Estimations of average crash density as a function of traffic elements and characteristics can be used for making good decisions relating to planning, designing, operating, and maintaining roadway networks. This study describes the relationships between total, collision, turnover, and runover accident densities with factors such as hourly traffic flow and average spot speed on multilane rural highways in Iraq. The study is based on data collected from two sources: police stations and traffic surveys. Three highways are selected in Wassit governorate as a case study to cover the studied locations of the accidents. Three highways are selected in Wassit governorate as a case study to cover the studied locations of the accidents. The selection includes Kut–Suwera, Kut–ShekhSaad, and Kut–Hay multilane divided highways located in the south of Iraq. The preliminary presentation of the studied highways was performed using Geographic Information System (GIS) software. Data collection was done to obtain crash numbers and types over five years with their locations, hourly traffic flow, and average spot speed and define roadway segments lengths of crash locations. The cumulative speed distribution curves introduce that the spot speed spectrum for each highway's whole traffic extends over a relatively wide range, indicating a maximum speed of 180 kph and a minimum speed of 30 kph. Multiple linear regression analysis is applied to the data using SPSS software to attain the relationships between the dependent variables and the independent variables to identify elements strongly correlated with crash densities. Four regression models are developed which verify good and strong statistical relationships between crash densities with the studied factors. The results show that traffic volume and driving speed have a significant impact on the crash densities. It means that there is a positive correlation between the single factors and crash occurrence. The higher volumes and the faster the driving speed, the more likely it is to crash. As the hourly traffic flow of automobile grows, the need for safe traffic facilities also extended. Doi: 10.28991/cej-2021-03091719 Full Text: PDF
Background: Kinesiologists, Physical Anthropologists, and Anatomists have all long been captivated by the structure and development of the superficial forearm flexor, the Palmaris longus.
Objective: To study the effect of Palmaris Longus on certain handwriting skills.
Subjects and Methods: Three Palmaris Longus occurrence tests were conducted on 200 students (100 males and 100 females) affiliated to Colleges of Medicine of Baghdad University then the participants were tested for certain handwriting skills to correlate the presence of Palmaris Longus in the dominant side with handwriting.
Results: 89% of all subject
... Show MoreIn this paper, the Normality set will be investigated. Then, the study highlights some concepts properties and important results. In addition, it will prove that every operator with normality set has non trivial invariant subspace of .
The notion of a Tˉ-pure sub-act and so Tˉ-pure sub-act relative to sub-act are introduced. Some properties of these concepts have been studied.
Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor
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