The influence of fiber orientation and water absorption on fatigue crack growth resistance for cold cure acrylic (PMMA) reinforced by chopped and woven -glass-fibers were investigated. A weight of 2 g for chopped fibers and the same weight for woven -glass-fibers (one layer) were used to prepare samples. Some of these samples would storage in dry condition; the others were immersed in water for 15 days. Fatigue test was carried out. The results shows that, for PMMA, the initial bending stress for dry specimen was 3.392 N/cm2 and the number of cycles were 1364, the initial bending stress for wet samples was 4.20 N/cm2, and the number of cycles was 2411. The samples would cut in two pieces because of the cracks would propagated fast during

Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms to

This Paper assesses the knowledge management system (KMS) requirements at Al-Ameed University concerning ISO 30401:2022. Specifically, the research aims to ascertain the degree to which international standards have been complied with and gaps that have been identified. A case study was conducted using field observations, interviews, and checklists to assess the institution's compliance with the KMS framework. The level of implementation and documentation of knowledge management processes was assessed using a seven-point scale. The findings reveal that Al-Ameed University has severe gaps in knowledge creation, sharing, and support for knowledge management in terms of strategic leadership. While certain elements like availability of r

With the increase in industry and industrial products, quantities of waste have increased worldwide, especially plastic waste, as plastic pollution is considered one of the wastes of the modern era that threatens the environment and living organisms. On this basis, a solution must be found to use this waste and recycle it safely so that it does not threaten the environment. Therefore, this research used plastic waste as an improvement material for clay soil. In this research, two types of tests were conducted, the first of which was a laboratory test, where the undrained shear strength (cohesion), compression index (Cc), and swelling index (Cr) of the improved and unimproved soils were calculated (plastic was added in pr

A field experiment was conducted at Abu-Ghrib during 2013- 2014 season to study the effect of harrowing systems on the decomposition and fermentation on organic matter(OM) when added and mixed with the soil under special technology, as well as its effect on the growth parameters and productivity of (Zea mays L. 5018). The experiment was laid out using factorial randomized complete block design (RCBD) in split-split design with three replications in SCL bare soil with a percent of moisture ranged from 16 – 18 %. The main plots were designated to the two systems of harrowing (Rotary Harrowand Disc Harrow ). The sub main plots were specified for two organic matters ( Sheep manure ,cow manure ) . Data were statistically analyzed, and

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod