The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

The removal of cadmium ions from simulated groundwater by zeolite permeable reactive barrier was investigated. Batch tests have been performed to characterize the equilibrium sorption properties of the zeolite in cadmium-containing aqueous solutions. Many operating parameters such as contact time, initial pH of solution, initial concentration, resin dosage and agitation speed were investigated. The best values of these parameters that will achieved removal efficiency of cadmium (=99.5%) were 60 min, 6.5, 50 mg/L, 0.25 g/100 ml and 270 rpm respectively. A 1D explicit finite difference model has been developed to describe pollutant transport within a groundwater taking the pollutant sorption on the permeable reactive barrier (PRB), which i

In this paper the process of metal ions extraction (Zn(II) and Cu(II)) was studied in PEG-KCl aqueous two phase system was investigated without using an extracting agent. The experimental runs were performance at constant temperature (25 ^oC), constant mixing time (30 min), and constant PH of the solution (about 3). The effect of KCl salt concentration (from 10% to 25%), volumetric phase ratio of PEG solution to KCl solution (from 0.5 to 2), and the initial metal ion concentration (from 0.25 ml to 2 ml of 1 gm/L solution) were investigated on the percent extraction of Zn(II) and Cu(II). The results indicated that the percent extraction of metal ions increase with increasing of salt concentration and phase ratio, and slightly de

Brainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's

A procedure, depending on the derivatization and determination of aniline was depicted andvalidated in this study. 8-hydroxyquinoline (8-HQ) was used as the derivatizing agent for thedetermination of aniline. An optimization study was performed for the derivatization reaction, i.e.,the diazonium coupling reaction, the optimum parameters were as follows: 22 mM of hydrochloricacid, 54mM of sodium hydroxide, and 1.8mM of sodium nitrate. The optimization study of themethod of cloud point extraction (CPE) revealed that the extraction solvent was 0.5 ml of Triton X-100, the optimum temperature was 90 °C, and the incubation time was 25 min. The linearity,correlation coefficients, molar absorptivities, and limits of detection were improved using t

This research presents the possibility of using banana peel (arising from agricultural production waste) as biosorbent for removal of copper from simulated aqueous solution. Batch sorption experiments were performed as a function of pH, sorbent dose, and contact time. The optimal pH value of Copper (II) removal by banana peel was 6. The amount of sorbed metal ions was calculated as 52.632 mg/g. Sorption kinetic data were tested using pseudo-first order, and pseudo-second order models. Kinetic studies showed that the sorption followed a pseudo second order reaction due to the high correlation coefficient and the agreement between the experimental and calculated values of q_e. Thermodynamic parameters such as enthalpy change (ΔH

Activated carbon derived from Ficus Binjamina agro-waste synthesized by pyro carbonic acid microwave method and treated with silicon oxide (SiO2) was used to enhance the adsorption capability of the malachite green (MG) dye. Three factors of concentration of dye, time of mixing, and the amount of activated carbon with four levels were used to investigate their effect on the MG removal efficiency. The results show that 0.4 g/L dosage, 80 mg/L dye concentration, and 40 min adsorption duration were found as an optimum conditions for 99.13% removal efficiency. The results also reveal that Freundlich isotherm and the pseudo-second-order kinetic models were the best models to describe the equilibrium adsorption data.

The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company