Sensitivity analysis-based control strategies of a mathematical model for reducing marijuana smoking

The aim of the current study is to reduce marijuana use among the general population. Because marijuana is an illegal narcotic with numerous negative health effects, it continues to pose a severe threat to public health in emerging nations. In this article, a modified mathematical model of the non-users, experimental users, recreational users, and addict's (NERA) model for marijuana consumption is established by incorporating a new compartment that represents the individuals who are being moved to jail by police intervention. The overall population of humans is divided into five main components: the non-smoker's compartment, experimental smoker's compartment, recreational smoker's compartment, addicted smoker's compartment, and prisoner's compartment. The novelty of this work is to modify the NERA model for marijuana consumption and validate the modified model. Furthermore, with the help of sensitivity analysis, control strategies for marijuana consumption in the population are addressed. The invariant region and the basic reproductive number (R0) are those parts that are needed for the validation of the proposed model. For the numerical simulation of the given model, the 4th-order Runge Kutta method will be used with the help of MATLAB to examine how the control strategies will play a role in marijuana consumption

Error Reduction Framework for In-Line Inspection Tools Corrosion Measurements

Measurements error reduction is one of the biggest concerns in metrology. Mis-estimation caused by error in measurements can lead to misleading decisions, economic and environmental loss, or system failure

Error Reduction Framework for In-Line Inspection Tools Corrosion Measurements

Measurements error reduction is one of the biggest concerns in metrology. Mis-estimation caused by error in measurements can lead to misleading decisions, economic and environmental loss, or system failure

Comparative Calibration of Corrosion Measurements Using K-Nearest Neighbour Based Techniques

Every measuring equipment or inspection tool is known to have its own accuracy, which may affect the reliability of its measurements. This includes oil and gas pipeline corrosion defects measurements. The inspection tolerance occurred in the measurements should be treated carefully for each equipment to prevent misinterpretation of the data which could lead to incorrect assessment. This paper presents a comparison between two K-Nearest Neighbour (KNN) interpolation techniques used to calibrate corrosion measurements collected by Magnetic Flux Leakage Intelligent Pig (MFL-IP) with the readings of Ultrasonic Testing (UT) scan device. The comparison has relied on the position of the interpolators, the weight sequence, and the error in the final enhanced metrics compared to the original measurements. Both techniques have the potential to calibrate and enhance IP measurements, with relative advantage for one technique in reducing over fitting problem. This enhancement will be used to improve the integrity assessment report that depends on the disturbed corrosion metrics of oil and gas pipelines, to decide whether the pipeline is fit for service or needs certain maintenance

Comparative Calibration of Corrosion Measurements Using K-Nearest Neighbour Based Techniques

Every measuring equipment or inspection tool is known to have its own accuracy, which may affect the reliability of its measurements. This includes oil and gas pipeline corrosion defects measurements. The inspection tolerance occurred in the measurements should be treated carefully for each equipment to prevent misinterpretation of the data which could lead to incorrect assessment. This paper presents a comparison between two K-Nearest Neighbour (KNN) interpolation techniques used to calibrate corrosion measurements collected by Magnetic Flux Leakage Intelligent Pig (MFL-IP) with the readings of Ultrasonic Testing (UT) scan device. The comparison has relied on the position of the interpolators, the weight sequence, and the error in the final enhanced metrics compared to the original measurements. Both techniques have the potential to calibrate and enhance IP measurements, with relative advantage for one technique in reducing over fitting problem. This enhancement will be used to improve the integrity assessment report that depends on the disturbed corrosion metrics of oil and gas pipelines, to decide whether the pipeline is fit for service or needs certain maintenance

Evaluation of postgraduate academic performance using artificial intelligence models

10.1016/j.aej.2022.03.021ALEXANDRIA ENGINEERING JOURNAL61129867-987

Implementation of FeSO4·H2O as an Eco-Friendly Coagulant for the Elimination of Organic Pollutants from Tertiary Palm Oil Mill Effluent: Process Optimization, Kinetics, and Thermodynamics Studies

The biologically treated palm oil mill effluent (POME) urges further treatment to minimize the residual pollutant concentration for safe discharge in the nearest watercourse. In the present study, the post-treatment of biologically treated POME was conducted using ferrous sulfate monohydrate (FeSO4·H2O) as a coagulant. The influence of the FeSO4·H2O coagulation of POME was determined on the elimination of biochemical oxygen demand (BOD), suspended solids (SS), and chemical oxygen demand (COD) with varying flocculation time (min), slow mixing speed (rpm), coagulant doses (g/L) and pH. The FeSO4·H2O coagulation–flocculation experimental conditions were designed following the central composite design (CCD) of experiments and optimized by employing response surface methodology (RSM) based on the optimal SS, COD, and BOD elimination from POME. The maximum BOD, SS, and COD elimination achieved were about 96%, 97%, and 98%, respectively, at the optimized experimental condition. The surface morphology and elemental composition analyses of raw FeSO4·H2O and sludge generated after coagulation revealed that the FeSO4·H2O effectively removed the colloidal and suspended particles from POME. The well-fitted kinetic model equation was the pseudo-second-order kinetic equation to describe the FeSO4·H2O coagulation–flocculation behavior. The thermodynamics properties analyses revealed that the FeSO4·H2O coagulation of POME was non-spontaneous and endothermic. The residual SS, COD, and BOD in treated POME were determined to be 28.27 ± 5 mg/L, 147 ± 3 mg/L, and 6.36 ± 0.5 mg/L, respectively, lower the recommended discharged limits as reported by the Department of Environment (DoE), Malaysia

Implementation of FeSO₄·H₂O as an Eco-Friendly Coagulant for the Elimination of Organic Pollutants from Tertiary Palm Oil Mill Effluent: Process Optimization, Kinetics, and Thermodynamics Studies

The biologically treated palm oil mill effluent (POME) urges further treatment to minimize the residual pollutant concentration for safe discharge in the nearest watercourse. In the present study, the post-treatment of biologically treated POME was conducted using ferrous sulfate monohydrate (FeSO4·H2O) as a coagulant. The influence of the FeSO4·H2O coagulation of POME was determined on the elimination of biochemical oxygen demand (BOD), suspended solids (SS), and chemical oxygen demand (COD) with varying flocculation time (min), slow mixing speed (rpm), coagulant doses (g/L) and pH. The FeSO4·H2O coagulation–flocculation experimental conditions were designed following the central composite design (CCD) of experiments and optimized by employing response surface methodology (RSM) based on the optimal SS, COD, and BOD elimination from POME. The maximum BOD, SS, and COD elimination achieved were about 96%, 97%, and 98%, respectively, at the optimized experimental condition. The surface morphology and elemental composition analyses of raw FeSO4·H2O and sludge generated after coagulation revealed that the FeSO4·H2O effectively removed the colloidal and suspended particles from POME. The well-fitted kinetic model equation was the pseudo-second-order kinetic equation to describe the FeSO4·H2O coagulation–flocculation behavior. The thermodynamics properties analyses revealed that the FeSO4·H2O coagulation of POME was non-spontaneous and endothermic. The residual SS, COD, and BOD in treated POME were determined to be 28.27 ± 5 mg/L, 147 ± 3 mg/L, and 6.36 ± 0.5 mg/L, respectively, lower the recommended discharged limits as reported by the Department of Environment (DoE), Malaysia