current research aims to build an intellectual framework for concept of organizational forgetting, which is considered one of the most important topics in contemporary management thought, which is gain the consideration of most scholars and researchers in field of organizational behavior, which is to be a loss of intentional or unintentional knowledge of any organizational level. It turned out that just as organizations should learn and acquire knowledge, they must also forget, especially knowledge obsolete and worn out. And represented the research problem in the absence of Arab research dealing with organizational forgetting, and highlights the supporting infrastructure core, and show a close relationship with organizational le

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

This paper proposes and studies an ecotoxicant system with Lotka-Volterra functional response for predation including prey protective region. The equilibrium points and the stability of this model have been investigated analytically both locally and globally. Finally, numerical simulations and graphical representations have been utilized to support our analytical findings

Bending effects on the transmission of optical signal are investigated on a single mode
optical fiber (SMOF) of 10 m length, core radius of 5 μm and optical refractive index difference
0.003. The bending radii (R) were between 0.08 and 0.0015 m. A great decrease in the amplitude is
shown for radii below 0.01 m. Sudden break down occurs for radii less than 0.0015 m. Birefringence
(B) is difficult to measure for long fibers. Meanwhile, B was found by comparing with calibrated
fiber of the same properties but of length of 0.075 m. The results show an increase in propagation
constant (Δβ) and the decrease in beat length (Lb), and show that bending decreases the critical radius
of curvature (Rc) related to B. The chang

This paper is dealing with an experimental study to show the influence of the geometric characteristics of the vortex generators VG son the thickness of the boundary layer (∂) and drag coefficients (C_D) of the flat plate. Vortex generators work effectively on medium and high angles of attack, since they are "hidden" under the boundary layer and practically ineffective at low angles.

            The height of VGs relative to the thickness of the boundary layer enables us to study the efficacy of VGs in delaying boundary layer separation. The distance between two VGs also has an effect on the boundary layer if we take into

Toxoplasma gondii is an obligate intracellular protozoan parasite; it spreads via the circulatory system during infection and causes chronic infection in various organs. Toxoplasmosis affects nearly one third of people worldwide, especially immunocompromised people. This study aimed to determine the effect of toxoplasmosis on renal function in hemodialysis patients. Overall 300 patients referred to the Medical City, Al-Karama General Hospital, Baghdad, Iraq were enrolled from 2021 to 2022. All serum samples were tested for T. gondii immunoglobulins (IgG and IgM) antibodies, urea and creatinine levels. In patients undergoing hemodialysis, the results revealed a high positivity percentage for anti-Toxoplasma IgG. In hemodialysis patients infe

Nanoparticles are a special group of materials with unique features and extensive applications in diverse fields. The use of nanoparticles of some metals is a viable solution to stop infectious diseases due to the antimicrobial properties of these nanoparticles. The present work demonstrates the effect of silver nanoparticles (AgNPs) on the antibacterial activity of four different antibiotics (amoxicillin, ceftriaxone, chloramphenicol, and penicillin) against eleven Gram-positive and Gram-negative isolates. Disk diffusion method was used to determine the antibacterial activity of various classes of antibiotics in the absence and presence of sub-inhibitory silver nanoparticles of concentration (80 microgram/ml). A synergistic effect was o