In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

Background: Diabetes mellitus has been suggested
to be the most common metabolic disorder
associated with magnesium deficiency, and because
available data suggest that adverse outcomes are
associated with hypomagnesemia, it is prudent that
routine surveillance for hypomagnesemia be done
and the condition be treated whenever possible.
Aim of the study:To explore the serum Mg
concentrations of diabetic patients and healthy
controls in our locality.
Mehtods: One hundred and forty four diabetic
patients (22 with type I and 122 with type II diabetes
mellitus) recruited from the outpatient diabetes clinic
at the Specialized Center For Endocrine DiseasesBaghdad (62 patients), National Diabetes Center-Al

The integration of gender in urban studies is considered a goal and objective to build a society characterized by justice and equality. It further allows all its residents to enjoy the opportunities to live in a safe urban life. Based on the that, the limitations of the research and its field of interest related to the relationship between gender and urban studies have become clear. The insufficient knowledge in this regard considers gender as a concept that does not exist in itself, but rather overlaps and intersects with several concepts and studies, including urban studies. Thus, it has become necessary to adopt a descriptive methodology that helps reach a theoretical framework to explain the beginnings of such an interaction and inte

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

MCM-48 zeolites have unique properties from the surfaces and structure point of view as it’s shown in the results ,and unique and very sensitive to be prepared, have been experimentally prepared and utilized as a second-generation/ acid - catalyst for esterification reactions of oleic acid as a model oil for a free fatty acid source with Ethanol. The characterization of the catalyst used in the reaction has been identified by various methods indicating the prepared MCM-48 is highly matching the profile of common commercial MCM-48 zeolite. The XRF results show domination of SiO₂ on the chemical structure with 99.1% and  agreeable with the expected from MCM-48 for it's of silica-based, and the SEM results show the cubic c

Background: A minimally invasive antral membrane balloon elevation (MIAMBE) has been introduced to overcome the invasiveness of modified Caldwell-Luc (lateral approach) and the drawbacks of the osteotome (summers' technique) in maxillary sinus floor elevation surgery. Materials and methods: A total of 13 adult Iraqi patients aged 28-55 years, 4 males and 9 females underwent sinus floor elevation surgery via crestal approach by using sinus balloon technique. A panoramic radiograph and (Cone beam computed tomography (CBCT)/or medical CT scan) were obtained before and after surgery. Postoperative gained bone was assessed and the patient reactions including pain, nasal bleeding, and ecchymosis were recorded. The whole follow up period was 1yea