitudes toward environmental issues. Females, aged from 20 to 30, and Ph.D. degree holders were paying more attention to the environment. Geographically, the participation ratio for the Sulaimani, Erbil, Duhok, Halabja, and Kirkuk Provinces was 28.48 %, 21.95 %, 17.61%, 16.69%, and 15.00 %, respectively. High and low participation levels of the contributors are a reflection of the environmental awareness of the contributors, providing environmentalfacilities for the people, background, and culture of the community, and stability of political, economical, and social issues of the areas. Furthermore, COVID-19 affected the environment, and commonly it had a positive impact on the environment.