Forward osmosis (FO) process was applied to concentrate the orange juice. FO relies on the driving force generating from osmotic pressure difference that result from concentration difference between the draw solution (DS) and orange juice as feed solution (FS). This driving force makes the water to transport from orange juice across a semi-permeable membrane to the DS without any energy applied. Thermal and pressure-driven dewatering methods are widely used, but they are prohibitively energy intensive and hence, expensive. Effects of various operating conditions on flux have been investigated. Four types of salts were used in the DS, (NaCl, CaCl2, KCl, and MgSO4) as osmotic agent and the experiments were performed at the concentration of

The biochar prepared from sawdust raw material was applied in this study for the treatment of wastewater polluted with methyl orange dye. The effect of pH (2-11), initial concertation (50-250 mg/L) and time were studied. The isotherm of Langmuir, Frendluch and temkin models studied. The Langmuir model was the best to explain the adsorption process, maximum uptake was 136.67 mg/g at 25C^o of methyl orange dye. Equilibrium reached after four hours of contact for most adsorbents.The values of thermodynamic parameters ∆G were negative at various temperatures, so the process spontaneous, while ∆H values were 16683 j/mol and ∆S values was 60.82 j/mol.k.

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

Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

Abstract This study explores the extent to which public relations (PR) departments within Traqj governmental institutions are integrating artificial intelligence (AI) applications into their communication activities. The research adresses the growing importanc of AI in enhancing administrative efficieney, communication transparency, and stakeholder engagement. Adopting a descriptive research design, the study relied on an electtonic questionnaire distributed to PR profesionals across various ministries and government bodies, collecting 100 valid responses. The indings reveal that while younger PR practitioners are actively embracing AI, older employees show limited engagement. Most participants acquired AI-related skills through self- learn

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen