Peak ground acceleration (PGA) is one of the critical factors that affect the determination of earthquake intensity. PGA is generally utilized to describe ground motion in a particular zone and is able to efficiently predict the parameters of site ground motion for the design of engineering structures. Therefore, novel models are developed to forecast PGA in the case of the Iraqi database, which utilizes the particle swarm optimization (PSO) approach. A data set of 187 historical ground-motion recordings in Iraq’s tectonic regions was used to build the explicit proposed models. The proposed PGA models relate to different seismic parameters, including the magnitude of the earthquake (Mw), average shear-wave velocity (VS30), focal depth (FD

This paper describes a practical study on the impact of learning's partners, Bluetooth Broadcasting system, interactive board, Real – time response system, notepad, free internet access, computer based examination, and interaction classroom, etc, had on undergraduate student performance, achievement and involving with lectures. The goal of this study is to test the hypothesis that the use of such learning techniques, tools, and strategies to improve student learning especially among the poorest performing students. Also, it gives some kind of practical comparison between the traditional way and interactive way of learning in terms of lectures time, number of tests, types of tests, student's scores, and student's involving with lectures

Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

One of the most recent research areas in subsurface applications, including well drilling, is the use of eco-friendly and sustainably synthesized nanoparticles to improve drilling fluid efficiency. Typically, Shale formations present significant challenges to traditional drilling fluids, including fluid infiltration and shale swelling, which jeopardize wellbore stability. Although water-based drilling fluids (WBM) are environmentally preferred, their performance often requires enhancement through advanced additives. This study thus examines the synthesis of silica (SiO₂) and alumina (Al₂O₃) nanoparticles (NPs) using sustainable methods, employing Iraqi bentonite for silica and recycled aluminum scrap for alumina, to improve WBM effici

The demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB

The present study aims to identify wisdom-based thinking and its relationship to psychological capital. It further aims to find out the differences in the level of wisdom-based thinking and psychological capital according to the variables of gender and specialization (scientific, humanities). To achieve this, the study has been conducted on a sample of (380) male and female students. The two scales, wisdom-based thinking and psychological capital are implemented to the sample after being constructed by the researcher and after ensuring their psychometric characteristics' suitability for the study's aims. Results concerning the first aim have shown that there is a significant relationship among students. The second aim has revealed that t

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit