<p>In Iraq, the number of people who own vehicles has grown up significantly. However, this increment in vehicles number doesn’t accomplished by a study of roads and intersections expansion. As a result, traffic jams became a big problem that led to long waiting time at each intersection, increased car accidents, pollution, and economic problems. To solve this problem a Smart Traffic Light System (STLS) has been implemented using Arduino, camera, IR sensor to overcome traffic jams problems in Kut city – Iraq.</p>
<p class="0abstract">Due to the increased rate of fire accidents which cause many damages and losses to people souls, material, and property in Basra city. The necessity of analyzing and mining the data of the fire accidents became an urgent need to find a solution. The need increased for a solution that helps to mitigate and reduce the number of accidents. In this paper, data mining techniques and applications including data preprocessing, data cleaning, and data exploration have been applied. Data mining applications is performed to analyze and discover the hidden knowledge in ten years of data (fire accidents happened from 2010 – 2019) which is approximately 20k record of accidents. These data mining techniques along with the association rules algorithm is applied on the dataset. The applied approach and techniques resulted in discovering the patterns and the nature of the fire accidents in Basra city. It also helped to reach to recommendations and resolutions for mitigating the fire accidents and its occurrence rate.</p>
E-learning became the main medium of education in the world for the past two years. COVID-19 virus has pushed all the universities and academic institutions to utilize and activate E-learning platforms and systems. The sudden and urgent transformation from the regular traditional learning system to E-learning system has involved many challenges and limitations. Therefore, the need to evaluate and enhance the current E-learning mechanism in Iraq became very urgent and critical need. The target level was students at higher education institutes which include university students in Basra city. The data collected based on students’ evaluation and opinions about E-learning based on their interaction and usage during two years under COVID-19 spread era. This research involved applying data mining techniques to sample dataset and utilizing the obtained results as feedback for a proposed model suggested by the authors to measure adaptability. The proposed model is derived from the idea of the Technology Acceptance Model (TAM) with focus on the positivity as the main factor to measure adaptability. The results of the research showed approximate adaptation level of 52% which is very close compared to the actual situation in real life which involve limitations and challenges faced by Iraqi students.
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