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 Data External and Internal, Innovative Usage, Indexing, and Sources Accuracy. In addition, Artificial intelligence positively affects business performance, including Data Accuracy, Data Transparency, Data Speed, and Creative Thinking and Learning. Moreover, business intelligence has a direct and positive impact on business performance, including Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. In addition, the findings indicate that e-learning which represents system quality, information quality, and self-efficacy has a positive relationship on enhancing business performance. Interestingly, the present findings are inconsistent with those of previous studies showing the variables of interest which have no effect on e-learning and business performance. Taken together, the findings of this study suggest that firms should begin to apply processes related with applying e-learning and developing business performance. The novelty of the present study lies in highlighting the key dimensions of big data, artificial intelligence, and business intelligence when it comes to enhancing e-learning and business performance at Jordanian telecommunications industry.
Experimental activity coefficients at infinite dilution are particularly useful for calculating the parameters needed in an expression for the excess Gibbs energy. If reliable values of γ∞1 and γ∞2 are available, either from direct experiment or from a correlation, it is possible to predict the composition of the azeotrope and vapor-liquid equilibrium over the entire range of composition. These can be used to evaluate two adjustable constants in any desired expression for G E. In this study MOSCED model and SPACE model are two different methods were used to calculate γ∞1 and γ∞2
Background: Generally, genetic disorders are a leading cause of spontaneous abortion, neonatal death, increased morbidity and mortality in children and adults as well. They a significant health care and psychosocial burden for the patient, the family, the healthcare system and the community as a whole. Chromosomal abnormalities occur much more frequently than is generally appreciated. It is estimated that approximately 1 of 200 newborn infants had some form of chromosomal abnormality. The figure is much higher in fetuses that do not survive to term. It is estimated that in 50% of first trimester abortions, the fetus has a chromosomal abnormality. Aim of the study: This study aims to shed some light on the results of chromosomal studies per
... Show MoreThe current study aims to show the importance of plant products as mosquitocides against Culex quinquefasciatus. Castor oil Nanoemulsions were subedit in various ratios including castor oil, ethanol, tween 80, and deionized water by using ultrasonication. Thermodynamic, centrifugation, PH, assay which improved that the formula of 10 ml of castor oil, ethanol 5ml, tween 80 (14 ml) and deionized water 71ml was more stable than other formulas. The stable formula of castor oil nanoemulsion was characterized by transmission electron microscopy (TEM) and dynamic light scattering (DLS). Nanoemulsion droplets were spherical in shape and were found to have a Z-average diameter of 87.4nm. A concentration of ca
... Show MoreIn recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
... Show MoreThe study includs,effect of concentration of Lead 0.2 ,0.3 , 0.5, 5 , 10 mg/L and Zinc 0.1,0.5 , 2 , 4 , 8 mg/L lonely or to gether on growth green algae( Scenedesmus quadricauda var . longispina) according to the total qauntity for the cells and the adsorption of the algae to the zn,pb concentration .growth curve and dubbling time growth were calculated with or without there heavy metals . Results shows that there are significant differences (P<0.01) for growth curve and the control. (7.5201 cell /h)and with dubbling times (9.87 cell/h). The heavy metals(Pb, Zn). shows antagonistic effect when both used in media.
The results of studying the effects of M. anisopiliae spores on mosquito, C. quinquefasciatus showed a biological effects represented by immature mortality. The mortality increased proportionally with the concentrations of fungal spores, which reached (at high concentration 2×1011 spores / ml), to 86.6, 56.6% in first and late instar larvae, respectively. An important to mention that cumulative death rate was significantly associated with the time, which reached to 56% at 7 day after treatment. In addition, M. anisopiliae had a long period permanence in aquatic habitats; in which the residual effects stay 30 days in aquatic habitats after treatment at laboratory conditions. Interestingly, the long period exposure of fungal spores (30 minut
... Show MoreThe present study investigated Haematological changes in Mesopotamichthys sharpeyi, as well as determination genotoxic effects of cadmium chloride on bunni fish by using 120 fingerlings, fish were distributed randomly into four treatments in addition to control group. Fish in first group treated (T1) with cadmium 0.093mg/L with changing water and added cadmium continuously, fish in the second group treated (T2) with cadmium 0.093mg/L with changing water without adding cadmium, third treatment (T3) with cadmium 0.046mg/L with changing water and adding cadmium continuously, and fourth treatment (T4) with cadmium 0.046mg/L with changing water without adding cadmium. Results of blood picture in T1 and T3 showed a significant reduction in red bl
... Show MoreArtificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa
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