University of Jordan

About: University of Jordan is a education organization based out in Amman, Jordan. It is known for research contribution in the topics: Population & Health care. The organization has 7796 authors who have published 13764 publications receiving 213526 citations.

Enhanced multi-verse optimizer for task scheduling in cloud computing environments

Abstract: Cloud computing is a trending technology that allows users to use computing resources remotely in a pay-per-use model. One of the main challenges in cloud computing environments is task scheduling, in which tasks should be scheduled efficiently to minimize execution time and cost while maximizing resources’ utilization. Many meta-heuristic algorithms are used for task scheduling in cloud environments in the literature such as Multi-Verse Optimizer (MVO) and Particle Swarm Optimization (PSO). In this paper, an Enhanced version of the Multi-Verse Optimizer (EMVO) is proposed as a superior task scheduler in this area. The proposed EMVO is compared with both original MVO and the PSO algorithms in cloud environments. The results show that EMVO substantially outperforms both MVO and PSO algorithms in terms of achieving minimized makespan time and increasing resources’ utilization.

Improving financial bankruptcy prediction in a highly imbalanced class distribution using oversampling and ensemble learning: a case from the Spanish market

Abstract: Bankruptcy is one of the most critical financial problems that reflects the company’s failure. From a machine learning perspective, the problem of bankruptcy prediction is considered a challenging one mainly because of the highly imbalanced distribution of the classes in the datasets. Therefore, developing an efficient prediction model that is able to detect the risky situation of a company is a challenging and complex task. To tackle this problem, in this paper, we propose a hybrid approach that combines the synthetic minority oversampling technique with ensemble methods. Moreover, we apply five different feature selection methods to find out what are the most dominant attributes on bankruptcy prediction. The proposed approach is evaluated based on a real dataset collected from Spanish companies. The conducted experiments show promising results, which prove that the proposed approach can be used as an efficient alternative in case of highly imbalanced datasets.

Zinc and Cadmium Adsorption to Aluminum Oxide Nanoparticles Affected by Naturally Occurring Ligands

Abstract: -1 and varying ligand concentration at a solid:solution ratio of 1:1000. Adsorption isotherms showed that Zn had higher affinity to the Al 2 O 3 nanoparticle surface than Cd and that adsorption of Zn and Cd in the binary-metal system was lower than in the respective mono-metal systems. Phosphate and HA enhanced Zn and Cd adsorption in all systems, whereas citrate reduced Zn adsorption in the mono-metal system by 25% and increased adsorption in the other metal systems. Removal of Zn or Cd from the systems was generally accompanied by enhanced removal of PO 4 and HA, which may indicate enhanced adsorption due to ternary complex formation or metal-ligand precipitation. Phosphate was the most effective among the three ligands in enhancing Zn and Cd adsorption. Overall, Al

Chemical composition, antioxidant, antimicrobial and Antiproliferative activities of essential oil of Mentha spicata L. (Lamiaceae) from Algerian Saharan atlas.

Abstract: Mentha spicata (M. spicata) is a member of Lamiaceae that spreads mainly in the temperate and sub-temperate zones of the world. It is considered as a rich source of essential oils, which is widely used in pharmaceutical industries and food production. The objectives of the current study were to evaluate chemical composition, antioxidant, antimicrobial and antiproliferative activities associated with the essential oil of M. spicata cultivated in Algerian Saharan Atlas. The aerial parts of M. spicata were subjected to hydrodistillation to produce the oil. Chemical identification of the oil composition was conducted by GC and GC-MS analyses. The antioxidant activity of the hydrodistilled oil was studied using DPPH, ABTS radical scavenging and ferric-reducing power assay. Antimicrobial potential was characterized against two microorganisms, signifying Gram positive, and Gram negative bacteria, and one Candida species. The microdilution method was employed to determine the minimum inhibitory concentration (MIC). The oil’s antiproliferative effects against three human tumor cell lines were also investigated using the MTT assay, and the toxic doses that yielded 50% reduction of cell viability (LD50) were reported. Chemical analysis of the essential oil composition revealed 44 unique compounds with oxygenated monoterpenes (67.2%), followed by monoterpene hydrocarbons (20.8%), as the most abundant chemical components. Essential oil of M. spicata demonstrated moderate antioxidant activities as well as moderate to weak antimicrobial activities with best susceptibility observed for Gram positive bacteria towards the oil. In addition, anticancer activities that are associated with the oil against three human cancer cell lines were observed with LD50 values of 324 μg/mL, 279 μg/mL, 975 μg/mL against T47D, HCT-116 and MCF-7 cell lines, respectively. The results suggest that M. spicata essential oil may have potential value as a bioactive oil, for nutraceutical and medical applications, with its antioxidant, antimicrobial and antiproliferative activities.