Undoubtedly, Road Traffic Accidents (RTAs) are a major dilemma in term of mortality and morbidity facing the road users as well as the traffic and road authorities. Since 2002, the population in Iraq has increased by 49 percent and the number of vehicles by three folds. Consequently, these increases were unfortunately combined with rising the RTAs number, mortality and morbidity. Alongside the humanitarian tragedies, every year, there are considerable economic losses in Iraq lost due to the epidemic of RTAs. Given the necessity of understanding the contributory factors related to RTAs for the implementation by traffic and road authorities to improve the road safety, the necessity have been a rise for

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

Cluster analysis (clustering) is mainly concerned with dividing a number of data elements into clusters. The paper applies this method to create a gathering of symmetrical government agencies with the aim to classify them and understand how far they are close to each other in terms of administrative and financial corruption by means of five variables representing the prevalent administrative and financial corruption in the state institutions. Cluster analysis has been applied to each of these variables to understand the extent to which these agencies are close to other in each of the cases related to the administrative and financial corruption.           

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

The limitations of conventional cement mortar as a widely used construction material include low tensile capacity, high permeability, and susceptibility to chemical degradation. The increasing demand for durable and sustainable construction materials has led to increased attention in modifying cementitious materials through nanotechnology. This study investigates the influence of nano-silica (NS) and nano-alumina (NA) on the physical, strength-related, and durability characteristics of cement mortar to determine the optimum nanomaterial type and dosage for performance enhancement. Six mortar mixes, in addition to a reference mix, were designed and prepared by adding 1%, 1.5%, and 2% of the cement weight with NS and NA separately, an

In this study, a system of nonthermal plasma that was operated under atmospheric pressure and was powered by argon gas was employed. The particular plasma properties are affected by changes in the Ar gas flow ranges from 0.5 to 2.5 l/min, product by stream of the plasma jet that is utilized. By using the aforementioned method generated from AC and DC. After placing Ar gas as the cathode, which represents the negative pole, flows toward the anode, which is represented by a tiny metal plate of Zn measuring 6 × 1 cm2 in size, with a submerged part of 4 cm2 long, with both types of current employed having a high voltage of 13.5 kV and the frequency of AC was 30 kHz, we measured these variable parameters. It has been shown that when argon f

Reflection cracking in asphalt concrete (AC) overlays is a common form of pavement deterioration that occurs when underlying cracks and joints in the pavement structure propagate through an overlay due to thermal and traffic-induced movement, ultimately degrading the pavement’s lifespan and performance. This study aims to determine how alterations in overlay thickness and temperature conditions, the incorporation of chopped fibers, and the use of geotextiles influence the overlay’s capacity to postpone the occurrence of reflection cracking. To achieve the above objective, a total of 36 prism specimens were prepared and tested using an overlay testing machine (OTM). The variables considered in this study were the thickness of the

Reflection cracking in asphalt concrete (AC) overlays is a common form of pavement deterioration that occurs when underlying cracks and joints in the pavement structure propagate through an overlay due to thermal and traffic-induced movement, ultimately degrading the pavement’s lifespan and performance. This study aims to determine how alterations in overlay thickness and temperature conditions, the incorporation of chopped fibers, and the use of geotextiles influence the overlay’s capacity to postpone the occurrence of reflection cracking. To achieve the above objective, a total of 36 prism specimens were prepared and tested using an overlay testing machine (OTM). The variables considered in this study were the thickness of the