Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

A Longitudinal opening is used to construct hollow core beam is a cast in site or precast or pre stressed concrete member with continuous voids provided to reduce weight, cost and, as a side benefit, to use for concealed electrical or mechanical runs. Primarily is used as floor beams or roof deck systems. This study investigate the behavior of six beams (solid or with opening) of dimension (length 1000 x height 180 x width120mm) simply support under partial uniformly distributed load, four of these beam contain long opening of varied section (40x40mm) or (80x40mm). The effect of vertical steel reinforcing, opening size and orientations are investigated to evaluate the response of beams. The experimental behavior based on load-deflection

Background: Angiogenesis is defined as the formation of new blood vessels. However, angiogenesis in cancer will lead to tumour growth and metastasis. Therefore, anti-angiogenesis is one of the ways to slow down growth and spreading of tumour. Moringa oleifera is also known as a “Miracle tree” which has high nutritive value and various therapeutics effect in different parts of the plant. This study aims to determine the anti-angiogenic property of Moringa oleifera leaves extract by using chick chorioallantoic membrane (CAM) assay. Materials and Methods: The extracts were prepared by decoction method using methanol and water. The qualitative phytochemical screening was carried out for

Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishman

Lactiplantibacillus plantarum‎, one of lactic acid bacteria (LAB), is found in various foods, ‎‎including dairy products, meat, and vegetables, and most of these bacteria offer beneficial ‎‎effects to humans and animals as potential probiotics with broad-spectrum antimicrobial ‎‎activities. The aim of this study was evaluating the antibacterial efficacy of L. ‎plantarum‎ ‎against ‎some foodborne bacteria isolated from dairy products. This research involved 34 dairy ‎products, ‎including local and imported milk, cheese, and yogurt sold locally in Baghdad ‎province, Iraq, during May ‎‎2022. For the isolation of L. ‎plantarum‎, a special medium called ‎MRS (de Man Rogosa and ‎Sharpe) was applied. Colonie

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm