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

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

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

Background: Hypothyroidism is the most prevalent thyroid disorders worldwide.  Hypothyroidism manifestations are wide spectrum, affecting various systems in human body including the nervous system. Hypothyroidism can cause neuropsychiatric symptoms such as anxiety, depression and diminishing in attention, memory and executive function. Aim: to investigate the level of anxiety and depression in patients with hypothyroidism receiving levothyroxine treatment. Method: a cross-sectional study was conducted at Baghdad Center for Nuclear Medicine and Radiation Therapy from March to June 2022. The study population included patients of both genders, aged 18-65 years, diagnosed with hypothyroidism, were receiving levothyroxine treatment and

Abstract The surface of kaolin was diagnosed by an AFM and the results were shown The height of the highest peak reached by a quantity of Kaolin ‎surface is 2.5 µm, the granules, and their diameter with an average diameter of 666.1nm. Using Kaolin's adsorption properties, erythrosine was removed of its aqueous solution. It was determined that the maximal dye adsorption ranged 36.53–40.61%. ‎‎‎‎The results of using the Freundlich, Langmuir, and Temkin adsorption isotherms revealed that at temperatures of (298,308,318) K, the Freundlich model was followed, the Langmuir model did not match, and the Temkin model could only be partially applied. There is also physical adsorption. One of the three kinetic models of the

Introduction: Candida spp. has become increasingly resistant to antifungal drugs, with elevated MIC levels causing a negative medical impact and increasing the number of patients at risk of candidiasis. According to the CDC, about 7% of Candida blood samples show reduced susceptibility to fluconazole. Monitoring the antifungal resistance profile of Candida spp. is vital, as non-Albicans species may limit treatment options. Objective: Evaluate the antifungal effectiveness against clinical Candida spp. isolates of six antifungals: amphotericin B, fluconazole, voriconazole, itraconazole, caspofungin, and 5-fluorocytosine. Methods: 100 samples were collected from various clinical samples at the National Centre of Teaching Laboratories

     The aim of  this paper  is to determine the role of job engagement in the Iraqi Residency Affairs Directorate and its impact on employees, as the job engagement variable based on the Rich’s model included dimensions of cognitive engagement, emotional engagement and physical engagement. This variable has been studied in the Directorate of Residence Affairs which are one of the specialized directorates in the Iraqi Ministry of Interior.   This study  relied on a questionnaire as a main tool for measuring and collecting data based on the random sampling method . The sample size included 206 individuals among 400 individuals. However,  the respondents were 190 whereas the final

The resistance of Staphylococcus aureus to ciprofloxacin has complicated the problem of treating staphylococcal associated infections in which MRSA is the causative agent since ciprofloxacin was the drug of choice to treat such infections. Our study investigated the incidence of Ciprofloxacin resistant S. aureus isolates that were also methicillin resistant among Iraqi patients. The obtained bacterial isolates were tested for Ciprofloxacin resistance using agar dilution method and the sequence of gyrA and parC. The results revealed that about 8% of the isolated MRSA strains were Ciprofloxacin resistant and the resistance was due to mutation in gyrA rather than parC.