Most of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment.  This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020.  The results revealed that positive and negative shocks for both exchange rates have unequal effects on

The research aims to verify that there is an influence between innovative marketing and the organization's reputation by brand mediation.

The research problem is that the Oil Marketing Company (SOMO) needs innovative, unconventional methods in marketing its products and improving its reputation by adopting a solid brand that adds value to the product.

The importance of the research: The importance of the research is highlighted as it deals with essential variables in business organizations that help increase customer loyalty by adopting a distinctive brand.

The research started from four main hypotheses to explore correlations and influence between researc

The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

Background: Blood group system and the ability to taste phenylthiocarbamide (PTC) are the most studied traits in human genetics which have been extensively used in describing genetic variations among human populations around the world that may had an effect on dental caries. The aims of present study were to investigate the caries experience among students with different bitter taste threshold in relation to blood type. Materials and Methods: The sample of present study includes dental students female aged19-21 years. The diagnosis of dental caries was done according to the criteria of Manjia et al, 1989 recording decayed lesion by severity (D1-4) MFS. Furthermore, bitter taste sensitivity was measured according to PTC (phenylthiocarbamid

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

This study reports on natural convection heat transfer in a square enclosure of length (L=20 cm) with a saturated porous medium (solid glass beads) having same fluid (air) at lower horizontal layer and free air fill in the rest of the cavity's space. The experimental work has been performed under the effects of heating from bottom by constant heat flux q=150,300,450,600 W/m2 for four porous layers thickness Hp (2.5,5,7.5,1) cm and three heaters length δ(20,14,7) cm. The top enclosure wall was good insulated and the two side walls were symmetrically cooled at constant temperature. Four layers of porous media with small porosity, Rayleigh number range (60.354 - 241.41) and (Da) 3.025x10-8 has been investigated. The obtained data of temperatu

Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota

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

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i