The role of neural network for estimating real estate prices value in post COVID-19: a case of the middle east market Laith T. Khrais, Osman Saad Shidwan International Journal of Electrical and Computer Engineering, 2023 The main goal of this paper was to explore the use of an artificial neural network (ANN) model in predicting real estate prices in the Middle East market. Although conventional modeling approaches such as regression can be used in prediction, they have a weakness of a predetermined relationship between input and output. In this regard, using the ANN model was expected to reduce the bias and ensure non-linear relationships are also covered in the prediction process for more accurate results. The ANN model was created using Python v.3.10 program. The model exhibited a high correlation between predicted and actual house price data (R=0.658). In this respect, it was realized that the model could be effectively used in appraising real estate by investors. However, a major limitation of the model was realized to be a limited dataset for large and luxurious houses, which were not accurately predicted as data distribution between actual and predicted values became sparse for high house prices. A key recommendation made is that future research should include more variables related to luxurious houses and macroeconomic factors to increase the ANN model accuracy.
Planning for Future Jobs in Light of the Unified Saudi Classification of Educational Levels and Specializations—A Case Study of Graduate Students at Imam Abdul Rahman bin Faisal University Ahmed Osman Ibrahim Ahmed, Anas Satti Satti Mohammed, Osman Saad Shidwan, Mohamednour Eltathir Ahmed Abdelgadir, Manal Mohamed EL Mekebbaty, Awad Mohamed Osman Sustainability Switzerland, 2023 This study deals with the issue of planning for future jobs in light of the Unified Saudi Classification of Educational Levels and Specializations. We aimed to identify the mechanism used by graduates to choose a future job and to shed light on the Unified Saudi Classification of Educational Levels and Specializations. The problem addressed in this study is the identification of the optimal formula such that the graduate can benefit from this classification. The community studied is made up of students at the College of Applied Studies and Community Service at Imam Abdul Rahman bin Faisal University in Dammam in the period from 2019 to 2022. The sample included 129 male and female students, representing 20% of the research community. The selection was random, taking into account the homogeneity of the research community. We attempted to verify the validity of the hypothesis, stating that there is a statistically significant relationship between graduates’ preferences for their future jobs and their knowledge, represented by The Saudi Standard Classification of Scientific Levels and Specializations. A number of findings resulted from this study, most notably that there was a discrepancy regarding students’ preferences for future jobs based on their gender. We conclude with a number of recommendations, including the need to shed more light on the Unified Classification of Educational Levels and Specializations in Saudi Arabia and increase communication between scientific departments and employers.
Emergent situations for smart cities: A survey Ahmad Mohamad Al-Smadi, Mutasem K. Alsmadi, Abdel Karim Baareh, Ibrahim Almarashdeh, Hayam Abouelmagd, Osman Saad Shidwan Ahmed International Journal of Electrical and Computer Engineering, 2019 <span>A smart city is a community that uses communication and information technology to improve sustainability, livability, and feasibility. As any community, there are always unexpected emergencies, which must be treated to preserve the regular order. However, a smart system is needed to be able to respond effectively to these emergent situations. The contribution made in this survey is twofold. Firstly, it provides a comprehensive exhaustive and categorized overview of the existing surveys for smart cities. The categorization is based on several criteria such as structures, benefits, advantages, applications, challenges, issues, and future directions. Secondly, it aims to analyze several studies with respect to emergent situations and management to smart cities. The analysis is based on several factors such as the challenges and issues discussed, the solutions proposed, and opportunities for future research. The challenges include security, privacy, reliability, performance, scalability, heterogeneity, scheduling, resource management, and latency. Few studies have investigated the emergent situations of smart cities and despite the importance of latency factor for smart city applications, it is rarely discussed.</span>
