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

Microalgae have been increasingly used for wastewater treatment due to their capacity to assimilate nutrients. Samples of wastewater were taken from the Erbil wastewater channel near Dhahibha village in northern Iraq. The microalga Coelastrella sp. was used in three doses (0.2, 1, and 2g. l^-1) in this experiment for 21 days, samples were periodically (every 3 days) analyzed for physicochemical parameters such as pH, EC, Phosphate, Nitrate, and BOD₅, in addition to, Chlorophyll a concentration. Results showed that the highest dose 2g.l^-1 was the most effective dose for removing nutrients, confirmed by significant differences (p≤0.05) between all doses. The highest removal percentage was

The study was conducted at research station A, department of field crops, college of agricultural engineering sciences, university of Baghdad during summer 2021 to evaluate the effect of boron and some growth regulators on some growth criteria and yield of soybean crop (cv. shimaa). The experiment  was carried out according to split plots by using randomized complete block design with three replications. The main plots included three concentrations of boron (75, 150 and 225) mg.L^-1, the sub-plots included three levels of growth regulators, spraying kinetin (100 mg. L^-1), spraying ethrel (200 mg.L^-1) and spraying kinetin (100 mg.L^-1) + spraying ethrel (200 mg.L^-1) as

This study aims at examining and confirming the patterns of phenetic relationships and the levels of variations within and among the species of Lotus L., 1753 in Egypt by using morphometric analysis techniques. We have evaluated 24 morphological characters from about 300 herbarium specimens representing 19 species of Lotus that are currently recognized. Based on numerical analyses of macromorphological characters (cluster analysis, principal coordinate analysis and principal component analysis), 19 species of Lotus were recognized from Egypt. These species were clustered in six species-specific groups: (I) Lotus halophilus Boiss. & Spruner, L. angustissimus L., L. glinoides Delile and L. schimperi Steud. ex Boiss., (II) Lotus glaber

Green synthesis methods have emerged as favorable techniques for the synthesis of nano-oxides due to their simplicity, cost-effectiveness, eco-friendliness, and non-toxicity. In this study, Nickel oxide nanoparticles (NiO-NPs) were synthesized using the aqueous extract of Laurus nobilis leaves as a natural capping agent. The synthesized NiO-NPs were employed as an adsorbent for the removal of Biebrich Scarlet (BS) dye from aqueous solution using adsorption technique. Comprehensive characterization of NiO-NPs was performed using various techniques such as atomic force microscopy (AFM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), Brunauer-Emmett and Teller (BET) analysis, and scanning electron microscopy (SEM). Additionally, o

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

Museum education is of great importance to an appropriate representation of museums’ collections and exhibits, including traditional fashion. Therefore, museum educators/curators need to be equipped with the most essential skills in their profession in order to adequately present the museum’s history and holdings. This could be achieved through specialized training programs. However, Arab countries are still behind in terms of museum education. Therefore, this article aims to shed light on this issue by assessing the knowledge and skills possessed by museum educators/curators and how training programs could affect them