This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai

Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.    This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized poros

Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

Antibiotics present the greatest threat to soil and aquatic ecosystems among the different therapeutic groups of medicines (which include prescription drugs and treatments for cancer). The strongest drugs, antibiotics, have been utilized to stop the growth of microorganisms or eradicate them. Using high-performance liquid chromatography technology with fluorescence detection, the amounts of levofloxacin and tetracycline in the wastewater from three hospitals (Medical City, AlKindi, and Al-Yarmouk) were determined. Levofloxacin and tetracycline were chosen in this study because they are the most important water pollutants. These antibiotic residues were separated and measured using a gradient elution technique on a reverse-phase C18 co

Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.

Large quantities of petroleum-contaminated soil are generated with increased global energy consumption and crude oil production. This theoretical study evaluates the treatment of 1 ton of petroleum-contaminated soil using seven methods: incineration, physical washing, chemical washing, thermal pyrolysis, Fenton-oxidation-pyrolysis, the biological treatment, and asphaltenes. Data were based on experimental results from the Nahran Bin Omar oil lake in Basra Governorate, Iraq, (2019–2021). The methods were compared by waste generation, treatment cost, and duration. Results indicate that using petroleum-contaminated soil as a raw material for asphalt manufacturing is most beneficial since it is sold as a raw material. Incineration is faster a

        A newly developed analytical method was conducted for the determination of Ketotifen fumarate (KTF) in pharmaceuticals drugs via quenching of continuous fluorescence of 9(10H)-Acridone (ACD). The method was applied using flow injection system of a new homemade ISNAG fluorimeter with fluorescence measurements at ± 90◦ via 2×4 solar cell. The calibration graph was linear in the range of 1-45 mmol/L, with correlation coefficient r = 0.9762 and the limit of detection 29.785 µg/sample from the stepwise dilution for the minimum concentration in the linear dynamic ranged of the calibration graph. The method was successfully applied to the determination of Ketotifen fumarate in two different pharma