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.
Convection heat transfer in a horizontal channel provided with metal foam blocks of two numbers of pores per unit of length (10 and 40 PPI) and partially heated at a constant heat flux is experimentally investigated with air as the working fluid. A series of experiments have been carried out under steady state condition. The experimental investigations cover the Reynolds number range from 638 to 2168, heat fluxes varied from 453 to 4462 W/m2, and Darcy number 1.77x10-5, 3.95x10-6. The measured data were collected and analyzed. Results show that the wall temperatures at each heated section are affected by the imposed heat flux variation, Darcy number, and Reynolds number variation. The var
... Show MoreThe taxonomy of Ficus L., 1753 species is confusing because of the intense morphological variability and the ambiguity of the taxa. This study handled 36 macro-morphological characteristics to clarify the taxonomic identity of the taxa. The study revealed that Ficus is represented in the Egyptian gardens with forty-one taxa; 33 species, 4 subspecies and 4 varieties, and classified into five subgenera: Ficus Corner, 1960; Terega Raf., 1838; Sycomorus Raf., 1838; Synoecia (Miq.) Miq., 1867, and Spherosuke Raf.,1838; out of them seven were misidentified. Amongst, four new Ficus taxa were recently introduced to Egypt namely: F. lingua subsp. lingua Warb. ex De Wild. & T. Durand, 1901; F. pumila L., 1753; F. rumphii Blume, 1825, and F. su
... Show MoreObjective: To evaluate nurses' practices concerning isolation techniques for Adult Leukemic Patients (ALP).
Methodology: A descriptive study was carried out at the isolation rooms at leukemic wards in Baghdad Teaching
Hospitals, starting from Jan. 27th 2008 up to the 27th of Apr. 2008. To achieve the objectives of study, a non-probability
"purposive" sample of (50) nurse was selected out of four Teaching Hospitals in Baghdad city were selected according
to the criteria of the study sample.
The study instrument consisted of two major parts. It is based on the review of literature. First is concerned with
demographic data for nurses; and the second part is observational tool (checklist) is composed of (83) item. The conte
Background: Polycystic ovary syndrome is a heterogeneous disorder and its etiology appears to be complex and multifactorial; characterized by hyperandrogenism, chronic anovulation and infertility. It’s associated with evidence of low-grade chronic inflammation, as indicated by the presence of elevated levels of high sensitive C- reactive protein levels, interleukin-6 and tumor necrosis factor-α. The source of excess circulating tumor necrosis factor-α in obese Polycystic ovary syndrome patient is likely to be the adipose tissues while in lean women increased visceral adiposity has been proposed as a source of excess tumor necrosis factor-α.Objectives: to evaluate the levels of high sensitive C- reactive protein, tumor necrosis facto
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