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 models for a variety of tasks under the control of a unified architecture for each proposed model.
The current research aims to identify the level of compulsive buying behavior and Histrionic Personality among a sample of primary school teachers for the academic year (2021-2022) and in the light of some variables
(sex, marital status). To measure the Histrionic Personality, the researcher applied two scales to a random stratified sample of (200) male and female teachers. The results showed statistically significant differences in the level of compulsive buying behavior according to the gender variable and in favor of female teachers. There are no statistically significant differences in terms of marital status. There are statistically significant differences in the Histrionic Personality based on gender variables in favor of f
... Show MoreThis research explores the integration of multi-walled carbon nanotubes (MWCNTs) into polyvinyl alcohol (PVA) matrices to enhance their structural, electrical and thermal properties. Fourier-transform infrared spectroscopy analysis confirms the formation of a PVA-MWCNT complex. The incorporation of MWCNTs, even at low concentrations, leads to increased electrical conductivity, making the composite material suitable for applications in flexible electronics and sensors. Dielectric studies reveal frequency-dependent electrical behavior, attributed to interfacial polarization, suggesting potential uses in capacitors and energy storage devices. The introduction of MWCNTs into PVA leads to N-type semiconductor behavior, as indicated by the Hall c
... Show MoreAn extensive program of laboratory testing was conducted on ring footing rested on gypseous soil brought from the north of Iraq (Salah El-Deen governorate) with a gypsum content of 59%. There are limited researches available, and even fewer have been done experimentally to understand how to ring footings behave; almost all the previous works only concern the behavior of ring footing under vertical loads, Moreover, relatively few studies have examined the impact of eccentric load and inclined load on such footing. In this study, a series of tests, including dry and wet tests, were carried out using a steel container (600×600×600) mm, metal ring footing (100 mm outer diameter and 40 mm inner diameter) was placed in the m
... Show MoreSoil tillage is a critical agricultural practice that creates favorable conditions for seedbed preparation and plant growth. This study presents an innovative application of artificial intelligence (AI) in agriculture by employing the YOLOv7 algorithm to classify and assess post-tillage soil surface conditions, a domain underexplored in current research. The integration of mechanical operation parameters with AI-based image classification enables optimization of tillage quality and mitigation of soil compaction, highlighting the novelty of this approach. The study aims to improve the efficiency of moldboard plow operations by examining the effects of tillage speed and depth on soil clod distribution, fuel consumption, and power requ
... Show MoreThis abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
... Show MoreThe main objective and primary concern to every investor not only to achieve a greater return on his or her investments, but also to create the largest possible value of these investments the, researchers and those interested in the field of investment and financial analysis try to develop standards for performance valuation is guided through the  
... Show Moreأستهدفت الدراسة اختبار أثر التوجه السوقي والتزام العاملين على أداء المنظمة المسوقة لخدمات النقل الجوي. حيث تم اختيار شركة الخطوط الجوية الملكية الأردنية كمجال تطبيقي.وقد اعتمدت الدراسة في قياس المتغيرات على مقاييس مختبرة وقد تأكد صحتها وثباتها لقياس المتغيرات في البيئة الحالية. وقد بينت نتائج التحليل الإحصائي الذي استخدمت فيه أساليب إحصائية مختلفة بالاستعانة ببرنامج SPSS))