Super learner implementation in corrosion rate prediction

This thesis proposes a new machine learning model for predicting the corrosion rate of 3C steel in seawater. The corrosion rate of a material depends not just on the nature of the material but also on the material\u27s environmental conditions. The proposed machine learning model comes with a selection framework based on the hyperparameter optimization method and a performance evaluation metric to determine the models that qualify for further implementation in the proposed models’ ensembles architecture. The major aim of the selection framework is to select the least number of models that will fit efficiently (while already hyperparameter-optimized) into the architecture of the proposed model. Subsequently, the proposed predictive model is fitted on some portion of a dataset generated from an experiment on corrosion rate in five different seawater conditions. The remaining portion of this dataset is implemented in estimating the corrosion rate. Furthermore, the performance of the proposed models’ predictions was evaluated using three major performance evaluation metrics. These metrics were also used to evaluate the performance of two hyperparameter-optimized models (Smart Firefly Algorithm and Least Squares Support Vector Regression (SFA-LSSVR) and Support Vector Regression integrating Leave Out One Cross-Validation (SVR-LOOCV)) to facilitate their comparison with the proposed predictive model and its constituent models. The test results show that the proposed model performs slightly below the SFA-LSSVR model and above the SVR-LOOCV model by an RMSE score difference of 0.305 and RMSE score of 0.792. Despite its poor performance against the SFA-LSSVR model, the super learner model outperforms both hyperparameter-optimized models in the utilization of memory and computation time (graphically presented in this thesis)

Response surface modelling and optimisation of biodiesel production from Manilkara Zapota L. seed oil

724-729Biodiesel production from non-edible oils is one of the prominent research avenues being exploited in recent times to achieve energy and environmental sustainability. The aim of this study is to model and optimise the production of biodiesel from the reaction of ethanol with Sapota (Manilkara Zapota L.) seed oil using potassium hydroxide (KOH) as catalyst. A quadratic response surface model has been developed and validated. Analysis of variance (ANOVA) reveals that the model is significant. The standard deviation is 3.76% and the coefficient of determination (R2) is 0.8438. Numerical optimisation reveal that the optimal biodiesel yield of 89.57% can be achieved at an ethanol to oil molar ratio is 6.58, catalyst amount of 1.07 wt% and temperature of 64.77C. Parametric studies reveal that the yield of biodiesel initially increases with increasing ethanol-oil ratio and catalyst amount but drops off gradually beyond the region of optimality. Temperature has a slight positive effect on the process

Development of high-performance self compacting concrete using eggshell powder and blast furnace slag as partial cement replacement

This study aimed to examine the properties of self-compacting concrete (SCC) developed using eggshell powder (ESP) and granulated ground blast furnace slag (GGBFS) as partial cement replacement. The coarse aggregate impact value was 21.6% and the water absorption of the fine aggregates was 24 wt%. 10 wt% partial replacement was optimal for flow-ability and workability. SCC with 20 wt% partial replacements had the highest compressive strength at 41.34 kN/mm2 and 42.4 kN/mm2 for ESP and GGBFS respectively after 28 days of curing. SCC with 20 wt% partial replacements had the highest flexural strength at 3.2 kN/mm2 for both ESP and GGBFS after 28 days of curing. From the microstructural analysis, partial replacement with mineral admixtures improved the interfacial interactions between constituents of the concrete and GGBFS SCC gave a better interfacial interaction between the concrete constituents than ESP SCC. In summary, GGBFS had better fresh, hard and microstructural properties than ESP

A Review: The Past, Present and Future of Radio Frequency Spectrum in Nigeria, Canada, United Kingdom, Ghana

Since the time of inception of cellular analogue telephony in 1985, there has been an unending improvement taking shape from the first generation to the second generation and now the fifth generation. The cellular mobile concept has been a major transformer of the human existence from the time of Stone Age to the Bronze Age. But this cellular mobile concept needed a system that would enable its technology to be readily accessible, the radio frequency spectrum. With the advancement in the wireless communication, the need for proper sharing of the RF spectrum became an issue since it is limited. The possibility of being able to share this spectrum to house all the forms of wireless communication ranging from mobile telephony, radio and TV broadcasting, broadband links etc. become a top issue in the research work. With this paper, we tend to study the past, the present and the future work done towards achieving a better radio frequency spectrum usage and make some recommendations for future growt

Design and Implementation of a Cattle Grazing Tracking and Anti-theft Alert GPS/GSM Collar, Leveraging on Improvement in Telecom and ICT Infrastructure

The objective of this study is to develop a cattle monitoring system for tracking cattle combating rustling in extensive grazing areas, grazing reserves, grazing routes and ranches. The system is majorly made up of a collar that consists majorly of a GSM & GPS module. This system would not only combat cattle rustling activities but would also servas an anti-theft system. When cattle wearing the collar exits the virtual fences, an SMS containing the coordinates of the collar is sent to the cattle farmer enabling him to check the cattle’s position and ward off a potential danger or theft. SMS alerts are also sent to the farmer also when the battery of the collar is low, the collar is unbuckled from the cattle and when the farmer calls the collar to know its location. This system would provide cattle farmers with the opportunity to fully monitor their herd within a particular grazing region

Metal-organic polyhedra (MOPs) as emerging class of metal-organic frameworks for CO2 photocatalytic conversions : current trends and future outlook

DATA AVAILABILITY : No data was used for the research described in the article.Please read abstract in the article.https://www.elsevier.com/locate/jcouhj2024PhysicsNon

Development of high-performance self compacting concrete using eggshell powder and blast furnace slag as partial cement replacement Gender Implications

This study aimed to examine the properties of self-compacting concrete (SCC) developed using eggshell powder (ESP) and granulated ground blast furnace slag (GGBFS) as partial cement replacement. The coarse aggregate impact value was 21.6% and the water absorption of the fine aggregates was 24 wt%. 10 wt% partial replacement was optimal for flow-ability and workability. SCC with 20 wt% partial replacements had the highest compressive strength at 41.34 kN/mm2 and 42.4 kN/mm2 for ESP and GGBFS respectively after 28 days of curing. SCC with 20 wt% partial replacements had the highest flexural strength at 3.2 kN/mm2 for both ESP and GGBFS after 28 days of curing. From the microstructural analysis, partial replacement with mineral admixtures improved the interfacial interactions between constituents of the concrete and GGBFS SCC gave a better interfacial interaction between the concrete constituents than ESP SCC. In summary, GGBFS had better fresh, hard and microstructural properties than ESP

RSM and ANN modelling of the mechanical properties of self-compacting concrete with silica fume and plastic waste as partial constituent replacement

In this study, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) was used to predict the mechanical properties of self‐compacting concrete (SCC) with silica fume as partial cement replacement and Polyethylene terephthalate (PET) solid waste as partial sand replacement. PET plastic was varied between 0 and 20 wt% while the silica fume was varied between 0 and 40 wt%. The parameters investigated were the compressive strength, tensile strength and impact strength of SCC. The RSM model was fairly accurate (R2 ≥ 0.92) in predicting the mechanical properties. The model was statistically significant (p‐value 0.93) for training, testing and validation. Parity plots revealed that both the ANN and RSM models do not have any prediction bias. However, the ANN model is superior because of its higher accuracy and the use of admixtures enhanced the workability suitability for dataset. The 3D microstructural analysis showed that the interfacial adhesion between the aggregates and the cementitious materials reduced at increased partial replacement leading to a decrease in the strengt

IoT-Enabled Alcohol Detection System for Road Transportation Safety in Smart City

In this paper, an alcohol detection system was developed for road transportation safety in smart city using Internet of Things (IoT) technology. Two Blood Alcohol Content (BAC) thresholds are set and monitored with the use of a microcontroller. When the first threshold is reached, the developed system transmits the BAC level of the driver and the position coordinates of the vehicle to the central monitoring unit. At the reach of the second BAC threshold, the IoT-enabled alcohol detection system shuts down the vehicle’s engine, triggers an alarm and puts on the warning light indicator. A prototype of this scenario is designed and implemented such that a Direct Current (DC) motor acted as the vehicle’s engine while a push button served as its ignition system. The efficiency of this system is tested to ensure proper functionality. The deployment of this system will help in reducing the incidence of drunk driving related road accidents in smart cities